Multiparametric Evaluation of Radiomics Features and Dual-Energy CT Iodine Maps for Discrimination and Outcome Prediction of Thymic Masses

Mahmoudi, Scherwin; Gruenewald, Leon D.; Eichler, Katrin; Althoff, Friederike C.; Martin, Simon S.; Bernatz, Simon; Booz, Christian; Yel, Ibrahim; Kinzler, Maximilian N.; Ziegengeist, Nicole Suarez; Torgashov, Katerina; Mohammed, Hanin; Geyer, Tobias; Scholtz, Jan-Erik; Hammerstingl, Renate; Weber, Christophe; Hardt, Stefan E.; Sommer, Christof M.; Gruber‐Rouh, Tatjana; Leistner, David M; Vogl, Thomas J.; Koch, Vitali

doi:10.1016/j.acra.2023.03.034

Cited by 2 publications

(3 citation statements)

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“…A subcohort (thymic pathologies) of the current study has been previously reported. 18 Abbreviations: DECT, dual-energy CT; HU, hounsfield units; SD, standard deviation. iodine concentration, to differentiate between thymic carcinoma and invasive thymoma in DECT perfusion imaging.…”

Section: Discussionmentioning

confidence: 99%

“…A subcohort (thymic pathologies) of the current study has been previously reported. 18 Abbreviation: SD, standard deviation.…”

Section: (22%)mentioning

confidence: 99%

“…Altogether, the findings of our studies are in line with previous studies that investigated a multiparametric approach involving radiomic features, DECT parameters and clinical parameters to discriminate between tumours of different degrees of malignancy. 18,31 Considering the broad range of anterior mediastinal lesions, our methodology offers a comprehensive framework to improve the characterization and classification of mediastinal tumours.…”

Section: T a B L Ementioning

confidence: 99%

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Advanced biomedical imaging for accurate discrimination and prognostication of mediastinal masses

Mahmoudi

Gruenewald

Eichler

et al. 2023

Eur J Clin Investigation

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BackgroundTo investigate the potential of radiomic features and dual‐source dual‐energy CT (DECT) parameters in differentiating between benign and malignant mediastinal masses and predicting patient outcomes.MethodsIn this retrospective study, we analysed data from 90 patients (38 females, mean age 51 ± 25 years) with confirmed mediastinal masses who underwent contrast‐enhanced DECT. Attenuation, radiomic features and DECT‐derived imaging parameters were evaluated by two experienced readers. We performed analysis of variance (ANOVA) and Chi‐square statistic tests for data comparison. Receiver operating characteristic curve analysis and Cox regression tests were used to differentiate between mediastinal masses.ResultsOf the 90 mediastinal masses, 49 (54%) were benign, including cases of thymic hyperplasia/thymic rebound (n = 10), mediastinitis (n = 16) and thymoma (n = 23). The remaining 41 (46%) lesions were classified as malignant, consisting of lymphoma (n = 28), mediastinal tumour (n = 4) and thymic carcinoma (n = 9). Significant differences were observed between benign and malignant mediastinal masses in all DECT‐derived parameters (p ≤ .001) and 38 radiomic features (p ≤ .044) obtained from contrast‐enhanced DECT. The combination of these methods achieved an area under the curve of .98 (95% CI, .893–1.000; p < .001) to differentiate between benign and malignant masses, with 100% sensitivity and 91% specificity. Throughout a follow‐up of 1800 days, a multiparametric model incorporating radiomic features, DECT parameters and gender showed promising prognostic power in predicting all‐cause mortality (c‐index = .8 [95% CI, .702–.890], p < .001).ConclusionsA multiparametric approach combining radiomic features and DECT‐derived imaging biomarkers allows for accurate and noninvasive differentiation between benign and malignant masses in the anterior mediastinum.

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Section: Discussionmentioning

confidence: 99%

“…A subcohort (thymic pathologies) of the current study has been previously reported. 18 Abbreviation: SD, standard deviation.…”

Section: (22%)mentioning

confidence: 99%

Section: T a B L Ementioning

confidence: 99%

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