放射線誘発性肺炎のT2マッピング磁気共鳴画像法による検出と局在化

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.

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 $\ge$ 20 Gy excluding the gross tumor volume. Their stratification potential (endpoint RP grade $\ge$ 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, ${\alpha }_{\mathrm{Stats}}$ =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.

RP grade $\ge$ 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 $\ge$ 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).

MRI $T_2$ -values allow an automated RP patient stratification and initial RP lung volume estimation.