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Journal articles on the topic 'Multi Imaging Modality'

Author: Grafiati

Published: 4 June 2025

Last updated: 14 July 2025

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1

Shaikh, Sikandar, and Minhajzafar Nasirabadi. "Multi Modality Dementia Imaging." Telangana Journal of IMA 02, no. 01 (2022): 32–39. http://dx.doi.org/10.52314/tjima.2022.v2i1.58.

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Imaging of the Dementia has undergone lot of advancements due to the availability of the newer techniques, newer modalities and the newer applications of the already existing contrasts, biomarkers, and newer software. The use of the various focussed agents for the diagnosis has led to the earlier and more precise diagnosis of the subclinical diseases which can prevent lot of the morbidi-ties leading to the concept of the precision medicine. To add this the concept of the hybrid functional imaging has revolutionized leading to the basis of the molecular imaging. This article will show the use of newer multiple modalities for the early and better diagnosis.

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Shankar, Prasad, and Matthew T. Heller. "Multi-modality imaging of pheochromocytoma." Radiology Case Reports 7, no. 4 (2012): 770. http://dx.doi.org/10.2484/rcr.v7i4.770.

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Allam, Mohamed N., Nima Baba Ali, Ahmed K. Mahmoud, et al. "Multi-Modality Imaging in Vasculitis." Diagnostics 14, no. 8 (2024): 838. http://dx.doi.org/10.3390/diagnostics14080838.

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Systemic vasculitides are a rare and complex group of diseases that can affect multiple organ systems. Clinically, presentation may be vague and non-specific and as such, diagnosis and subsequent management are challenging. These entities are typically classified by the size of vessel involved, including large-vessel vasculitis (giant cell arteritis, Takayasu’s arteritis, and clinically isolated aortitis), medium-vessel vasculitis (including polyarteritis nodosa and Kawasaki disease), and small-vessel vasculitis (granulomatosis with polyangiitis and eosinophilic granulomatosis with polyangiitis). There are also other systemic vasculitides that do not fit in to these categories, such as Behcet’s disease, Cogan syndrome, and IgG4-related disease. Advances in medical imaging modalities have revolutionized the approach to diagnosis of these diseases. Specifically, color Doppler ultrasound, computed tomography and angiography, magnetic resonance imaging, positron emission tomography, or invasive catheterization as indicated have become fundamental in the work up of any patient with suspected systemic or localized vasculitis. This review presents the key diagnostic imaging modalities and their clinical utility in the evaluation of systemic vasculitis.

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Beekman, Freek, and Brian F. Hutton. "Multi-modality imaging on track." European Journal of Nuclear Medicine and Molecular Imaging 34, no. 9 (2007): 1410–14. http://dx.doi.org/10.1007/s00259-007-0434-1.

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Thobani, Aneesha, Rajesh Sachdeva, and Gautam Kumar. "MULTI-MODALITY IMAGING IN CARDIAC AMYLOIDOSIS." Journal of the American College of Cardiology 77, no. 18 (2021): 2259. http://dx.doi.org/10.1016/s0735-1097(21)03614-7.

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Brasse, D., and F. Boisson. "Instrumentation challenges in multi-modality imaging." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 809 (February 2016): 67–75. http://dx.doi.org/10.1016/j.nima.2015.10.077.

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Salerno, Michael. "Multi-modality imaging of diastolic function." Journal of Nuclear Cardiology 17, no. 2 (2010): 316–27. http://dx.doi.org/10.1007/s12350-010-9196-4.

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Bai, Jing, Fei Liu, and Xin Liu. "Progress on Multi-Modality Molecular Imaging." Current Medical Imaging Reviews 8, no. 4 (2012): 295–301. http://dx.doi.org/10.2174/157340512803759857.

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Serganova, Inna, and Ronald G. Blasberg. "Multi-Modality Molecular Imaging of Tumors." Hematology/Oncology Clinics of North America 20, no. 6 (2006): 1215–48. http://dx.doi.org/10.1016/j.hoc.2006.09.006.

