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Evaluation of 18F-FDG PET and DWI Datasets for Predicting Therapy Response of Soft-Tissue Sarcomas Under Neoadjuvant Isolated Limb Perfusion

医学 核医学 有效扩散系数 软组织肉瘤 软组织 肉瘤 分级(工程) 灌注 磁共振成像 标准摄取值 磁共振弥散成像 梅尔法兰 正电子发射断层摄影术 放射科 化疗 病理 内科学 土木工程 工程类
作者
Michal Chodyla,Aydın Demircioğlu,Benedikt M. Schaarschmidt,Stefanie Bertram,Nils Martin Bruckmann,Jennifer Haferkamp,Yan Li,Sebastian Bauer,Lars Erik Podleska,Christoph Rischpler,Michael Forsting,Ken Herrmann,Lale Umutlu,Johannes Grueneisen
出处
期刊:The Journal of Nuclear Medicine [Society of Nuclear Medicine and Molecular Imaging]
卷期号:62 (3): 348-353 被引量:10
标识
DOI:10.2967/jnumed.120.248260
摘要

Our purpose was to evaluate and compare the clinical utility of simultaneously obtained quantitative 18F-FDG PET and diffusion-weighted MRI datasets for predicting the histopathologic response of soft-tissue sarcoma (STS) to neoadjuvant isolated limb perfusion (ILP). Methods: In total, 37 patients with a confirmed STS of the extremities underwent 18F-FDG PET/MRI before and after ILP with melphalan and tumor necrosis factor-α. For each patient, the maximum tumor size, metabolic activity (SUV), and diffusion restriction (apparent diffusion coefficient, ADC) were determined in pre- and posttherapeutic examinations, and percentage changes during treatment were calculated. Mann–Whitney U testing and receiver-operating-characteristic analysis were used to compare the results of the different quantitative parameters to predict the histopathologic response to therapy. Results from histopathologic analysis after tumor resection served as the reference standard, and patients were defined as responders or nonresponders based on the grading scale by Salzer-Kuntschik. Results: Histopathologic analysis categorized 22 (59%) patients as responders (grades I–III) and 15 (41%) as nonresponders (grades IV–VI). Under treatment, tumors in responders showed a mean reduction in size (−9.7%) and metabolic activity (SUVpeak, −51.9%; SUVmean, −43.8%), as well as an increase of the ADC values (ADCmin, +29.4%; ADCmean, +32.8%). The percentage changes in nonresponders were −6.2% in tumor size, −17.3% in SUVpeak, −13.9% in SUVmean, +15.3% in ADCmin, and +14.6% in ADCmean. Changes in SUV and ADCmean significantly differed between responders and nonresponders (<0.01), whereas differences in tumor size and ADCmin did not (>0.05). The corresponding AUCs were 0.63 for tumor size, 0.87 for SUVpeak, 0.82 for SUVmean, 0.63 for ADCmin, 0.84 for ADCmean, and 0.89 for ratio of ADCmean to SUVpeak. Conclusion: PET- and MRI-derived quantitative parameters (SUV and ADCmean) and their combination performed well in predicting the histopathologic therapy response of STS to neoadjuvant ILP. Therefore, integrated PET/MRI could serve as a valuable tool for pretherapeutic assessment as well as monitoring of neoadjuvant treatment strategies of STS.

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