1. Pre-Treatment Apparent Diffusion Coefficient Histogram Metrics as a Predictor of Local Tumor Control After Proton Beam Therapy in Patients With Hepatocellular Carcinomas
- Author
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Khin Khin Tha, Sodai Tanaka, Hidefumi Aoyama, Koichi Yasuda, Y. Fujita, Y. Uchinami, Hiroshi Taguchi, Masaya Tamura, Kentaro Nishioka, F. Koizumi, Takashi Mori, Seishin Takao, Shinichi Shimizu, Yoichi M. Ito, M. Otsuka, Norio Katoh, Kenneth Sutherland, and Hideki Minatogawa
- Subjects
Cancer Research ,Percentile ,Reproducibility ,Radiation ,business.industry ,Radiofrequency ablation ,Intraclass correlation ,medicine.disease ,law.invention ,Oncology ,law ,Statistical significance ,Histogram ,Hepatocellular carcinoma ,Medicine ,Effective diffusion coefficient ,Radiology, Nuclear Medicine and imaging ,business ,Nuclear medicine - Abstract
PURPOSE/OBJECTIVE(S) Apparent diffusion coefficient (ADC) values extractable by diffusion-weighted imaging (DWI) are reported as useful in predicting the outcome of surgery and radiofrequency ablation (RFA) in hepatocellular carcinoma (HCC). However, their relationship with local tumor control (LC) after proton beam therapy (PBT) has not been fully evaluated. This study aimed to investigate interobserver variability in ADC histogram metrics and their usefulness in predicting LC in HCC patients who underwent PBT. MATERIALS/METHODS The ADC maps of the liver of HCC patients who underwent PBT between 2015 and 2020 were reviewed. The inclusion criteria were imaging DWI at 1.5T within 6 weeks before PBT and the largest tumor dimension between 2 and 10 cm. Twenty-nine patients and 32 tumors were eligible. Axial DWI was acquired using a single-shot spin-echo echo-planar sequence and the b values of 0 and 1000 s mm-2. The ADC maps generated were transferred to a workstation. Five board-certified radiation oncologists (ROs) contoured the whole tumor regions-of-interest (ROIs) on these maps, using anatomical images obtained together as reference. For each ROI, the minimum (ADCmin), mean (ADCmean), maximum (ADCmax), and the 5th (ADC5), 25th (ADC25), 50th (ADC50), 75th (ADC75), and 95th (ADC95) percentiles were extracted. The intraclass correlation coefficient (2,1) (ICC) was calculated to determine interobserver reproducibility: ICC of 0.75 - 0.90 was considered good and > 0.90 excellent. The ADC metrics were averaged among 5 ROs. The optimal cut-off values that determined LC, i.e., non-progressive disease (PD) based on the modified RECIST, were identified using receiver-operating characteristics (ROC) analysis. The LC rates were calculated using the Kaplan-Meier method, and statistical significance was assessed by log-rank test. RESULTS The median calculated biologically effective dose (α / β = 10) was 97 GyE. With a median follow-up of 39 months (5 - 62), 5 tumors had local PD. The ADCmin, ADCmean, ADCmax, ADC5, ADC25, ADC50, ADC75, and ADC95 of all tumors ranged between 0 - 1131, 748 - 1726, 1566 - 3149, 396 - 1430, 600 - 1566, 723 - 1719, 858 - 1874, and 1166 - 2426 (×10-6 mm 2 s-1), respectively. The ICC were 0.761, 0.969, 0.513, 0.864, 0.978, 0.983, 0.974, and 0.859, respectively. For ADCmean, ADC25, ADC50, and ADC75 which showed excellent reproducibility, the optimal cut-off values to determine LC were 1025, 1005, 1156, and 1132 (×10-6 mm 2 s-1), respectively. The tumors with higher ADC metrics had higher 2-year LC rates than their counterparts (100 % vs 40 %, P = 0.002; 100% vs 74%, P = 0.011; 100% vs 76%, P = 0.024; 100% vs 25%, P < 0.001, respectively). CONCLUSION ADCmean, ADC25, ADC50, and ADC75 showed excellent interobserver reproducibility. Pre-treatment ADC histogram metrics may be useful in predicting LC after PBT in HCC.
- Published
- 2021
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