Статті в журналах: "Breath cancer"

1

Bukreyeva, Ye B., A. A. Bulanova, and Yu V. Kistenev. "APPLYING OF GAS ANALYSIS IN DIAGNOSIS OF BRONCHOPULMONARY DISEASES." Bulletin of Siberian Medicine 13, no. 5 (October 28, 2014): 122–29. http://dx.doi.org/10.20538/1682-0363-2014-5-122-129.

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Bronchopulmonary system diseases are on the first place among the causes of people's death. Most of methods for lung diseases diagnosis are invasive or not suitable for children and patients with severe disease. One of the promising methods of clinical diagnosis and disease activity monitoring of bronchopulmonary system is analyzing of human breath. Directly exhaled breath or exhaled breath condensate are using for human breaths analyzing. Analysis of human breath can apply for diagnostic, long monitoring and evaluation of efficacy of the treatment bronchopulmonary diseases. Differential diagnostic between chronic obstructive lung disease (COPD) and bronchial asthma is complicated because they have differences in pathogenesis. Analysis of human breath allows to explore features of COPD and bronchial asthma and to improve differential diagnostic of these diseases. Human breaths analyzing can apply for diagnostic dangerous diseases, such as tuberculosis, lung cancer. The analysis of breath air by spectroscopy methods is new noninvasive way for diagnosis of bronchopulmonary diseases.

2

Haick, Hossam, and Dina Hashoul. "Lung cancer breath tests." Expert Review of Respiratory Medicine 13, no. 7 (May 8, 2019): 597–99. http://dx.doi.org/10.1080/17476348.2019.1614918.

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3

Polaka, Inese, Manohar Prasad Bhandari, Linda Mezmale, Linda Anarkulova, Viktors Veliks, Armands Sivins, Anna Marija Lescinska, et al. "Modular Point-of-Care Breath Analyzer and Shape Taxonomy-Based Machine Learning for Gastric Cancer Detection." Diagnostics 12, no. 2 (February 14, 2022): 491. http://dx.doi.org/10.3390/diagnostics12020491.

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Background: Gastric cancer is one of the deadliest malignant diseases, and the non-invasive screening and diagnostics options for it are limited. In this article, we present a multi-modular device for breath analysis coupled with a machine learning approach for the detection of cancer-specific breath from the shapes of sensor response curves (taxonomies of clusters). Methods: We analyzed the breaths of 54 gastric cancer patients and 85 control group participants. The analysis was carried out using a breath analyzer with gold nanoparticle and metal oxide sensors. The response of the sensors was analyzed on the basis of the curve shapes and other features commonly used for comparison. These features were then used to train machine learning models using Naïve Bayes classifiers, Support Vector Machines and Random Forests. Results: The accuracy of the trained models reached 77.8% (sensitivity: up to 66.54%; specificity: up to 92.39%). The use of the proposed shape-based features improved the accuracy in most cases, especially the overall accuracy and sensitivity. Conclusions: The results show that this point-of-care breath analyzer and data analysis approach constitute a promising combination for the detection of gastric cancer-specific breath. The cluster taxonomy-based sensor reaction curve representation improved the results, and could be used in other similar applications.

4

Abdah-Bortnyak, R. V., H. Haick, S. Billan, G. Peng, E. Trock, N. Shachada, and A. Kuten. "Sniffing out cancer from real breath samples by means of nanomaterial-based electronic nose device." Journal of Clinical Oncology 27, no. 15_suppl (May 20, 2009): e17552-e17552. http://dx.doi.org/10.1200/jco.2009.27.15_suppl.e17552.

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e17552 Background: Several studies have shown that characteristic patterns of volatile organic compounds (VOCs) appear to be elevated in the alveolar breath of cancer patients, as compared to healthy controls. It has been shown, that VOCs’ composition acts as a fingerprint for the distinction of a certain cancer from other cancers, including the cases where various cancers have similar type of biomarkers. The goal of the current study is to establish a background to ultimately achieve a simple-to-use device that can detect such patterns of cancer when exhaling into it. Methods: Breath samples were collected from 40 healthy volunteers and 75 patients having known conditions in six main categories: (I) 40 healthy controls; (II) 30 patients with lung cancer; (III) 15 patients with breast cancer; (IV) 20 patients with colon cancer; (V) 5 patients with prostate cancer; and (VI) 5 patients with head and neck cancer. The breath of the volunteers was examined by means of gas chromatography linked with mass spectrometry technique (GC-MS) as well as by an electronic nose device that is based on molecularly modified Au nanoparticles to check the feasibility of the electronic nose in cancer detection via breath samples Results: GC-MS results showed that each category of cancer has a unique pattern (or mixture) of VOCs. In parallel to these findings, results indicate the ability of nanomaterial-based electronic nose devices to differentiate between “healthy” and “cancerous” breath, and, furthermore, between the breath of patients with different cancer types, with >92% sensitivity. Conclusions: The electronic nose technology has a high potential for assessing various types of cancer via simple exhalation procedure. The results provide a launching pad towards obtaining an inexpensive, compact tool that is amenable to widespread screening and that has a potential for direct and real-time monitoring (2–3 minutes only). No significant financial relationships to disclose.

5

Sivertsen, S. M., A. Bjørneklett, H. P. Gullestad, and K. Nygaard. "Breath Methane and Colorectal Cancer." Scandinavian Journal of Gastroenterology 27, no. 1 (January 1992): 25–28. http://dx.doi.org/10.3109/00365529209011161.

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6

Dobie, Monika. "Breath test to detect cancer." Nursing Standard 21, no. 46 (July 25, 2007): 28. http://dx.doi.org/10.7748/ns.21.46.28.s34.

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7

Goodwin, Peter M. "Breath Test Detects Esophagogastric Cancer." Oncology Times 39, no. 5 (March 2017): 30. http://dx.doi.org/10.1097/01.cot.0000514193.74091.a7.

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8

Marshall, E. "A Breath Test for Cancer?" Science 259, no. 5100 (March 5, 1993): 1395. http://dx.doi.org/10.1126/science.259.5100.1395.

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9

Uppal, N., and P. Singh. "Oral cancer: Breath of death." British Dental Journal 221, no. 5 (September 2016): 212. http://dx.doi.org/10.1038/sj.bdj.2016.619.

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10

Clarke, Berwyn. "Breath test aids cancer chemotherapy." Lancet Oncology 1 (May 2000): 6. http://dx.doi.org/10.1016/s1470-2045(09)70272-4.

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11

Haddad, Ghazal, Stef Schouwenburg, Ashraf Altesha, Wei Xu, and Geoffrey Liu. "Using breath analysis as a screening tool to detect gastric cancer: A systematic review." Journal of Clinical Oncology 39, no. 3_suppl (January 20, 2021): 175. http://dx.doi.org/10.1200/jco.2021.39.3_suppl.175.

