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计算机断层扫描图像和剂量分布图所生成的预测性皮炎与实际性皮炎的比较。

Comparison of predicted and actual dermatitis generated from computed tomography images and dose distribution maps.

作者信息

Miyabe Yasuhide, Oshiro Saori, Seki Hiroto, Muroi Yusuke, Kawashima Eriko, Hosoda Megumi, Ohashi Kento, Yamanaka Hiromu, Shao Mingliang, Sugawara Hiromi, Mizoe Jyunetsu, Komaki Ritsuko

机构信息

Sapporo Kojinkai Memorial Hospital, Sapporo High Functioning Radiotherapy Center, 1-16-1 Miyanosawa 2-jo, Nishi-ku, Sapporo-shi, Hokkaido 063-0052, Japan.

Baylor College of Medicine Houston TX One Baylor Plaza, Houston, TX 77030, United States.

出版信息

Tech Innov Patient Support Radiat Oncol. 2024 Nov 22;32:100294. doi: 10.1016/j.tipsro.2024.100294. eCollection 2024 Dec.

DOI:10.1016/j.tipsro.2024.100294
PMID:39669002
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11634977/
Abstract

Anticipating the onset, location and severity of radiation dermatitis before radiotherapy can aid in dermatological care. This study developed a method for creation of a prediction diagram for dermatitis and conducted a comparative verification between the prediction diagram and actual patient condition. The prediction diagram involved converting skin doses into 2 Gy fractionated equivalent doses using α/β of 10.0, defining regions of interest (ROIs) from 20-50 Gy at 10 Gy intervals. Overlaps between these ROIs at each dose level and the skin (external) was sequentially color-coded as blue, yellow, red, and purple. The study included four patients: two underwent head and neck treatment and two received neck and chest treatment. This approach involved a visual assessment comparing the prediction diagram with skin photographs captured at the end of treatment. Nurses marked skin sites corresponding to grades 1 and 2 on photographs, assessing their correlation with the predicted range. Visual assessment results were largely positive, although one patient exhibited slightly lower scores. Results revealed a correlation between grade 1 skin reactions and the 20 Gy regions. Grade 2 reactions were observed in regions near 30 and 40 Gy. Although discrepancies between prediction diagram and actual skin symptoms were observed in patients, a broad agreement was evident. The prediction diagram cannot accurately predict radiation dermatitis, as it does not account for skin symptoms unrelated to the dose. However, the diagram is significant as it provides physicians, nurses, and patients with concise and visually comprehensible information regarding the location of dermatitis.

摘要

在放疗前预测放射性皮炎的发作、位置和严重程度有助于皮肤科护理。本研究开发了一种创建皮炎预测图的方法,并对预测图与患者实际情况进行了对比验证。该预测图是利用10.0的α/β值将皮肤剂量转换为2Gy分次等效剂量,以10Gy间隔定义20 - 50Gy的感兴趣区域(ROI)。这些ROI在每个剂量水平与皮肤(体表)的重叠部分依次用蓝色、黄色、红色和紫色进行颜色编码。该研究纳入了4名患者:2名接受头颈部治疗,2名接受颈部和胸部治疗。此方法包括通过视觉评估将预测图与治疗结束时拍摄的皮肤照片进行比较。护士在照片上标记出对应1级和2级的皮肤部位,评估其与预测范围的相关性。视觉评估结果总体呈阳性,不过有1名患者的得分略低。结果显示1级皮肤反应与20Gy区域之间存在相关性。在30Gy和40Gy附近区域观察到了2级反应。虽然在患者中观察到预测图与实际皮肤症状之间存在差异,但总体一致性很明显。该预测图无法准确预测放射性皮炎,因为它没有考虑与剂量无关的皮肤症状。然而,该图很重要,因为它为医生、护士和患者提供了关于皮炎位置的简洁且直观易懂的信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04e6/11634977/3be5013c9102/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04e6/11634977/eab51e4a7845/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04e6/11634977/469719ed3b37/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04e6/11634977/f39cfeaca3ec/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04e6/11634977/3be5013c9102/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04e6/11634977/eab51e4a7845/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04e6/11634977/469719ed3b37/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04e6/11634977/f39cfeaca3ec/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04e6/11634977/3be5013c9102/gr4.jpg

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本文引用的文献

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A New Approach to Quantify and Grade Radiation Dermatitis Using Deep-Learning Segmentation in Skin Photographs.一种利用皮肤照片中的深度学习分割技术对放射性皮炎进行量化和分级的新方法。
Clin Oncol (R Coll Radiol). 2023 Jan;35(1):e10-e19. doi: 10.1016/j.clon.2022.07.001. Epub 2022 Jul 30.
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NTCP Models for Severe Radiation Induced Dermatitis After IMRT or Proton Therapy for Thoracic Cancer Patients.IMRT或质子治疗后胸段癌患者严重放射性皮炎的NTCP模型
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