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Sahiner, Berkman, Heang-Ping Chan, Lubomir M. Hadjiiski, et al. "Multi-modality CADx." Academic Radiology 16, no. 7 (2009): 810–18. http://dx.doi.org/10.1016/j.acra.2009.01.011.

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Benedek, Theodora. "Multi-Modality Cardiac Imaging in Interventional Cardiology." Current Medical Imaging Formerly Current Medical Imaging Reviews 16, no. 2 (2020): 95–97. http://dx.doi.org/10.2174/157340561602200124090520.

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Traynor, Bryan Paul, Aamir Shamsi, and Victor Voon. "Multi-modality imaging in transthyretin amyloid cardiomyopathy." World Journal of Cardiology 11, no. 11 (2019): 266–76. http://dx.doi.org/10.4330/wjc.v11.i11.266.

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Longmoor, Charles E. "Musculoskeletal Imaging: A Concise Multi-Modality Approach,." Journal of Trauma and Acute Care Surgery 51, no. 6 (2001): 1216. http://dx.doi.org/10.1097/00005373-200112000-00035.

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Puranik, Rajesh, Vivek Muthurangu, David S. Celermajer, and Andrew M. Taylor. "Congenital Heart Disease and Multi-modality Imaging." Heart, Lung and Circulation 19, no. 3 (2010): 133–44. http://dx.doi.org/10.1016/j.hlc.2010.01.001.

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Malm, Brian J., and Mehran M. Sadeghi. "Multi-modality molecular imaging of aortic aneurysms." Journal of Nuclear Cardiology 24, no. 4 (2017): 1239–45. http://dx.doi.org/10.1007/s12350-017-0883-2.

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Ann, Soe Hee, Kyung Hun Lim, Cai De Jin, and Eun-Seok Shin. "Multi-modality imaging for stent edge assessment." Heart and Vessels 30, no. 2 (2014): 162–68. http://dx.doi.org/10.1007/s00380-014-0467-x.

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Bhattacharyya, S., J. Tarkin, S. Prasad, A. De Souza, and S. Kaddoura. "Multi-modality imaging of apical aortic conduit." European Journal of Echocardiography 12, no. 12 (2011): 975. http://dx.doi.org/10.1093/ejechocard/jer234.

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McAllister, Brylie J. "Multi Modality Imaging Features of Cardiac Myxoma." Journal of Cardiovascular Imaging 28, no. 4 (2020): 235. http://dx.doi.org/10.4250/jcvi.2020.0027.

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Ann, Soe Hee, Jun Ho Lee, Jong Min Kim, Shin-Jae Kim, and Eun-Seok Shin. "Multi-modality Imaging for Stent Edge Assessment." American Journal of Cardiology 111, no. 7 (2013): 83B—84B. http://dx.doi.org/10.1016/j.amjcard.2013.01.209.

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Gulati, Shrea, Sunil Chumber, Gopal Puri, Stanzin Spalkit, N. A. Damle, and CJ Das. "Multi-modality parathyroid imaging: A shifting paradigm." World Journal of Radiology 15, no. 3 (2023): 69–82. http://dx.doi.org/10.4329/wjr.v15.i3.69.

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Jovanić, Jelena, Dijana Trninić, Miron Marjanović, et al. "Preoperative multi-modality imaging of tricuspid regurgitation." Cardiologia Croatica 18, no. 5-6 (2023): 172. http://dx.doi.org/10.15836/ccar2023.172.

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Zhou, Jinyan, Shuwen Wang, Hao Wang, Yaxue Li, and Xiang Li. "Multi-Modality Fusion and Tumor Sub-Component Relationship Ensemble Network for Brain Tumor Segmentation." Bioengineering 12, no. 2 (2025): 159. https://doi.org/10.3390/bioengineering12020159.