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175 Background: In its early stages, gastric cancer symptoms are frequently lacking, resulting in an often late and incurable diagnosis. A non-invasive, cheap, and reliable screening method for gastric cancer could improve outcomes and increase the number of surgically resectable gastric cancers. Breath analysis has emerged as an experimental method of non-invasive screening of gastric cancer and identification of individuals suitable for confirmatory, diagnostic upper gastrointestinal endoscopy. We aimed to evaluate the accuracy and applicability of breath analysis for gastric cancer detection in adults. Methods: This systematic review searched MEDLINE, EMBASE, BIOSIS, CENTRAL, and Compendex until 11 July 2019 for original studies analyzing exhaled breath to detect gastric cancer in patients. Two authors then independently screened the abstracts, titles, and full texts. Summary sensitivity and specificity analyses were obtained using a hierarchical bivariate method. Positive predictive value and number needed to screen (NNS) of breath analysis methods for gastric cancer detection were calculated for each country using gastric cancer prevalence by country obtained from the Global Cancer Observatory. Non-quantitative results were descriptively summarized. Risk of bias was assessed using the QUADAS-2 tool. This study protocol was pre-registered in PROSPERO (CRD42020139422). Results: Twenty studies were included. Together, the studies included 2,976 subjects. The pooled mean age of the subjects in the gastric cancer groups was 60.5 ± 11 years while the pooled mean age for control groups was 55.4 ± 12 years. Within these twenty studies, breath analysis technologies most commonly used were mass spectrometry (MS)-based methods; other methods included volatile organic compound sensors, thermal desorption tubes, and silicon nanowire field effect transistors. Across all included studies, we found and summarized the characteristics of 131 chemical compounds found in the exhaled breath of study subjects. Eleven studies (total n = 1905) involving all technologies reported quantitative results, with sensitivities ranging from 67-100% and specificities from 71-98%. The summary sensitivity across six studies utilizing MS-based breath analysis methods was 85.3% (95% CI: 82-96%); summary specificity was 81.7%. (95% CI: 78-85%). Based on the MS-based values, we estimated that screening with MS-based breath tests could lower the NNS by more than four-fold in the 15 countries with the highest prevalence of gastric cancer. Conclusions: Breath analysis is a promising method for gastric cancer detection with good diagnostic performance and potential to decrease the NNS for endoscopy-based gastric cancer detection. However, due to the heterogeneity of breath analysis technologies, rigorous studies with standardized, reproducible methods are needed to evaluate the clinical applicability of these technologies.

12

Wan, Qianqian, Yancheng Xu, and Xiaoxing Zhang. "Adsorption Properties of Typical Lung Cancer Breath Gases on Ni-SWCNTs through Density Functional Theory." Journal of Sensors 2017 (2017): 1–8. http://dx.doi.org/10.1155/2017/7974545.

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A lot of useful information is contained in the human breath gases, which makes it an effective way to diagnose diseases by detecting the typical breath gases. This work investigated the adsorption of typical lung cancer breath gases: benzene, styrene, isoprene, and 1-hexene onto the surface of intrinsic and Ni-doped single wall carbon nanotubes through density functional theory. Calculation results show that the typical lung cancer breath gases adsorb on intrinsic single wall carbon nanotubes surface by weak physisorption. Besides, the density of states changes little before and after typical lung cancer breath gases adsorption. Compared with single wall carbon nanotubes adsorption, single Ni atom doping significantly improves its adsorption properties to typical lung cancer breath gases by decreasing adsorption distance and increasing adsorption energy and charge transfer. The density of states presents different degrees of variation during the typical lung cancer breath gases adsorption, resulting in the specific change of conductivity of gas sensing material. Based on the different adsorption properties of Ni-SWCNTs to typical lung cancer breath gases, it provides an effective way to build a portable noninvasive portable device used to evaluate and diagnose lung cancer at early stage in time.

13

KIDA, Hiroshi. "Exhaled Breath Analysis for Lung Cancer." Journal of the Japan Society for Precision Engineering 82, no. 8 (2016): 718–21. http://dx.doi.org/10.2493/jjspe.82.718.

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14

Altomare, Donato F. "Breath analysis for colorectal cancer screening." Colorectal Disease 18, no. 12 (December 2016): 1127–28. http://dx.doi.org/10.1111/codi.13480.

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15

Kabir, K. M. Mohibul, and William A. Donald. "Cancer breath testing: a patent review." Expert Opinion on Therapeutic Patents 28, no. 3 (January 6, 2018): 227–39. http://dx.doi.org/10.1080/13543776.2018.1423680.

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16

Adiguzel, Yekbun, and Haluk Kulah. "Breath sensors for lung cancer diagnosis." Biosensors and Bioelectronics 65 (March 2015): 121–38. http://dx.doi.org/10.1016/j.bios.2014.10.023.

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17

Saalberg, Yannick, and Marcus Wolff. "VOC breath biomarkers in lung cancer." Clinica Chimica Acta 459 (August 2016): 5–9. http://dx.doi.org/10.1016/j.cca.2016.05.013.

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18

Amann, Anton, Massimo Corradi, Peter Mazzone, and Antonio Mutti. "Lung cancer biomarkers in exhaled breath." Expert Review of Molecular Diagnostics 11, no. 2 (March 2011): 207–17. http://dx.doi.org/10.1586/erm.10.112.

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19

Chen, Jinliang, Jianrong Chen, Xuedong Lv, Qichang Yang, and Sumei Yao. "Epidermal Growth Factor in Exhaled Breath Condensate as Diagnostic Method for Non-Small Cell Lung Cancer." Technology in Cancer Research & Treatment 18 (January 1, 2019): 153303381987227. http://dx.doi.org/10.1177/1533033819872271.

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Objective: Lung cancer is one of the most common malignant tumors in humans. Finding a highly sensitive and specific marker is very important. This study investigated the clinical significance of epidermal growth factor in exhaled breath condensate and serum of patients with non-small cell lung cancer. Methods: From October 17, 2013, to June 5, 2017, exhaled breath condensate and blood samples from 155 patients with non-small cell lung cancer, 63 patients with benign pulmonary nodules, and 115 healthy controls were collected using a breath condenser. Each sample was analyzed by enzyme-linked immunosorbent assay. Results: Epidermal growth factor level in the exhaled breath condensate from the non-small cell lung cancer group (197.86 ± 60.67 pg/mL) was higher than that in the healthy group (124.75 ± 36.09 pg/mL), P < .05. Epidermal growth factor level in the exhaled breath condensate of the smoking group (208.85 ± 40.94 pg/mL) was higher than that of the nonsmoking group (185.52 ± 36.88 pg/mL), P < .05. Epidermal growth factor level in the exhaled breath condensate in phases III and IV of non-small cell lung cancer group (212.17 ± 35.41 pg/mL) was higher than that in phases I and II (173.91 ± 38.08 pg/mL), P < .05. Epidermal growth factor level in the exhaled breath condensate of the death group (241.05 ± 27.19 pg/mL) was higher than that of the survival group (188.75 ± 37.07 pg/mL), P < .05. The epidermal growth factor exhaled breath condensate levels were positively correlated with the serum epidermal growth factor levels with a correlation coefficient of 0.495 ( P < .05). The sensitivity and specificity of epidermal growth factor exhaled breath condensate test were 80.0% and 89.6%, respectively. Conclusion: The detection of epidermal growth factor level in exhaled breath condensate exhibits is important in the diagnosis, disease monitoring, and prognosis of non-small cell lung cancer.

