食道癌に対する化学放射線療法による急性期有害事象予測のための放射線感受性評価

内容の要約広島大学(Hiroshima University)博士(医学)Doctor of Philosophy in Medical Sciencedoctora

Quantifying esophageal motion during free-breathing and breath-hold using fiducial markers in patients with early-stage esophageal cancer.

INTRODUCTION:Cardiac toxicity after definitive chemoradiotherapy for esophageal cancer is a critical issue. To reduce irradiation doses to organs at risk, individual internal margins need to be identified and minimized. The purpose of this study was to quantify esophageal motion using fiducial makers based on four-dimensional computed tomography, and to evaluate the inter-CBCT session marker displacement using breath-hold. MATERIALS AND METHODS:Sixteen patients with early stage esophageal cancer, who received endoscopy-guided metallic marker placement for treatment planning, were included; there were 35 markers in total, with 9, 15, and 11 markers in the upper thoracic, middle thoracic, and lower thoracic/esophagogastric junction regions, respectively. We defined fiducial marker motion as motion of the centroidal point of the markers. Respiratory esophageal motion during free-breathing was defined as the amplitude of individual marker motion between the consecutive breathing and end-expiration phases, derived from four-dimensional computed tomography. The inter-CBCT session marker displacement using breath-hold was defined as the amplitudes of marker motion between the first and each cone beam computed tomography image. Marker motion was analyzed in the three regions (upper thoracic, middle thoracic, and lower thoracic/esophagogastric junction) and in three orthogonal directions (right-left; anterior-posterior; and superior-inferior). RESULTS:Respiratory esophageal motion during free-breathing resulted in median absolute maximum amplitudes (interquartile range), in right-left, anterior-posterior, and superior-inferior directions, of 1.7 (1.4) mm, 2.0 (1.5) mm, and 3.6 (4.1) mm, respectively, in the upper thoracic region, 0.8 (1.1) mm, 1.4 (1.2) mm, and 4.8 (3.6) mm, respectively, in the middle thoracic region, and 1.8 (0.8) mm, 1.9 (2.0) mm, and 8.0 (4.5) mm, respectively, in the lower thoracic/esophagogastric region. The inter-CBCT session marker displacement using breath-hold resulted in median absolute maximum amplitudes (interquartile range), in right-left, anterior-posterior, and superior-inferior directions, of 1.3 (1.0) mm, 1.1 (0.7) mm, and 3.3 (1.8) mm, respectively, in the upper thoracic region, 0.7 (0.7) mm, 1.1 (0.4) mm, and 3.4 (1.4) mm, respectively, in the middle thoracic region, and 2.0 (0.8) mm, 2.6 (2.2) mm, and 3.5 (1.8) mm, respectively, in the lower thoracic/esophagogastric region. CONCLUSIONS:During free-breathing, esophageal motion in the superior-inferior direction in all sites was large, compared to the other directions, and amplitudes showed substantial inter-individual variability. The breath-hold technique is feasible for minimizing esophageal displacement during radiotherapy in patients with esophageal cancer

Predicting the Local Response of Esophageal Squamous Cell Carcinoma to Neoadjuvant Chemoradiotherapy by Radiomics with a Machine Learning Method Using 18F-FDG PET Images

Background: This study aimed to propose a machine learning model to predict the local response of resectable locally advanced esophageal squamous cell carcinoma (LA-ESCC) treated by neoadjuvant chemoradiotherapy (NCRT) using pretreatment 18-fluorodeoxyglucose positron emission tomography (FDG PET) images. Methods: The local responses of 98 patients were categorized into two groups (complete response and noncomplete response). We performed a radiomics analysis using five segmentations created on FDG PET images, resulting in 4250 features per patient. To construct a machine learning model, we used the least absolute shrinkage and selection operator (LASSO) regression to extract radiomics features optimal for the prediction. Then, a prediction model was constructed by using a neural network classifier. The training model was evaluated with 5-fold cross-validation. Results: By the LASSO analysis of the training data, 22 radiomics features were extracted. In the testing data, the average accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve score of the five prediction models were 89.6%, 92.7%, 89.5%, and 0.95, respectively. Conclusions: The proposed machine learning model using radiomics showed promising predictive accuracy of the local response of LA-ESCC treated by NCRT

Efficacy of Supportive Care for Radiodermatitis in Patients with Head and Neck Cancer: Supplementary Analysis of an Exploratory Phase II Trial

Self-care demonstrated efficacy in preventing severe acute radiation dermatitis among patients with head and neck squamous cell carcinoma undergoing chemoradiotherapy (CRT). This prospective trial aimed to confirm the feasibility and safety of transcutaneous electrical sensory stimulation while examining the relationship between changes in self-care behavior through supportive care interventions and the severity of acute radiation dermatitis during CRT. Patients underwent assessments for dermatitis grading (Grades 1 to ≥3) and were interviewed regarding self-care practices. The self-care questionnaires comprised six items, and a point was deducted for each task that the patient could not perform independently. Statistical analysis was performed to determine the association between G3 radiation dermatitis and the lowest self-care behavior scores. Of the 10 patients enrolled, three experienced G3 dermatitis. During CRT, six patients maintained their initial scores and did not develop ≥G3 dermatitis. Meanwhile, three of four patients with decreased scores exhibited ≥G3 dermatitis. The group with ≥G3 dermatitis had significantly lower scores than those with ≤G2 dermatitis, suggesting that the inability of patients to perform self-care routinely may lead to severe acute radiation dermatitis. Further prospective studies are needed to confirm the potential of self-care interventions in preventing severe dermatitis

An overview of stereotactic body radiation therapy for hepatocellular carcinoma

Introduction: According to several guidelines, stereotactic body radiation therapy (SBRT) for early hepatocellular carcinoma (HCC) can be considered an alternative to other modalities, such as resection, radiofrequency ablation (RFA), and transarterial chemoembolization (TACE), or when these therapies have failed or are contraindicated. This article reviews the current status of SBRT for the treatment of HCC. Areas covered: From the results of many retrospective reports, SBRT is a promising modality with an excellent local control of almost 90% at 2–3 years and acceptable toxicities. Currently there are no randomized trials to compare SBRT and other modalities, such as resection, RFA, and TACE, but many retrospective reports and propensity score matching have shown that SBRT is comparable to the different modalities. Repeated SBRT for intra-hepatic recurrent HCC also resulted in high local control with safety and satisfactory overall survival, which were comparable to those of other curative local treatments. Expert opinion: Despite the good results of SBRT, the conclusions of the comparisons of SBRT and other modalities are still controversial. Further studies, including randomized phase III studies to define that patients are more suitable for each curative local treatment, are needed

Patient characteristics.

<p>Patient characteristics.</p

Contouring of metallic markers.

<p>Metal markers, placed by endoscopy to identify tumor location, were contoured in (A) four-dimensional computed tomography (4D-CT) and (B) cone beam CT (CBCT).</p

Plots of inter-CBCT session marker displacement using breath-hold.

<p>This figure provides plots of inter-CBCT session marker displacement using breath-hold. CBCT data based on the first CBCT scan are shown. Three, four, and five CBCT scans were performed in 7, 4, and 5 patients, respectively. The different colors stand for the data from the different metal markers. CBCT: Cone beam computed tomography; Ut: upper thoracic esophagus; Mt: middle thoracic esophagus; Lt: lower thoracic esophagus /esophagogastric junction; RL: right–left; AP: anterior–posterior; SI: superior-inferior.</p