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Deep learning technology has been widely used in brain tumor segmentation with multi-modality magnetic resonance imaging, helping doctors achieve faster and more accurate diagnoses. Previous studies have demonstrated that the weighted fusion segmentation method effectively extracts modality importance, laying a solid foundation for multi-modality magnetic resonance imaging segmentation. However, the challenge of fusing multi-modality features with single-modality features remains unresolved, which motivated us to explore an effective fusion solution. We propose a multi-modality and single-modality feature recalibration network for magnetic resonance imaging brain tumor segmentation. Specifically, we designed a dual recalibration module that achieves accurate feature calibration by integrating the complementary features of multi-modality with the specific features of a single modality. Experimental results on the BraTS 2018 dataset showed that the proposed method outperformed existing multi-modal network methods across multiple evaluation metrics, with spatial recalibration significantly improving the results, including Dice score increases of 1.7%, 0.5%, and 1.6% for the enhanced tumor core, whole tumor, and tumor core regions, respectively.

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Bailey, D. L., B. J. Pichler, B. Gückel, et al. "Combined PET/MRI: Multi-modality Multi-parametric Imaging Is Here." Molecular Imaging and Biology 17, no. 5 (2015): 595–608. http://dx.doi.org/10.1007/s11307-015-0886-9.

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Osborne, Dustin R., and Derek W. Austin. "Feasibility and Initial Performance of Simultaneous SPECT-CT Imaging Using a Commercial Multi-Modality Preclinical Imaging System." International Journal of Molecular Imaging 2015 (June 3, 2015): 1–11. http://dx.doi.org/10.1155/2015/134768.

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Multi-modality imaging provides coregistered PET-CT and SPECT-CT images; however such multi-modality workflows usually consist of sequential scans from the individual imaging components for each modality. This typical workflow may result in long scan times limiting throughput of the imaging system. Conversely, acquiring multi-modality data simultaneously may improve correlation and registration of images, improve temporal alignment of the acquired data, increase imaging throughput, and benefit the scanned subject by minimizing time under anesthetic. In this work, we demonstrate the feasibility and procedure for modifying a commercially available preclinical SPECT-CT platform to enable simultaneous SPECT-CT acquisition. We also evaluate the performance of simultaneous SPECT-CT tomographic imaging with this modified system. Performance was accessed using a 57Co source and image quality was evaluated with Tc99m phantoms in a series of simultaneous SPECT-CT scans.

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Roy, Ashwin, Mohamed Mansour, David Oxborough, Tarekegn Geberhiwot, and Richard Steeds. "Multi-Modality Cardiovascular Imaging Assessment in Fabry Disease." Applied Sciences 12, no. 3 (2022): 1605. http://dx.doi.org/10.3390/app12031605.

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Fabry disease (FD) is a rare X-linked lysosomal storage disorder manifesting as progressive multi-organ accumulation of sphingolipids due to deficiency in the enzyme α-Galactosidase A. Sphingolipid accumulation can take place in all cardiac cell types which manifests as left ventricular hypertrophy, microvascular ischaemia, conduction abnormalities, arrhythmia, heart failure, and valvular disease. The use of advanced cardiovascular imaging techniques have enabled clinicians to stage and prognosticate the disease and guide therapy. Transthoracic echocardiography (TTE) and cardiac magnetic resonance imaging (CMR) in conjunction are the hallmark imaging modalities to allow for this assessment. Traditionally, the assessment of cardiac involvement in FD was based on the assessment of maximal wall thickness (MWT) and the development of left ventricular hypertrophy (LVH). It is now understood that sphingolipid accumulation takes place before the development of LVH. Advances in techniques within TTE and CMR, particularly that of strain assessment and T1/T2 mapping, have meant that Fabry cardiomyopathy (FCM) can be diagnosed earlier in the disease process. This potentially provides a window for initiation of enzyme replacement therapy (ERT) at a stage where it is likely to have the most beneficial effect in reducing the high mortality associated with FCM. This review outlines the advances in multimodality imaging in staging and prognosticating FCM, as well as the applications of cardiac imaging in assessing symptoms and complications of FCM.