20

Patterson, Sharla Gayle, Charlene W. Bayer, Robert J. Hendry, Nancy Sellers, Kichun Sky Lee, Brani Vidakovic, Boris Mizaikoff, and Sheryl G. A. Gabram-Mendola. "Breath Analysis by Mass Spectrometry: A New Tool for Breast Cancer Detection?" American Surgeon 77, no. 6 (June 2011): 747–51. http://dx.doi.org/10.1177/000313481107700632.

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Breath analysis has received attention as a noninvasive diagnostic tool with increasing research into its potential usefulness. We are investigating the utility of the analysis of breath volatile organic compounds (VOCs) as an effective modality for breast cancer (BC) detection and monitoring by collecting breath samples with a simple portable device to determine whether BC patients have breath VOCs distinct from those in healthy volunteers. We prospectively enrolled 20 healthy volunteers and 20 newly diagnosed stage II-IV BC patients. The study subjects deeply exhaled into a commercially available Teflon/valved breath sampler equipped with a rapid passive diffusive sampler five times at 5-minute intervals trapping alveolar breath VOCs. The exhaled breath samples were analyzed by thermal desorption/gas chromatography/mass spectrometry monitoring 383 VOCs in the breath of both populations. Our results indicate that aggregate low-dimensional summaries and compound quantities result in specific patterns that can confirm BC. We found a definite clustering of the presence of BC from cancer-free points. Overall sensitivity was 72 per cent and specificity was 64 per cent resulting in a correct classification rate of approximately 77 per cent. Our data show promising evidence that BC patients can be differentiated from healthy volunteers through distinct breath VOCs.

21

McCarthy, Nicola. "Take a deep breath." Nature Reviews Cancer 9, no. 11 (October 15, 2009): 771. http://dx.doi.org/10.1038/nrc2753.

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22

Vallabhaneni, Geetha D., Sheryl G. A. Gabram, Kichun Sky Lee, Taofeek Kunle Owonikoko, Johann Christoph Brandes, Scott Arthur Kono, Nabil F. Saba, Fadlo Raja Khuri, Suresh S. Ramalingam, and Charlene W. Bayer. "Breath analysis for early detection of lung cancer." Journal of Clinical Oncology 30, no. 15_suppl (May 20, 2012): 7048. http://dx.doi.org/10.1200/jco.2012.30.15_suppl.7048.

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7048 Background: Lung cancer (LC) is the leading cause of cancer death worldwide. Early detection is critical to reduce LC related mortality. Breath analysis can be used as a non invasive diagnostic tool in conjunction with CT screening. We assessed the diagnostic value of breath volatile organic compounds (BVOCs) in the alveolar breath of female non-small cell lung cancer (NSCLC) patients. Methods: This is a prospective case-control study that enrolled newly diagnosed NSCLC and cancer-free female controls. The study aims: 1) To compare the BVOC signature in female NSCLC patients to a control group without LC 2) To compare the BVOC signature between NSCLC and breast cancer (BC) patients. The study was restricted to women because the pilot data was generated from female subjects with BC. Consenting eligible patients provided a total of five deep breath samples into a proprietary breath sampler developed at the Georgia Tech Research Institute (GTRI) for collecting alveolar breath. Breath samples were collected five minutes apart from each subject. The collected samples were analyzed for BVOCs using thermal desorption/gas chromatographic/mass spectrometric (TD/GC/MS) technique. Statistical differences in BVOCs in breath samples from cases and controls were assessed using this technique. Support vector machine classification method was employed to compare the BVOCs pattern between LC and BC patients. Results: We enrolled 25 NSCLC and 25 cancer-free subjects. TD/GC/MS analysis identified a total of 422 BVOCs among the controls and NSCLC subjects. 75 unique BVOCs that were significantly different between cases and controls were employed for statistical modeling. This 75 BVOCs signature has a sensitivity of 0.75, a specificity of 0.75 and a classification accuracy of 75% for NSCLC and controls. Statistical analysis on the full BVOCs data set from NSCLC and previously collected BVOCs data from BC patients achieved a classification accuracy of 88%. Conclusions: Unique BVOCs pattern can identify patients with established NSCLC. Future studies in at-risk patients will assess the utility of this approach as a less invasive and minimal risk screening tool for early detection of NSCLC. Supported by the Kennedy Seed Grant awarded by the Winship Cancer Institute of Emory University.

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Naz, Farah, Amy Grace Groom, MD Mohiuddin, Arpita Sengupta, Trisha Daigle-Maloney, Margot J. Burnell, James Charles Roger Michael, et al. "Using infrared spectroscopy to analyze breath of patients diagnosed with breast cancer." Journal of Clinical Oncology 40, no. 16_suppl (June 1, 2022): e13579-e13579. http://dx.doi.org/10.1200/jco.2022.40.16_suppl.e13579.

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e13579 Background: Population-level screening programs aimed at early detection and treatment of breast cancer saves lives. Analyzing breath using infrared spectroscopy offers a highly sensitive, non-invasive, and cost-effective mechanism for identifying exhaled volatile organic chemicals, and it is hypothesized that it may identify differences in the “breathprint” of women with breast cancer relative to those without a breast cancer diagnosis. Methods: Alveolar breath samples (10 L) were collected using a Breathe BioMedical alveolar breath sampler onto Tenax TA sorbent tubes. Corresponding room air samples (10 L) were collected in the same manner. Absorption spectra of the samples at a desorb temperature of 75 °C were measured by infrared cavity ring-down spectroscopy (IR-CRDS), a highly sensitive method of measuring absorption coefficients due to trace volatile organic compounds (VOCs) present in exhaled breath. After subtracting room air absorption and ordering each measured spectrum by increasing wavelength, missing values were imputed using spline interpolation. The absorption spectra were then normalized using one of four techniques: min-max, vector, peak or standard normal variate normalization. The first derivatives of the normalized absorption coefficients (187 values in total) were then used as features for discriminating samples from subjects with breast cancer and controls. The most useful features were selected based on minimum redundancy and maximum relevance (mRMR) and were used to train a linear support vector machine (SVM) classifier. Performance of classification models was estimated based on two data splitting configurations, non-nested leave-one-out cross-validation (LOOCV) and nested LOOCV. These approaches provide upper and lower bounds of expected model performance. Classification performance was used for tuning the number of features included in each model. Results: The analysis of this study is based on the spectra obtained from 70 participants (38 breast cancer and 32 controls), collected at the Saint John Regional Hospital in New Brunswick, Canada. Table below shows the non-nested and nested performance characteristics of classifiers with the best performing normalization technique. The number of features given for the nested model is not an integer as it indicates an average across the cross-validation folds. Conclusions: These results suggest that the classification of alveolar breath using IR-CRDS is a promising technique for the detection of breast cancer. Performance of classification models. AUC is the area under the receiver operator characteristics curve.[Table: see text]

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Naz, Farah, Amy Grace Groom, MD Mohiuddin, Arpita Sengupta, Trisha Daigle-Maloney, Margot J. Burnell, James Charles Roger Michael, et al. "Using infrared spectroscopy to analyze breath of patients diagnosed with breast cancer." Journal of Clinical Oncology 40, no. 16_suppl (June 1, 2022): e13579-e13579. http://dx.doi.org/10.1200/jco.2022.40.16_suppl.e13579.

