Prognostic Value of Radiomics Analysis of Skeletal Muscle After Radical Irradiation of Esophageal Cancer

Iwashita, Kazuma; Kubota, Hikaru; Nishioka, Riku; Emoto, Yukio; Kawahara, Daisuke; Ishihara, Takeshi; Miyawaki, Daisuke; Nishibuchi, Ikuno; Nagata, Yasushi; Sasaki, Ryohei

doi:10.21873/anticanres.16328

Cited by 6 publications

(8 citation statements)

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“…Recently, the significant influence of body composition on the prognosis of patients undergoing RT has attracted increasing attention. For example, Iwashita et al found that sarcopenia is closely associated with poor survival in patients with EC receiving radical irradiation [ 37 ]. Another retrospective study demonstrated that sarcopenia is an effective indicator of prognosis in patients with ESCC undergoing RT [ 38 ].…”

Section: Discussionmentioning

confidence: 99%

Association of preoperative muscle-adipose index measured by computed tomography with survival in patients with esophageal squamous cell carcinoma

Qian,

Shen,

Zhu

et al. 2024

World J Surg Onc

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Background Conventional nutritional metrics are closely associated with the prognosis of patients with radically resected esophageal squamous cell carcinoma (ESCC). Nevertheless, the prognostic implications of muscle and adipose tissue composite indexes in ESCC remain unknown. Methods We retrospectively analyzed clinicopathological data of 304 patients who underwent resected ESCC. To obtain measurements of the muscle and adipose indexes, preoperative computed tomography (CT) images were used to quantify skeletal-muscle adipose tissue. The diagnostic threshold for muscle-adipose imbalance was determined using X-tile software and used to analyze the association between the muscle-adipose index (MAI) and survival. Instantaneous risk of recurrence was assessed using a hazard function. We constructed a nomogram based on the MAI and other clinical characteristics and established a novel predictive model with independent prognostic factors. The prognostic capabilities of these nomograms were evaluated using calibration curves, receiver operating characteristic (ROC) curves, and decision-curve analysis (DCA). Results The overall survival (OS) and disease-free survival (DFS) rates in the muscle-adipose-balanced group were significantly better than those in the muscle-adipose-imbalanced group. Multivariate analyses revealed that the MAI, prognostic nutritional index (PNI), tumor stage, and tumor differentiation were independent prognostic factors for OS and DFS in patients with resected ESCC (P < 0.05). The nuclear density curve indicated a lower risk of recurrence for patients in the muscle-adipose-balanced group than that for their imbalanced counterparts. Conversely, the nuclear density curve for PNI was confounded. Postoperative radiotherapy- (RT) benefit analysis demonstrated that patients with ESCC in the muscle-adipose-balanced group could benefit from adjuvant RT. Conclusion This study confirmed that preoperative MAI could serve as a useful independent prognostic factor in patients with resected ESCC. A nomogram based on the MAI and other clinical characteristics could provide individualized survival prediction for patients receiving radical resection. Timely and appropriate nutritional supplements may improve treatment efficacy.

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Section: Discussionmentioning

confidence: 99%

Association of preoperative muscle-adipose index measured by computed tomography with survival in patients with esophageal squamous cell carcinoma

Qian,

Shen,

Zhu

et al. 2024

World J Surg Onc

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“…Univariable In addition, individual publications were able to show that modern medical imaging post-processing methods, e. g., radiomics, also allow sensitive analysis of muscle quality [46,47]. The literature in this regard is based solely on individual studies.…”

Section: Diagnosismentioning

confidence: 99%

“…The literature in this regard is based solely on individual studies. Therefore, definitive population-based statements currently cannot be made [46,47].…”

Section: Diagnosismentioning

confidence: 99%

Prognostic role of the skeletal musculature in oncology: significance, coherences and clinical implications

Surov,

Wienke,

Gutzmer

et al. 2023

Rofo

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Background Sarcopenia is defined as a loss of muscle mass and strength as well as decreased physical performance. Method The present study provides a systematic overview of the current literature in regard to the prognostic role of sarcopenia in oncology. Conclusion In oncologic patients, sarcopenia occurs in 39.6 % of cases in a curative setting and in 49.2 % in a palliative setting. Sarcopenia is associated with dose-limiting toxicity. Furthermore, sarcopenia is associated with the occurrence of postoperative complications. Also, reduced muscle mass limits overall survival in most tumors both in a curative and a palliative setting. Therefore, analysis of the skeletal musculature on staging CT should be implemented in the clinical routine in oncology. Key Points: Citation Format

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“…Its central concept is to convert images into digital information that can be mined, extracted, and analyzed, as well as to predict target associations and build model [ 14 , 15 ]. Iwashita et al reported CT radiomics and clinical data might help determine survival outcomes in patients with esophageal cancer treated with radical radiotherapy [ 16 ]. Yang et al found that radiomics can be used for chemoradiation outcome prediction in esophageal cancer [ 17 ].…”

Section: Introductionmentioning

confidence: 99%

Prediction of malignant esophageal fistula in esophageal cancer using a radiomics-clinical nomogram

Zhu,

Sun,

Chen

et al. 2024

Eur J Med Res

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Background Malignant esophageal fistula (MEF), which occurs in 5% to 15% of esophageal cancer (EC) patients, has a poor prognosis. Accurate identification of esophageal cancer patients at high risk of MEF is challenging. The goal of this study was to build and validate a model to predict the occurrence of esophageal fistula in EC patients. Methods This study retrospectively enrolled 122 esophageal cancer patients treated by chemotherapy or chemoradiotherapy (53 with fistula, 69 without), and all patients were randomly assigned to a training (n = 86) and a validation (n = 36) cohort. Radiomic features were extracted from pre-treatment CTs, clinically predictors were identified by logistic regression analysis. Lasso regression model was used for feature selection, and radiomics signature building. Multivariable logistic regression analysis was used to develop the clinical nomogram, radiomics-clinical nomogram and radiomics prediction model. The models were validated and compared by discrimination, calibration, reclassification, and clinical benefit. Results The radiomic signature consisting of ten selected features, was significantly associated with esophageal fistula (P = 0.001). Radiomics-clinical nomogram was created by two predictors including radiomics signature and stenosis, which was identified by logistic regression analysis. The model showed good discrimination with an AUC = 0.782 (95% CI 0.684–0.8796) in the training set and 0.867 (95% CI 0.7461–0.987) in the validation set, with an AIC = 101.1, and good calibration. When compared to the clinical prediction model, the radiomics-clinical nomogram improved NRI by 0.236 (95% CI 0.153, 0.614) and IDI by 0.125 (95% CI 0.040, 0.210), P = 0.004. Conclusion We developed and validated the first radiomics-clinical nomogram for malignant esophageal fistula, which could assist clinicians in identifying patients at high risk of MEF.

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Prognostic Value of Radiomics Analysis of Skeletal Muscle After Radical Irradiation of Esophageal Cancer

Cited by 6 publications

References 0 publications

Association of preoperative muscle-adipose index measured by computed tomography with survival in patients with esophageal squamous cell carcinoma

Association of preoperative muscle-adipose index measured by computed tomography with survival in patients with esophageal squamous cell carcinoma

Prognostic role of the skeletal musculature in oncology: significance, coherences and clinical implications

Prediction of malignant esophageal fistula in esophageal cancer using a radiomics-clinical nomogram

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