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Dykas, C., B. H. Rovin, M. Boesen, O. Kubassova, and P. Lipsky. "FRI0177 MULTI-MODALITY IMAGING TO EVALUATE LUPUS NEPHRITIS." Annals of the Rheumatic Diseases 79, Suppl 1 (2020): 672.2–673. http://dx.doi.org/10.1136/annrheumdis-2020-eular.5012.

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Background:Lupus nephritis (LN) remains a significant cause of morbidity and mortality in subjects with Systemic Lupus Erythematosus (SLE). The gold standard for evaluation of LN remains the kidney biopsy, whereas renal function is usually evaluated by eGFR and urinary protein:creatinine ratio. More effective and sensitive methodology is needed to assess LN and also the response to treatment. Functional imaging of the kidney using quantitative techniques has great potential, as it can assess kidney function and pathologic changes non-invasively by evaluating perfusion, oxygenation, cellular density and fibrosis.Objectives:The objective of this study was to develop a multi-modality imaging approach for the evaluation of the spectrum of pathologic changes in LN and to determine when imaging data correlated with renal functionMethods:In this multi-center study (NCT03180021), subjects who were having a standard of care renal biopsy for LN were asked to participate in the imaging evaluation. Local Institutional Review Board approval was obtained, and subjects signed an Informed Consent Form. Dynamic contrast enhanced MRI (DCE-MRI) was employed to detect changes in vascularization and perfusion, Diffusion Weighted Imaging (DWI) to assess interstitial diffusion, T2*Map/BOLD to evaluate tissue oxygenation and T1rho to evaluate fibrosis (Figure 1). Regions of interest were identified in the imaged kidneys and imaging parameters were correlated with measures of renal function, including eGFR and urinary protein: creatinine ratio. In DCE-MRI, we specifically focused on mean Maximum Enhancement (ME), mean Time to Peak Enhancement (TTP) and mean Time of Washout (Twashout) as indicators of renal perfusion.Results:Nine subjects have been evaluated to date and their imaging data assessed for quality. Evaluation of mean data from DCE-MRI has shown a significant correlation between renal perfusion and renal function. For example, as shown in the figure, the 24 hour protein concentration negatively correlated with ME (rs=-0.81, p=0.015), TTP (rs=-0.83, p=0.01) and Twashout (rs=-0.81.p=0.01, Spearman rank correlation). In addition, the protein:creatinine ratio also negatively correlated with ME (rs=-0.79, p=0.02), TTP (rs=-0.74, p=0.04) and Twashout (rs=-0.79, p=0.02, Spearman rank correlation).Conclusion:These initial results have established the feasibility of multi-modality imaging as a tool to evaluate LN in a multi-center study. Moreover, changes in perfusion detected by DCE-MRI significantly correlate with proteinuria and urinary protein:creatinine ratio. These results suggest that multiparameter imaging may contribute useful data in the evaluation of subjects with LN.Figure:Disclosure of Interests:Claire Dykas: None declared, Brad H Rovin Grant/research support from: GSK, Consultant of: GSK, Mikael Boesen Consultant of: AbbVie, AstraZeneca, Eli Lilly, Esaote, Glenmark, Novartis, Pfizer, UCB, Paid instructor for: IAG, Image Analysis Group, AbbVie, Eli Lilly, AstraZeneca, esaote, Glenmark, Novartis, Pfizer, UCB (scientific advisor)., Speakers bureau: Eli Lilly, Esaote, Novartis, Pfizer, UCB, Olga Kubassova Shareholder of: IAG, Image Analysis Group, Consultant of: Novartis, Takeda, Lilly, Employee of: IAG, Image Analysis Group, Peter Lipsky Consultant of: Horizon Therapeutics

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Quinn, Erina, Madeline Mahowald, Patricia A. Pellikka, et al. "MULTI-MODALITY CARDIAC IMAGING OF ERDHEIM-CHESTER DISEASE." Journal of the American College of Cardiology 79, no. 9 (2022): 1345. http://dx.doi.org/10.1016/s0735-1097(22)02336-1.