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e13579 Background: Population-level screening programs aimed at early detection and treatment of breast cancer saves lives. Analyzing breath using infrared spectroscopy offers a highly sensitive, non-invasive, and cost-effective mechanism for identifying exhaled volatile organic chemicals, and it is hypothesized that it may identify differences in the “breathprint” of women with breast cancer relative to those without a breast cancer diagnosis. Methods: Alveolar breath samples (10 L) were collected using a Breathe BioMedical alveolar breath sampler onto Tenax TA sorbent tubes. Corresponding room air samples (10 L) were collected in the same manner. Absorption spectra of the samples at a desorb temperature of 75 °C were measured by infrared cavity ring-down spectroscopy (IR-CRDS), a highly sensitive method of measuring absorption coefficients due to trace volatile organic compounds (VOCs) present in exhaled breath. After subtracting room air absorption and ordering each measured spectrum by increasing wavelength, missing values were imputed using spline interpolation. The absorption spectra were then normalized using one of four techniques: min-max, vector, peak or standard normal variate normalization. The first derivatives of the normalized absorption coefficients (187 values in total) were then used as features for discriminating samples from subjects with breast cancer and controls. The most useful features were selected based on minimum redundancy and maximum relevance (mRMR) and were used to train a linear support vector machine (SVM) classifier. Performance of classification models was estimated based on two data splitting configurations, non-nested leave-one-out cross-validation (LOOCV) and nested LOOCV. These approaches provide upper and lower bounds of expected model performance. Classification performance was used for tuning the number of features included in each model. Results: The analysis of this study is based on the spectra obtained from 70 participants (38 breast cancer and 32 controls), collected at the Saint John Regional Hospital in New Brunswick, Canada. Table below shows the non-nested and nested performance characteristics of classifiers with the best performing normalization technique. The number of features given for the nested model is not an integer as it indicates an average across the cross-validation folds. Conclusions: These results suggest that the classification of alveolar breath using IR-CRDS is a promising technique for the detection of breast cancer. Performance of classification models. AUC is the area under the receiver operator characteristics curve.[Table: see text]

25

Hubers, A. Jasmijn, Paul Brinkman, Remco J. Boksem, Robert J. Rhodius, Birgit I. Witte, Aeilko H. Zwinderman, Daniëlle A. M. Heideman, et al. "Combined sputum hypermethylation and eNose analysis for lung cancer diagnosis." Journal of Clinical Pathology 67, no. 8 (June 10, 2014): 707–11. http://dx.doi.org/10.1136/jclinpath-2014-202414.

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AimsThe aim of this study is to explore DNA hypermethylation analysis in sputum and exhaled breath analysis for their complementary, non-invasive diagnostic capacity in lung cancer.MethodsSputum samples and exhaled breath were prospectively collected from 20 lung cancer patients and 31 COPD controls (Set 1). An additional 18 lung cancer patients and 8 controls only collected exhaled breath as validation set (Set 2). DNA hypermethylation of biomarkers RASSF1A, cytoglobin, APC, FAM19A4, PHACTR3, 3OST2 and PRDM14 was considered, and breathprints from exhaled breath samples were created using an electronic nose (eNose).ResultsBoth DNA hypermethylation markers in sputum and eNose were independently able to distinguish lung cancer patients from controls. The combination of RASSF1A and 3OST2 hypermethylation had a sensitivity of 85% with a specificity of 74%. eNose had a sensitivity of 80% with a specificity of 48%. Sensitivity for lung cancer diagnosis increased to 100%, when RASSF1A hypermethylation was combined with eNose, with specificity of 42%. Both methods showed to be complementary to each other (p≤0.011). eNose results were reproducible in Set 2.ConclusionsWhen used in concert, RASSF1A hypermethylation in sputum and exhaled breath analysis are complementary for lung cancer diagnosis, with 100% sensitivity in this series. This finding should be further validated.

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LaCorte, Sarah. "3 QUESTIONS ON... Breath Tests for Cancer." Oncology Times 43, no. 9 (May 5, 2021): 42. http://dx.doi.org/10.1097/01.cot.0000752040.98194.7f.

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27

Phillips, Michael, Renee N. Cataneo, Cassie Lebauer, Mayur Mundada, and Christobel Saunders. "Breath mass ion biomarkers of breast cancer." Journal of Breath Research 11, no. 1 (January 10, 2017): 016004. http://dx.doi.org/10.1088/1752-7163/aa549b.

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Campanella, Annalisa, Simona De Summa, and Stefania Tommasi. "Exhaled breath condensate biomarkers for lung cancer." Journal of Breath Research 13, no. 4 (August 20, 2019): 044002. http://dx.doi.org/10.1088/1752-7163/ab2f9f.

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&NA;. "Sensor breath test to detect early cancer." Oncology Times UK 7, no. 9 (September 2010): 4. http://dx.doi.org/10.1097/01.otu.0000394210.14640.ad.

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30

Szulejko, Jan E., Michael McCulloch, Jennifer Jackson, Dwight L. McKee, Jim C. Walker, and Touradj Solouki. "Evidence for Cancer Biomarkers in Exhaled Breath." IEEE Sensors Journal 10, no. 1 (January 2010): 185–210. http://dx.doi.org/10.1109/jsen.2009.2035669.

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31

Phillips, Michael, Renee N. Cataneo, Cassie Lebauer, Mayur Mundada, and Christobel Saunders. "Breath mass ion biomarkers of breast cancer." Journal of Clinical Oncology 34, no. 15_suppl (May 20, 2016): e23076-e23076. http://dx.doi.org/10.1200/jco.2016.34.15_suppl.e23076.

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32

Binson, V. A., and M. Subramoniam. "Exhaled Breath Volatile Organic Compound Analysis for the Detection of Lung Cancer- A Systematic Review." Journal of Biomimetics, Biomaterials and Biomedical Engineering 56 (May 20, 2022): 17–35. http://dx.doi.org/10.4028/p-dab04j.

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A rapid and effective diagnostic method is essential for lung cancer since it shows symptoms only at its advanced stage. Research is being carried out in the area of exhaled breath analysis for the diagnosis of various pulmonary diseases including lung cancer. In this method exhaled breath volatile organic compounds (VOC) are analyzed with various techniques such as gas chromatography-mass spectrometry, ion mobility spectrometry, and electronic noses. The VOC analysis is suitable for lung cancer detection since it is non-invasive, fast, and also a low-cost method. In addition, this technique can detect primary stage nodules. This paper presents a systematic review of the various method employed by researchers in the breath analysis field. The articles were selected through various search engines like EMBASE, Google Scholar, Pubmed, and Google. In the initial screening process, 214 research papers were selected using various inclusion and exclusion criteria and finally, 55 articles were selected for the review. The results of the reviewed studies show that detection of lung cancer can be effectively done using the VOC analysis of exhaled breath. The results also show that this method can be used for detecting the different stages and histology of lung cancer. The exhaled breath VOC analysis technique will be popular in the future, bypassing the existing imaging techniques. This systematic review conveys the recent research opportunities, obstacles, difficulties, motivations, and suggestions associated with the breath analysis method for lung cancer detection.

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Li, Wenwen, Wei Dai, Mingxin Liu, Yijing Long, Chunyan Wang, Shaohua Xie, Yuanling Liu, et al. "VOC biomarkers identification and predictive model construction for lung cancer based on exhaled breath analysis: research protocol for an exploratory study." BMJ Open 9, no. 8 (August 2019): e028448. http://dx.doi.org/10.1136/bmjopen-2018-028448.

