Physics and imaging in radiation oncology · 2025
Detection and localization of radiation-induced pneumonitis using T 2 -mapping magnetic resonance imaging.
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Klaar Rabea, Begaj Kaltra, Rabe Moritz, Corradini Stefanie, Eze Chukwuka, Belka Claus, Sabel Bastian, Landry Guillaume, Kurz Christopher, Dinkel Julien
Аннотация
BACKGROUND AND PURPOSE: Radiation-induced pneumonitis (RP), a complication of lung radiotherapy, occurs at the earliest 6-12 weeks post-treatment. To assess RP, repeated computed tomography (CT)-scans post-radiotherapy are standard-of-care, but increase the patients' dose burden and secondary cancer risk. We propose a pipeline based on magnetic resonance imaging (MRI) T 2 -mapping acquired 2-3 months post-radiotherapy that provides an automated patient stratification and initial segmentation of the RP lung volume.
MATERIALS AND METHODS: In total, 24 lung tumor patients received MRI-guided radiotherapy at a 0.35 T MR-Linac. MRI T 2 -maps were retrieved from T 2 -weighted images acquired at a diagnostic 1.5 T MRI-scanner 8-20 weeks post-radiotherapy. Mean baseline-corrected T 2 -values were calculated in the planning target volume and the lung volume receiving ≥ 20 Gy excluding the gross tumor volume. Their stratification potential (endpoint RP grade ≥ 1) was assessed in a univariate receiver operating characteristic curve-area under the curve (ROC-AUC) analysis using bootstrapping. Significant differences were probed (Mann-Whitney U test, α Stats =0.05). Thresholding using the maximal Youden index was utilized for the T 2 -based RP segmentation. The Dice similarity coefficient (DSC), 95% Hausdorff distance (HD95), sensitivity, precision and segmentation AUC (SegAUC) were used for the comparison with the ground-truth CT-based RP segmentation.
RESULTS: RP grade ≥ 1 was diagnosed in 15/24 patients. The T 2 -values in both regions achieved significant separation of distributions (median 13.8/2.9 ms and 5.0/-2.6 ms RP/non-RP) with p -values < 0.05 and AUC ≥ 0.76. Moderate quantitative agreement was found between T 2 -based and ground-truth segmentation (DSC=0.32, HD95=20.1 mm and SegAUC=0.76).
CONCLUSION: MRI T 2 -values allow an automated RP patient stratification and initial RP lung volume estimation.
MATERIALS AND METHODS: In total, 24 lung tumor patients received MRI-guided radiotherapy at a 0.35 T MR-Linac. MRI T 2 -maps were retrieved from T 2 -weighted images acquired at a diagnostic 1.5 T MRI-scanner 8-20 weeks post-radiotherapy. Mean baseline-corrected T 2 -values were calculated in the planning target volume and the lung volume receiving ≥ 20 Gy excluding the gross tumor volume. Their stratification potential (endpoint RP grade ≥ 1) was assessed in a univariate receiver operating characteristic curve-area under the curve (ROC-AUC) analysis using bootstrapping. Significant differences were probed (Mann-Whitney U test, α Stats =0.05). Thresholding using the maximal Youden index was utilized for the T 2 -based RP segmentation. The Dice similarity coefficient (DSC), 95% Hausdorff distance (HD95), sensitivity, precision and segmentation AUC (SegAUC) were used for the comparison with the ground-truth CT-based RP segmentation.
RESULTS: RP grade ≥ 1 was diagnosed in 15/24 patients. The T 2 -values in both regions achieved significant separation of distributions (median 13.8/2.9 ms and 5.0/-2.6 ms RP/non-RP) with p -values < 0.05 and AUC ≥ 0.76. Moderate quantitative agreement was found between T 2 -based and ground-truth segmentation (DSC=0.32, HD95=20.1 mm and SegAUC=0.76).
CONCLUSION: MRI T 2 -values allow an automated RP patient stratification and initial RP lung volume estimation.