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Wang, Tom Kai Ming, Ossama K. Abou Hassan, Wael Jaber, and Bo Xu. "Multi-modality imaging of cardiac amyloidosis: Contemporary update." World Journal of Radiology 12, no. 6 (2020): 87–100. http://dx.doi.org/10.4329/wjr.v12.i6.87.

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Jung, Hae Won, Joon Hyung Doh, and Woo-Ik Chang. "Multi-modality imaging of a left atrial myxoma." SAGE Open Medical Case Reports 5 (January 1, 2017): 2050313X1773623. http://dx.doi.org/10.1177/2050313x17736230.

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Objectives: Although echocardiography has traditionally been used to diagnose myxoma, invasive or non-invasive coronary angiography can be useful diagnostic tool before surgery. Methods: We present a case of an angiographically detected left atrial myxoma feeding from the left circumflex coronary artery. Results: The patient underwent open-heart surgery to remove the left atrial myxoma. After ligation of feeding artery, the mass was successfully excised Conclusion: Preoperative coronary angiography can offer additional valuable information moreover detecting coronary artery disease. Because, there is sudden death risk from embolization during invasive coronary angiography, preoperative cardiac computed tomography angiography should be considered to plan the surgery of myxoma.

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Ethiraj, Dillibabu, Venkatraman Indiran, Kannan Kanakaraj, T. Ramachandra Prasad, and M. Prabakaran. "Alkaptonuria—an atypical case: multi-modality imaging review." Skeletal Radiology 48, no. 5 (2018): 819–22. http://dx.doi.org/10.1007/s00256-018-3104-4.

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Zhang, M., L. Ma, and M. Soleimani. "Dual modality ECT–MIT multi-phase flow imaging." Flow Measurement and Instrumentation 46 (December 2015): 240–54. http://dx.doi.org/10.1016/j.flowmeasinst.2015.03.005.

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Levin Klausen, Thomas, Flemming Andersen, and Brad Kemp. "Hardware and Software Approaches to Multi-Modality Imaging." Current Medical Imaging Reviews 7, no. 3 (2011): 169–74. http://dx.doi.org/10.2174/157340511796411195.

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Isorni, Marc-Antoine, Sebastien Monnot, Martin Kloeckner, Benoit Gerardin, and Sebastien Hascoet. "Innovative multi-modality imaging to assess paravalvular leak." Advances in Interventional Cardiology 15, no. 1 (2019): 120–22. http://dx.doi.org/10.5114/aic.2019.83778.

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Jones, I. W., C. J. Burrell, and G. C. Vivian. "55. Multi-modality imaging in coronary artery disease." Nuclear Medicine Communications 15, no. 4 (1994): 239. http://dx.doi.org/10.1097/00006231-199404000-00058.

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Ozturk, Mesut, Ahmet Veysel Polat, Tumay Bekci, and Yurdanur Sullu. "Angiolipoma of the Breast: Multi-modality Imaging Findings." Breast Journal 22, no. 6 (2016): 698–700. http://dx.doi.org/10.1111/tbj.12667.

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Reyes, Eliana. "Multi-modality imaging for assessment of myocardial viability?" International Journal of Cardiovascular Imaging 23, no. 6 (2007): 767–70. http://dx.doi.org/10.1007/s10554-007-9242-8.

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Kaichi, Ryota, Yu Kataoka, and Satoshi Yasuda. "Erupted coronary atheroma: insights from multi-modality imaging." International Journal of Cardiovascular Imaging 34, no. 10 (2018): 1669–71. http://dx.doi.org/10.1007/s10554-018-1378-1.

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Goldie, Fraser C., Matthew M. Y. Lee, Caroline J. Coats, and Sabrina Nordin. "Advances in Multi-Modality Imaging in Hypertrophic Cardiomyopathy." Journal of Clinical Medicine 13, no. 3 (2024): 842. http://dx.doi.org/10.3390/jcm13030842.