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IntroductionLung cancer is the most common cancer and the leading cause of cancer death in China, as well as in the world. Late diagnosis is the main obstacle to improving survival. Currently, early detection methods for lung cancer have many limitations, for example, low specificity, risk of radiation exposure and overdiagnosis. Exhaled breath analysis is one of the most promising non-invasive techniques for early detection of lung cancer. The aim of this study is to identify volatile organic compound (VOC) biomarkers in lung cancer and to construct a predictive model for lung cancer based on exhaled breath analysis.Methods and analysisThe study will recruit 389 lung cancer patients in one cancer centre and 389 healthy subjects in two lung cancer screening centres. Bio-VOC breath sampler and Tedlar bag will be used to collect breath samples. Gas chromatography-mass spectrometry coupled with solid phase microextraction technique will be used to analyse VOCs in exhaled breath. VOC biomarkers with statistical significance and showing abilities to discriminate lung cancer patients from healthy subjects will be selected for the construction of predictive model for lung cancer.Ethics and disseminationThe study was approved by the Ethics Committee of Sichuan Cancer Hospital on 6 April 2017 (No. SCCHEC-02-2017-011). The results of this study will be disseminated in presentations at academic conferences, publications in peer-reviewed journals and the news media.Trial registration numberChiCTR-DOD-17011134; Pre-results.

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Markar, Sheraz, and George Hanna. "Non-invasive volatile organic compound analysis from exhaled breath for the diagnosis of gastroesophageal cancer." Journal of Clinical Oncology 33, no. 3_suppl (January 20, 2015): TPS225. http://dx.doi.org/10.1200/jco.2015.33.3_suppl.tps225.

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TPS225 Background: The work carried out in our laboratory using Selective Ion Flow-Tube Mass Spectrometry (SIFT-MS) analysis of volatile organic compounds (VOCs) in exhaled breath has identified compounds that can differentiate gastro-esophageal cancer from non-cancer patients. A model has been developed based on 220 patients with upper gastrointestinal pathology (81 cancer, 88 positive control and 51 patients with endoscopically normal gastrointestinal tract). Methods: Clinical trial registry number: 14/LO/1136. Study 1: Refinement of VOC exhaled breath model. Exhaled breath from 120 patients undergoing diagnostic lower endoscopy for the investigation of gastrointestinal symptoms will be used to refine the existing model by studying the influence of lower gastrointestinal diseases and in particular colorectal cancer, upon VOC analysis. To date 94 patients have been recruited. Study 2: Blinded validation multi-centre study for the use of exhaled Breath SIFT-MS analysis to predict gastro-esophageal cancer. This study will be conducted across four centers and will utilize SIFT-MS exhaled breath analysis, for comparison of predicted cancer risk based upon the VOC exhaled breath model compared to endoscopic findings and histology biopsies in order to determine the overall diagnostic accuracy for this non-invasive test. Sample Size – Based upon a prevalence of cancer of 50% in the study population and maintaining a sensitivity and specificity of 80% for the diagnostic model derived from our previous research, the sample size estimated is 325 patients. Inclusion criteria:Patients with upper gastrointestinal symptoms attending for endoscopy or surgery. Exclusion criteria: Patients with a documented active infection or liver disease. Statistical methods: Comparison of predicted cancer risk and actual OGD findings or histology from endoscopic biopsies will then be made, and the overall diagnostic accuracy (sensitivity, specificity, positive and negative predictive value, ROC curve analysis) for this non-invasive diagnostic investigation will be determined. Deliverables: The diagnostic accuracy of the exhaled breath test for the prediction of oesophago-gastric cancer. Clinical trial information: 14/LO/1136.

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Goymer, Patrick. "A breath of fresh air." Nature Reviews Cancer 6, no. 3 (March 2006): 172. http://dx.doi.org/10.1038/nrc1832.

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Keogh, Rachel J., and John C. Riches. "The Use of Breath Analysis in the Management of Lung Cancer: Is It Ready for Primetime?" Current Oncology 29, no. 10 (September 30, 2022): 7355–78. http://dx.doi.org/10.3390/curroncol29100578.

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Breath analysis is a promising non-invasive method for the detection and management of lung cancer. Exhaled breath contains a complex mixture of volatile and non-volatile organic compounds that are produced as end-products of metabolism. Several studies have explored the patterns of these compounds and have postulated that a unique breath signature is emitted in the setting of lung cancer. Most studies have evaluated the use of gas chromatography and mass spectrometry to identify these unique breath signatures. With recent advances in the field of analytical chemistry and machine learning gaseous chemical sensing and identification devices have also been created to detect patterns of odorant molecules such as volatile organic compounds. These devices offer hope for a point-of-care test in the future. Several prospective studies have also explored the presence of specific genomic aberrations in the exhaled breath of patients with lung cancer as an alternative method for molecular analysis. Despite its potential, the use of breath analysis has largely been limited to translational research due to methodological issues, the lack of standardization or validation and the paucity of large multi-center studies. It is clear however that it offers a potentially non-invasive alternative to investigations such as tumor biopsy and blood sampling.

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Arseniev, A., A. Nefedova, A. Ganeeva, A. Nefedov, S. Novikov, Anton Barchuk, S. Kanaev, et al. "COMBINED DIAGNOSTICS OF LUNG CANCER USING EXHALED BREATH ANALSYSIS AND SPUTUM CYTOLOGY." Problems in oncology 66, no. 4 (April 1, 2020): 381–84. http://dx.doi.org/10.37469/0507-3758-2020-66-4-381-384.

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In this article we summarize our own experience of lung cancer diagnostics using exhaled breath analysis with a non-selective method using metal oxide chemoresistor gas sensors with cross-sensitivity combined with the sputum cytology. Volatile organic compounds of exhaled breath change the conductivity of the sensor, the resulting pulse is displayed as a peak on the graph, the area of which is used as test results. The combination of two diagnostic techniques in 204 participants demonstrated the possibility of non-invasively detecting the disease at an early stage. The sensitivity, specificity and accuracy of the breath analysis was 91.2%, 100% and 93.4%, respectively. The combination of the breath test and the sputum cytology compared to the breath test alone showed statistically significant (p = 0.03) increase in sensitivity to 96.8% (95% CI: 80.9% -99%) with acceptable decrease in specificity to 93.4% (95% CI: 88% -96%). The convenience of analysis and realtime measurements show some promise for the early detection.

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Labuschagne, Christiaan Frederick, Rob Smith, Neelam Kumar, Max Allsworth, Billy Boyle, Sam Janes, Phil Crosbie та Robert Rintoul. "Breath biopsy early detection of lung cancer using an EVOC probe targeting tumor-specific extracellular β-glucuronidase." Journal of Clinical Oncology 40, № 16_suppl (1 червня 2022): 2569. http://dx.doi.org/10.1200/jco.2022.40.16_suppl.2569.

