Radiography (London, England : 1995) · 2024
Morphometry-based radiomics for predicting prognosis in soft tissue sarcomas of extremities following radiotherapy.
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Sherminie L P G, Jayatilake M L, Hewavithana P B, Weerakoon B S, Vijithananda S M
Аннотация
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.
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.