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Hypertrophic cardiomyopathy (HCM) is characterized by abnormal growth of the myocardium with myofilament disarray and myocardial hyper-contractility, leading to left ventricular hypertrophy and fibrosis. Where culprit genes are identified, they typically relate to cardiomyocyte sarcomere structure and function. Multi-modality imaging plays a crucial role in the diagnosis, monitoring, and risk stratification of HCM, as well as in screening those at risk. Following the recent publication of the first European Society of Cardiology (ESC) cardiomyopathy guidelines, we build on previous reviews and explore the roles of electrocardiography, echocardiography, cardiac magnetic resonance (CMR), cardiac computed tomography (CT), and nuclear imaging. We examine each modality’s strengths along with their limitations in turn, and discuss how they can be used in isolation, or in combination, to facilitate a personalized approach to patient care, as well as providing key information and robust safety and efficacy evidence within new areas of research.

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He, Yaoyao, Yulin Liu, Brandon A. Dyer, et al. "3D-printed breast phantom for multi-purpose and multi-modality imaging." Quantitative Imaging in Medicine and Surgery 9, no. 1 (2019): 63–74. http://dx.doi.org/10.21037/qims.2019.01.05.

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Nada, A., E. Mahdi, E. Mahmoud, J. Cousins, H. Ahsan, and C. Leiva-Salinas. "Multi-modality imaging evaluation of the dorsal arachnoid web." Neuroradiology Journal 33, no. 6 (2020): 508–16. http://dx.doi.org/10.1177/1971400920970919.

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Purpose Dorsal arachnoid web (DAW) is a rare intradural abnormality which is associated with progressive myelopathy. Our objective was to review multi-modality imaging techniques demonstrating the scalpel sign appearance in evaluation of DAW. Methods We retrospectively reviewed various imaging modalities of patients found to have DAW at our institution during January 2015 to February 2020. Five patients underwent surgical decompression with pathological correlation. The remaining patients were presumptively diagnosed based on the characteristic finding of scalpel sign. Clinical data were evaluated and correlated to imaging findings. All imaging modalities demonstrated the characteristic scalpel sign. Results Sixteen patients (10 females, and six males) with multi-imaging modalities were evaluated. Their mean age was 52 year (range 23–74 years). Fifteen patients underwent conventional spine MRI. Further high-resolution MR imaging techniques, e.g. 3D T2 myelographic sequence, were utilized with two patients. MRI spine CSF flow study was performed to evaluate the flow dynamic across the arachnoid web in one patient. Eight patients were evaluated with CT myelogram. Syrinx formation was discovered in seven (44%) patients; five (71%) of them underwent surgical resection and decompression. Two patients underwent successful catheter-directed fenestration of the web with clinical improvement. We found a statically significant positive correlation between the degree of cord displacement and compression with syrinx formation (r = 0.55 and 0.65 with p-value of 0.03 and 0.009, respectively). Conclusion DAW has characteristic scalpel sign independent of imaging modality. Multi-modality imaging evaluation of DAW is helpful for evaluation and surgical planning.

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Jamshidi, Neema, Alborz Feizi, Claude B. Sirlin, Joel E. Lavine, and Michael D. Kuo. "Multi-Modality, Multi-Dimensional Characterization of Pediatric Non-Alcoholic Fatty Liver Disease." Metabolites 13, no. 8 (2023): 929. http://dx.doi.org/10.3390/metabo13080929.

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Non-alcoholic fatty liver disease is a multifaceted disease that progresses through multiple phases; it involves metabolic as well as structural changes. These alterations can be measured directly or indirectly through blood, non-invasive imaging, and/or tissue analyses. While some studies have evaluated the correlations between two sets of measurements (e.g., histopathology with cross-sectional imaging or blood biomarkers), the interrelationships, if any, among histopathology, clinical blood profiles, cross-sectional imaging, and metabolomics in a pediatric cohort remain unknown. We created a multiparametric clinical MRI–histopathologic NMR network map of pediatric NAFLD through multimodal correlation networks, in order to gain insight into how these different sets of measurements are related. We found that leptin and other blood markers were correlated with many other measurements; however, upon filtering out the blood biomarkers, the network was decomposed into three independent hubs centered around histopathological features, each with associated MRI and plasma metabolites. These multi-modality maps could serve as a framework for characterizing disease status and progression and could potentially guide medical interventions.