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2569 Background: Lung cancer is a leading cause of mortality with 5-year survival less than 20%, largely a result of many cases being diagnosed late. Early detection can increase cancer survival up to 13-fold underscoring the need for effective screening. Targeted Low dose computed tomography (LDCT) has been shown to be effective but its impact to date has been limited due to slow adoption and variable uptake in high-risk populations. Breath analysis represents a non-invasive screening approach either alone or alongside LDCT. Numerous studies have investigated potential endogenous breath biomarkers of lung cancer. Many have produced promising results but to date, no validated biomarkers with clear connections to cancer metabolism have been revealed. We have explored an alternative, probe-based approach based around Exogenous Volatile Organic Compound Probes (EVOC Probes). The probes target tumour associated extracellular b-glucuronidase, a glycosidase enzyme that normally resides within lysosomes. Methods: We use a hydrophilic non cell permeable substrate probe D5-ethyl-βD-glucuronide (D5-EtGlu) that upon hydrolysis by the target enzyme releases D5-ethanol, a unique volatile reporter molecule detectable on breath. This provides a readout of tumour associated enzyme activity using breath analysis. Results: Administering D5-EtGlu to mice resulted in tumour specific release of D5-ethanol, enabling discrimination between healthy and tumour bearing animals. Increased expression of b-glucuronidase in lung cancer tissue and the tumour microenvironment was confirmed with immunohistochemistry (IHC) in clinical samples. A phase 1a clinical trial administered D5-EtGlu to healthy individuals in a single ascending dose study to establish safety and background D5-ethanol levels in healthy individuals. This resulted in no adverse events and low/no D5-ethanol signal verifying the inaccessibility of D5-EtGlu to intracellular b-glucuronidase. The next stage, currently ongoing, is a proof of mechanism in humans. D5-EtGlu is administered intravenously to confirmed lung cancer patients followed by breath analysis. D5-ethanol breath levels will be compared to cancer free individuals receiving the same dose of D5-EtGlu. Conclusions: Non-invasive breath testing has great potential to contribute to diagnosis for lung cancer including a potential role in screening. Our current work is evaluating the use of an administered probe to stimulate tumour-specific enzyme activity and produce a marker detectable on breath. Continued success could result in a sensitive and highly specific method for lung cancer early detection.

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Labuschagne, Christiaan Frederick, Rob Smith, Neelam Kumar, Max Allsworth, Billy Boyle, Sam Janes, Phil Crosbie та Robert Rintoul. "Breath biopsy early detection of lung cancer using an EVOC probe targeting tumor-specific extracellular β-glucuronidase." Journal of Clinical Oncology 40, № 16_suppl (1 червня 2022): 2569. http://dx.doi.org/10.1200/jco.2022.40.16_suppl.2569.

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2569 Background: Lung cancer is a leading cause of mortality with 5-year survival less than 20%, largely a result of many cases being diagnosed late. Early detection can increase cancer survival up to 13-fold underscoring the need for effective screening. Targeted Low dose computed tomography (LDCT) has been shown to be effective but its impact to date has been limited due to slow adoption and variable uptake in high-risk populations. Breath analysis represents a non-invasive screening approach either alone or alongside LDCT. Numerous studies have investigated potential endogenous breath biomarkers of lung cancer. Many have produced promising results but to date, no validated biomarkers with clear connections to cancer metabolism have been revealed. We have explored an alternative, probe-based approach based around Exogenous Volatile Organic Compound Probes (EVOC Probes). The probes target tumour associated extracellular b-glucuronidase, a glycosidase enzyme that normally resides within lysosomes. Methods: We use a hydrophilic non cell permeable substrate probe D5-ethyl-βD-glucuronide (D5-EtGlu) that upon hydrolysis by the target enzyme releases D5-ethanol, a unique volatile reporter molecule detectable on breath. This provides a readout of tumour associated enzyme activity using breath analysis. Results: Administering D5-EtGlu to mice resulted in tumour specific release of D5-ethanol, enabling discrimination between healthy and tumour bearing animals. Increased expression of b-glucuronidase in lung cancer tissue and the tumour microenvironment was confirmed with immunohistochemistry (IHC) in clinical samples. A phase 1a clinical trial administered D5-EtGlu to healthy individuals in a single ascending dose study to establish safety and background D5-ethanol levels in healthy individuals. This resulted in no adverse events and low/no D5-ethanol signal verifying the inaccessibility of D5-EtGlu to intracellular b-glucuronidase. The next stage, currently ongoing, is a proof of mechanism in humans. D5-EtGlu is administered intravenously to confirmed lung cancer patients followed by breath analysis. D5-ethanol breath levels will be compared to cancer free individuals receiving the same dose of D5-EtGlu. Conclusions: Non-invasive breath testing has great potential to contribute to diagnosis for lung cancer including a potential role in screening. Our current work is evaluating the use of an administered probe to stimulate tumour-specific enzyme activity and produce a marker detectable on breath. Continued success could result in a sensitive and highly specific method for lung cancer early detection.

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Jacobson, Geraldine M., Christopher Nicholas Watson, Jianjun Zhang, Sijin Wen, and Nicole Helen Bunda-Randall. "Mean radiation dose to the heart in patients with left breast cancer with and without breath-hold technique." Journal of Clinical Oncology 32, no. 26_suppl (September 10, 2014): 85. http://dx.doi.org/10.1200/jco.2014.32.26_suppl.85.

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85 Background: Mean heart dose (MHD) from breast irradiation has been correlated with late risk of ischemic heart disease. We previously reported using 3-D conformal radiation with field-in-field forward planning and heart blocking; MHD is substantially lower than described for patients treated before 2001. To further reduce MHD, we treated eligible patients with left breast cancer with breath hold technique. We compared the MHD with and without breath hold technique. Methods: We reviewed 45 radiation treatment plans of patients treated to the left breast from 5/2013-5/2014. All patients were evaluated for breath hold technique. Criteria were ability to hold the breath for 20 seconds and a stable chest position. 18 patients were treated with breath hold (BH), 27 patients with non-breath hold (NBH). All treatment plans were CT-based, 3-D conformal with field-in- field forward planning and heart blocking. Two treatment regimens were used: hypofractionation (HF) (16 x 2.66 Gy, no boost) or standard fractionation (SF) (46.8-50.4 Gy, +/- 10 Gy boost). Fisher's exact test and t-test were used to assess the data between MHD with breath hold (BH) and without (NBH). Results: Average MHD was 1.03 Gy (0.59-1.7) in BH patients, in comparison to 1.57 Gy (0.89-2.50) in NBH patients p<0.0001). MHD was associated with total breast dose (p=0.01) and BH patients were younger, average age 55.78 years (21.41-48.37) vs NBH, average 62.78 years (38-82). There was no association between breath hold and BMI. BH BMI average 34.12 (21.41-48.37), NBH average BMI 32.6 (20.58-44.71) p=0.46. Conclusions: Patients treated with radiation to the left breast with breath hold technique had significantly lower MHD than those treated with non-breath hold. (p=0.0001) Breath hold eligible patients tended to be younger; there was no relation between breath hold eligibility and BMI.

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Sutaria, Saurin R., Sadakatali S. Gori, James D. Morris, Zhenzhen Xie, Xiao-An Fu, and Michael H. Nantz. "Lipid Peroxidation Produces a Diverse Mixture of Saturated and Unsaturated Aldehydes in Exhaled Breath That Can Serve as Biomarkers of Lung Cancer—A Review." Metabolites 12, no. 6 (June 18, 2022): 561. http://dx.doi.org/10.3390/metabo12060561.

