{"title":"基于形态计量的放射组学预测放疗后四肢软组织肉瘤的预后","authors":"","doi":"10.1016/j.radi.2024.09.048","DOIUrl":null,"url":null,"abstract":"<div><h3>Introduction</h3><p>Cancer is a leading cause of premature death worldwide. Especially cancers like soft tissue sarcomas of extremities (STSE) pose a challenge in oncologic management. Thus, the assessment of prognosis in patients with such cancers is important to select proper management strategies. Radiomics is a promising approach that has shown a wide range of potential applications including predicting prognosis. This study focused on finding out whether the morphometry-based radiomics features could be used to predict the prognosis of patients with STSE following radiotherapy.</p></div><div><h3>Methods</h3><p>The deidentified images, contours and clinical data from The Cancer Imaging Archive (TCIA) were used to evaluate thirty patients with histologically proven STSE following radiotherapy. Twenty-nine three dimensional (3D) morphometric features were extracted for each patient and the two-sample t-test (one-tailed) with the 95% confidence level was used to determine whether there was a significant difference between the patients who developed recurrence or metastasis (RM) and patients who were recurrence or metastasis-free (RMF) following radiotherapy for each morphometric feature.</p></div><div><h3>Results</h3><p>According to the findings, only surface-to-volume ratio demonstrated a significant difference (<em>p</em>-value of 0.029) between the RM and RMF after receiving radiotherapy for STSE.</p></div><div><h3>Conclusion</h3><p>Only surface-to-volume ratio could be utilized as a predictor for assessing the prognosis of patients with STSE following radiotherapy.</p></div><div><h3>Implications for practice</h3><p>The ability to predict the response after radiotherapy can facilitate the decision-making process, which will ultimately improve patient outcomes, especially considering the challenges in the management of STSE. This study provides insight that the integration of morphometry-based radiomics features into radiotherapy practice could be useful to evaluate the prognosis of patients who received radiotherapy for STSE.</p></div>","PeriodicalId":47416,"journal":{"name":"Radiography","volume":null,"pages":null},"PeriodicalIF":2.5000,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Morphometry-based radiomics for predicting prognosis in soft tissue sarcomas of extremities following radiotherapy\",\"authors\":\"\",\"doi\":\"10.1016/j.radi.2024.09.048\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Introduction</h3><p>Cancer is a leading cause of premature death worldwide. Especially cancers like soft tissue sarcomas of extremities (STSE) pose a challenge in oncologic management. Thus, the assessment of prognosis in patients with such cancers is important to select proper management strategies. Radiomics is a promising approach that has shown a wide range of potential applications including predicting prognosis. This study focused on finding out whether the morphometry-based radiomics features could be used to predict the prognosis of patients with STSE following radiotherapy.</p></div><div><h3>Methods</h3><p>The deidentified images, contours and clinical data from The Cancer Imaging Archive (TCIA) were used to evaluate thirty patients with histologically proven STSE following radiotherapy. Twenty-nine three dimensional (3D) morphometric features were extracted for each patient and the two-sample t-test (one-tailed) with the 95% confidence level was used to determine whether there was a significant difference between the patients who developed recurrence or metastasis (RM) and patients who were recurrence or metastasis-free (RMF) following radiotherapy for each morphometric feature.</p></div><div><h3>Results</h3><p>According to the findings, only surface-to-volume ratio demonstrated a significant difference (<em>p</em>-value of 0.029) between the RM and RMF after receiving radiotherapy for STSE.</p></div><div><h3>Conclusion</h3><p>Only surface-to-volume ratio could be utilized as a predictor for assessing the prognosis of patients with STSE following radiotherapy.</p></div><div><h3>Implications for practice</h3><p>The ability to predict the response after radiotherapy can facilitate the decision-making process, which will ultimately improve patient outcomes, especially considering the challenges in the management of STSE. This study provides insight that the integration of morphometry-based radiomics features into radiotherapy practice could be useful to evaluate the prognosis of patients who received radiotherapy for STSE.</p></div>\",\"PeriodicalId\":47416,\"journal\":{\"name\":\"Radiography\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2024-09-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Radiography\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1078817424002657\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Radiography","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1078817424002657","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
Morphometry-based radiomics for predicting prognosis in soft tissue sarcomas of extremities following radiotherapy
Introduction
Cancer is a leading cause of premature death worldwide. Especially cancers like soft tissue sarcomas of extremities (STSE) pose a challenge in oncologic management. Thus, the assessment of prognosis in patients with such cancers is important to select proper management strategies. Radiomics is a promising approach that has shown a wide range of potential applications including predicting prognosis. This study focused on finding out whether the morphometry-based radiomics features could be used to predict the prognosis of patients with STSE following radiotherapy.
Methods
The deidentified images, contours and clinical data from The Cancer Imaging Archive (TCIA) were used to evaluate thirty patients with histologically proven STSE following radiotherapy. Twenty-nine three dimensional (3D) morphometric features were extracted for each patient and the two-sample t-test (one-tailed) with the 95% confidence level was used to determine whether there was a significant difference between the patients who developed recurrence or metastasis (RM) and patients who were recurrence or metastasis-free (RMF) following radiotherapy for each morphometric feature.
Results
According to the findings, only surface-to-volume ratio demonstrated a significant difference (p-value of 0.029) between the RM and RMF after receiving radiotherapy for STSE.
Conclusion
Only surface-to-volume ratio could be utilized as a predictor for assessing the prognosis of patients with STSE following radiotherapy.
Implications for practice
The ability to predict the response after radiotherapy can facilitate the decision-making process, which will ultimately improve patient outcomes, especially considering the challenges in the management of STSE. This study provides insight that the integration of morphometry-based radiomics features into radiotherapy practice could be useful to evaluate the prognosis of patients who received radiotherapy for STSE.
RadiographyRADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING-
CiteScore
4.70
自引率
34.60%
发文量
169
审稿时长
63 days
期刊介绍:
Radiography is an International, English language, peer-reviewed journal of diagnostic imaging and radiation therapy. Radiography is the official professional journal of the College of Radiographers and is published quarterly. Radiography aims to publish the highest quality material, both clinical and scientific, on all aspects of diagnostic imaging and radiation therapy and oncology.