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Wong, Kristen, Spencer Carter, Michael Luna, and M. Beth Brickner. "MULTI-MODALITY IMAGING FOR THE DIAGNOSIS OF BAFFLE STENOSIS." Journal of the American College of Cardiology 77, no. 18 (2021): 2767. http://dx.doi.org/10.1016/s0735-1097(21)04122-x.

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Guvendi Sengor, Busra, Alev Kilicgedik, Tuba Unkun, et al. "Diagnosis of Pulmonary Artery Sarcoma with Multi-modality Imaging." Turk Kardiyoloji Dernegi Arsivi-Archives of the Turkish Society of Cardiology 50, no. 2 (2022): 155–58. http://dx.doi.org/10.5543/tkda.2022.21135.

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Ricci, Fabrizio, Cesare Mantini, Chrysanthos Grigoratos, et al. "The Multi-modality Cardiac Imaging Approach to Cardiac Sarcoidosis." Current Medical Imaging Formerly Current Medical Imaging Reviews 15, no. 1 (2018): 10–20. http://dx.doi.org/10.2174/1573405614666180522074320.

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Background: Sarcoidosis is a multisystem granulomatous disease with a neglected but high prevalence of life-threatening cardiac involvement. </P><P> Discussion: The clinical presentation of Cardiac Sarcoidosis (CS) depends upon the location and extent of the granulomatous inflammation, with left ventricular free wall the most common location followed by interventricular septum. The lack of a diagnostic gold standard and the unpredictable risk of sudden cardiac death pose serious challenges for the validation of accurate and effective screening test and the management of the disease. In the last few years advanced cardiac imaging modalities such as Cardiac Magnetic Resonance (CMR) and Positron Emission Tomography (PET) have significantly improved our knowledge and understanding of CS, and have also contributed in risk stratification, assessment of inflammatory activity and therapeutic monitoring of the disease. Conclusion: In this review, we will discuss the state of the art in the diagnosis of CS focusing on the role and importance of multi-modality cardiac imaging.

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Davies, Laura H., Benjamin B. Kasten, Paul D. Benny, et al. "Re and99mTc complexes of BodP3– multi-modality imaging probes." Chem. Commun. 50, no. 98 (2014): 15503–5. http://dx.doi.org/10.1039/c4cc06367h.

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Looi, Jen-Li, and Ruvin S. Gabriel. "Multi-modality imaging in congenital aorto-right atrial tunnel." European Heart Journal – Cardiovascular Imaging 17, no. 5 (2016): 586. http://dx.doi.org/10.1093/ehjci/jev360.

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van Dalen, Jorn A. "Multi-modality nuclear medicine imaging: artefacts, pitfalls and recommendations." Cancer Imaging 7, no. 1 (2007): 77–83. http://dx.doi.org/10.1102/1470-7330.2007.0014.

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Ureche, Carina, Radu Sascău, Laura Țăpoi, et al. "Multi-modality cardiac imaging in advanced chronic kidney disease." Echocardiography 36, no. 7 (2019): 1372–80. http://dx.doi.org/10.1111/echo.14413.

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Simmons, John D. "Musculoskeletal Imaging: A Concise Multi-Modality Approach, First Edition,." Spine Journal 1, no. 3 (2001): 232–33. http://dx.doi.org/10.1016/s1529-9430(01)00111-5.

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Veeranna, Vikas, Stephen Horgan, Marc Bonaca, Michael Steigner, Hyewon Hyun, and Sharmila Dorbala. "MYO-PERICARDITIS WITH AORTITIS: UTILITY OF MULTI-MODALITY IMAGING." Journal of the American College of Cardiology 65, no. 10 (2015): A702. http://dx.doi.org/10.1016/s0735-1097(15)60702-1.

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