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The peroxidation of unsaturated fatty acids is a widely recognized metabolic process that creates a complex mixture of volatile organic compounds including aldehydes. Elevated levels of reactive oxygen species in cancer cells promote random lipid peroxidation, which leads to a variety of aldehydes. In the case of lung cancer, many of these volatile aldehydes are exhaled and are of interest as potential markers of the disease. Relevant studies reporting aldehydes in the exhaled breath of lung cancer patients were collected for this review by searching the PubMed and SciFindern databases until 25 May 2022. Information on breath test results, including the biomarker collection, preconcentration, and quantification methods, was extracted and tabulated. Overall, 44 studies were included spanning a period of 34 years. The data show that, as a class, aldehydes are significantly elevated in the breath of lung cancer patients at all stages of the disease relative to healthy control subjects. The type of aldehyde detected and/or deemed to be a biomarker is highly dependent on the method of exhaled breath sampling and analysis. Unsaturated aldehydes, detected primarily when derivatized during preconcentration, are underrepresented as biomarkers given that they are also likely products of lipid peroxidation. Pentanal, hexanal, and heptanal were the most reported aldehydes in studies of exhaled breath from lung cancer patients.

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Walston, Steve, Allison M. Quick, Karla Kuhn, and Yi Rong. "Dosimetric Considerations in Respiratory-Gated Deep Inspiration Breath-Hold for Left Breast Irradiation." Technology in Cancer Research & Treatment 16, no. 1 (July 8, 2016): 22–32. http://dx.doi.org/10.1177/1533034615624311.

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Purpose: To present our clinical workflow of incorporating AlignRT for left breast deep inspiration breath-hold treatments and the dosimetric considerations with the deep inspiration breath-hold protocol. Material and Methods: Patients with stage I to III left-sided breast cancer who underwent lumpectomy or mastectomy were considered candidates for deep inspiration breath-hold technique for their external beam radiation therapy. Treatment plans were created on both free-breathing and deep inspiration breath-hold computed tomography for each patient to determine whether deep inspiration breath-hold was beneficial based on dosimetric comparison. The AlignRT system was used for patient setup and monitoring. Dosimetric measurements and their correlation with chest wall excursion and increase in left lung volume were studied for free-breathing and deep inspiration breath-hold plans. Results: Deep inspiration breath-hold plans had significantly increased chest wall excursion when compared with free breathing. This change in geometry resulted in reduced mean and maximum heart dose but did not impact lung V20 or mean dose. The correlation between chest wall excursion and absolute reduction in heart or lung dose was found to be nonsignificant, but correlation between left lung volume and heart dose showed a linear association. It was also identified that higher levels of chest wall excursion may paradoxically increase heart or lung dose. Conclusion: Reduction in heart dose can be achieved for many left-sided breast and chest wall patients using deep inspiration breath-hold. Chest wall excursion as well as left lung volume did not correlate with reduction in heart dose, and it remains to be determined what metric will provide the most optimal and reliable dosimetric advantage.

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Marzorati, Davide, Luca Mainardi, Giulia Sedda, Roberto Gasparri, Lorenzo Spaggiari, and Pietro Cerveri. "MOS Sensors Array for the Discrimination of Lung Cancer and At-Risk Subjects with Exhaled Breath Analysis." Chemosensors 9, no. 8 (August 5, 2021): 209. http://dx.doi.org/10.3390/chemosensors9080209.

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Lung cancer is characterized by a tremendously high mortality rate and a low 5-year survival rate when diagnosed at a late stage. Early diagnosis of lung cancer drastically reduces its mortality rate and improves survival. Exhaled breath analysis could offer a tool to clinicians to improve the ability to detect lung cancer at an early stage, thus leading to a reduction in the associated survival rate. In this paper, we present an electronic nose for the automatic analysis of exhaled breath. A total of five a-specific gas sensors were embedded in the electronic nose, making it sensitive to different volatile organic compounds (VOCs) contained in exhaled breath. Nine features were extracted from each gas sensor response to exhaled breath, identifying the subject breathprint. We tested the electronic nose on a cohort of 80 subjects, equally split between lung cancer and at-risk control subjects. Including gas sensor features and clinical features in a classification model, recall, precision, and accuracy of 78%, 80%, and 77% were reached using a fourfold cross-validation approach. The addition of other a-specific gas sensors, or of sensors specific to certain compounds, could improve the classification accuracy, therefore allowing for the development of a clinical tool to be integrated in the clinical pipeline for exhaled breath analysis and lung cancer early diagnosis.

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Amran, Wirya Sastra, Putri Suci, Nina Aspiah, Menaldi Rasmin, Prasenohadi Prasenohadi, and Agus Dwi Susanto. "Breath Failure in Obesity." Jurnal Respirologi Indonesia 38, no. 2 (April 30, 2018): 123–33. http://dx.doi.org/10.36497/jri.v38i2.167.

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Based on calculations of over one million people in the world weighing excessively or known as obesity with body mass index (IMT) 25 kg / m2 or more. Obesity is the cause of morbidity, as is the case in the population of the United States an estimated 400,000 deaths caused due to obesity. Obesity especially abdominal obesity is a significant risk factor for cardiovascular diseases, type 2 diabetes, rheumatoid arthritis and cancer. The relationship between obesity and chronic respiratory illness began to increase and began to be recognized. The World Health Organization (WHO) predicts about 10% of the global population will be obese by 2015. (J Respir Indo 2018; 38(2): 123-33)

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Gashimova, Elina, Anna Osipova, Azamat Temerdashev, Vladimir Porkhanov, Igor Polyakov, Dmitry Perunov, and Ekaterina Dmitrieva. "Study of confounding factors influence on lung cancer diagnostics effectiveness using gas chromatography–mass spectrometry analysis of exhaled breath." Biomarkers in Medicine 15, no. 11 (August 2021): 821–29. http://dx.doi.org/10.2217/bmm-2020-0828.

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Aim: The purpose of this study was to estimate volatile organic compounds (VOCs) ability to distinguish exhaled breath samples of lung cancer patients and healthy volunteers and to assess the effect of smoking status and gender on parameters. Patients & methods: Exhaled breath samples of 40 lung cancer patients and 40 healthy individuals were analyzed using gas chromatography–mass spectrometry. Influence of other factors on the exhaled breath VOCs profile was investigated. Results: Some parameters correlating with the disease status were affected by other factors. Excluding these parameters allows creating a logistic regression diagnostic model with 83% sensitivity and 81% specificity. Conclusion: Influence of other factors on the exhaled breath VOCs profile has to be taken into account to avoid misleading results.

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Miolo, Gianmaria, Debora Basile, Andrea Carretta, Davide Adriano Santeufemia, Agostino Steffan, and Giuseppe Corona. "The metabolomic scent of cancer disease progression in soft tissue sarcoma: A case report." International Journal of Biological Markers 34, no. 2 (March 11, 2019): 205–9. http://dx.doi.org/10.1177/1724600818817316.

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Background: The purpose of this case report is to describe the potential that metabolomics breath analysis may have in cancer disease monitoring. The advances in mass spectrometry instrumentation allow the accurate real-time analysis of volatile metabolites exhaled in the breath. The application of such non-invasive devices may provide innovative and complementary monitoring of the physio-pathological conditions of cancer patients. Case presentation: A 59-year-old Caucasian woman with spindle cell malignant mesenchymal sarcoma of the presacral region started a first-line therapy with non-pegylated liposomal doxorubicin and ifosfamide associated with pelvic radiant treatment. After two cycles of chemotherapy plus radiotherapy, a significant pulmonary disease progression was reported. Thus, a second-line therapy with trabectedin was administered. However, after only two cycles of treatment a re-staging computed tomography scan reported further cancer disease progression of the target pulmonary lesions as well as occurrence of new satellite bilateral nodules. Real-time analysis of breath exhaled volatile organic compounds, performed by select ion flow tube mass spectrometry (SIFT-MS) during the follow-up of the patient, showed a specific metabolic pattern not observed in the breath of other soft tissue sarcoma patients who achieved clinical benefit from the treatments. Conclusions: This case report revealed the importance of the non-invasive real-time volatile organic compounds breath analysis to distinguish individual specific chemo-resistance phenotypes among soft tissue sarcoma patients. Such observation seems to suggest that breath metabolomics may be particularly useful for monitoring cancer disease progression in soft tissue sarcoma patients where only cost-effective diagnostic tools, such as positron emission tomography and computed tomography, are available.

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Parkes, MJ, Wilfried De Neve, Vincent Vakaet, Geoffrey Heyes, Timothy Jackson, Richard Delaney, Gavin Kirby, et al. "Safely achieving single prolonged breath-holds of > 5 minutes for radiotherapy in the prone, front crawl position." British Journal of Radiology 94, no. 1122 (June 1, 2021): 20210079. http://dx.doi.org/10.1259/bjr.20210079.

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Objective: Breast cancer radiotherapy is increasingly delivered supine with multiple, short breath-holds. There may be heart and lung sparing advantages for locoregional breast cancer of both prone treatment and in a single breath-hold. We test here whether single prolonged breath-holds are possible in the prone, front crawl position. Methods: 19 healthy volunteers were trained to deliver supine, single prolonged breath-holds with pre-oxygenation and hypocapnia. We tested whether all could achieve the same durations in the prone, front crawl position. Results: 19 healthy volunteers achieved supine, single prolonged breath-holds for mean of 6.2 ± 0.3 min. All were able to hold safely for the same duration while prone (6.1 ± 0.2 min ns. by paired ANOVA). With prone, the increased weight on the chest did not impede chest inflation, nor the ability to hold air in the chest. Thus, the rate of chest deflation (mean anteroposterior deflation movement of three craniocaudally arranged surface markers on the spinal cord) was the same (1.2 ± 0.2, 2.0 ± 0.4 and 1.2 ± 0.4 mm/min) as found previously during supine prolonged breath-holds. No leakage of carbon dioxide or air was detectable into the facemask. Conclusion: Single prolonged (>5 min) breath-holds are equally possible in the prone, front crawl position. Advances in knowledge: Prolonged breath-holds in the front crawl position are possible and have the same durations as in the supine position. Such training would therefore be feasible for some patients with breast cancer requiring loco-regional irradiation. It would have obvious advantages for hypofractionation.

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Di Gilio, Alessia, Jolanda Palmisani, Gianrocco Ventrella, Laura Facchini, Annamaria Catino, Niccolò Varesano, Pamela Pizzutilo, et al. "Breath Analysis: Comparison among Methodological Approaches for Breath Sampling." Molecules 25, no. 24 (December 10, 2020): 5823. http://dx.doi.org/10.3390/molecules25245823.

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Despite promising results obtained in the early diagnosis of several pathologies, breath analysis still remains an unused technique in clinical practice due to the lack of breath sampling standardized procedures able to guarantee a good repeatability and comparability of results. The most diffuse on an international scale breath sampling method uses polymeric bags, but, recently, devices named Mistral and ReCIVA, able to directly concentrate volatile organic compounds (VOCs) onto sorbent tubes, have been developed and launched on the market. In order to explore performances of these new automatic devices with respect to sampling in the polymeric bag and to study the differences in VOCs profile when whole or alveolar breath is collected and when pulmonary wash out with clean air is done, a tailored experimental design was developed. Three different breath sampling approaches were compared: (a) whole breath sampling by means of Tedlar bags, (b) the end-tidal breath collection using the Mistral sampler, and (c) the simultaneous collection of the whole and alveolar breath by using the ReCIVA. The obtained results showed that alveolar fraction of breath was relatively less affected by ambient air (AA) contaminants (p-values equal to 0.04 for Mistral and 0.002 for ReCIVA Low) with respect to whole breath (p-values equal to 0.97 for ReCIVA Whole). Compared to Tedlar bags, coherent results were obtained by using Mistral while lower VOCs levels were detected for samples (both breath and AA) collected by ReCIVA, likely due to uncorrected and fluctuating flow rates applied by this device. Finally, the analysis of all data also including data obtained by explorative analysis of the unique lung cancer (LC) breath sample showed that a clean air supply might determine a further confounding factor in breath analysis considering that lung wash-out is species-dependent.

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Kort, Sharina, Marjolein Brusse-Keizer, Jan Willem Gerritsen, Hugo Schouwink, Emanuel Citgez, Frans de Jongh, Jan van der Maten, Suzy Samii, Marco van den Bogart, and Job van der Palen. "Improving lung cancer diagnosis by combining exhaled-breath data and clinical parameters." ERJ Open Research 6, no. 1 (January 2020): 00221–2019. http://dx.doi.org/10.1183/23120541.00221-2019.

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IntroductionExhaled-breath analysis of volatile organic compounds could detect lung cancer earlier, possibly leading to improved outcomes. Combining exhaled-breath data with clinical parameters may improve lung cancer diagnosis.MethodsBased on data from a previous multi-centre study, this article reports additional analyses. 138 subjects with non-small cell lung cancer (NSCLC) and 143 controls without NSCLC breathed into the Aeonose. The diagnostic accuracy, presented as area under the receiver operating characteristic curve (AUC-ROC), of the Aeonose itself was compared with 1) performing a multivariate logistic regression analysis of the distinct clinical parameters obtained, and 2) using this clinical information beforehand in the training process of the artificial neural network (ANN) for the breath analysis.ResultsNSCLC patients (mean±sd age 67.1±9.1 years, 58% male) were compared with controls (62.1±7.0 years, 40.6% male). The AUC-ROC of the classification value of the Aeonose itself was 0.75 (95% CI 0.69–0.81). Adding age, number of pack-years and presence of COPD to this value in a multivariate regression analysis resulted in an improved performance with an AUC-ROC of 0.86 (95% CI 0.81–0.90). Adding these clinical variables beforehand to the ANN for classifying the breath print also led to an improved performance with an AUC-ROC of 0.84 (95% CI 0.79–0.89).ConclusionsAdding readily available clinical information to the classification value of exhaled-breath analysis with the Aeonose, either post hoc in a multivariate regression analysis or a priori to the ANN, significantly improves the diagnostic accuracy to detect the presence or absence of lung cancer.

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Abderrahman, Balkees. "Exhaled breath biopsy: a new cancer detection paradigm." Future Oncology 15, no. 15 (May 2019): 1679–82. http://dx.doi.org/10.2217/fon-2019-0091.

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Статті в журналах з теми "Breath cancer"

Оформте джерело за APA, MLA, Chicago, Harvard та іншими стилями