CT radiomics-based long-term survival prediction for locally advanced non-small cell lung cancer patients treated with concurrent chemoradiotherapy using features from tumor and tumor organismal environment.

BACKGROUND: Definitive concurrent chemoradiotherapy (CCRT) is the standard treatment for locally advanced non-small cell lung cancer (LANSCLC) patients, but the treatment response and survival outcomes varied among these patients. We aimed to identify pretreatment computed tomography-based radiomics features extracted from tumor and tumor organismal environment (TOE) for long-term survival prediction in these patients treated with CCRT. METHODS: A total of 298 eligible patients were randomly assigned into the training cohort and validation cohort with a ratio 2:1. An integrated feature selection and model training approach using support vector machine combined with genetic algorithm was performed to predict 3-year overall survival (OS). Patients were stratified into the high-risk and low-risk group based on the predicted survival status. Pulmonary function test and blood gas analysis indicators were associated with radiomic features. Dynamic changes of peripheral blood lymphocytes counts before and after CCRT had been documented. RESULTS: Nine features including 5 tumor-related features and 4 pulmonary features were selected in the predictive model. The areas under the receiver operating characteristic curve for the training and validation cohort were 0.965 and 0.869, and were reduced by 0.179 and 0.223 when all pulmonary features were excluded. Based on radiomics-derived stratification, the low-risk group yielded better 3-year OS (68.4% vs. 3.3%, p < 0.001) than the high-risk group. Patients in the low-risk group had better baseline FEV1/FVC% (96.3% vs. 85.9%, p = 0.046), less Grade ≥ 3 lymphopenia during CCRT (63.2% vs. 83.3%, p = 0.031), better recovery of lymphopenia from CCRT (71.4% vs. 27.8%, p < 0.001), lower incidence of Grade ≥ 2 radiation-induced pneumonitis (31.6% vs. 53.3%, p = 0.040), superior tumor remission (84.2% vs. 66.7%, p = 0.003). CONCLUSION: Pretreatment radiomics features from tumor and TOE could boost the long-term survival forecast accuracy in LANSCLC patients, and the predictive results could be utilized as an effective indicator for survival risk stratification. Low-risk patients might benefit more from radical CCRT and further adjuvant immunotherapy. TRIAL REGISTRATION: retrospectively registered.

Prognostic value of early radiological response to first-line platinum-containing chemotherapy in patients with metastatic nasopharyngeal carcinoma.

BACKGROUND: To explore the prognostic value of early radiological response (ERR) to first-line platinum-containing chemotherapy in patients with metastatic nasopharyngeal carcinoma (mNPC), as well as its correlation with the best radiological response (BRR). PATIENTS AND METHODS: A total of 756 mNPC patients with measurable lesions who received first-line platinum-containing chemotherapy were enrolled in this study. ERR was defined as complete or partial response after 6 weeks of chemotherapy according to the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. We performed survival analyses according to the radiological response after repeated chemotherapy. Log-rank test and Cox regression were used to analyze the survival data. RESULTS: About 470 patients achieved ERR and 78 patients achieved subsequent response (objective response after repeated chemotherapy). ERR patients had better OS (P < .001, median OS: 34.3 vs 22.2 months) and PFS (P < .001, median PFS: 10.2 vs 7.4 months) than non-ERR ones. ERR (OS: HR = 0.591, 95% CI, 0.495-0.705, P < .001, PFS: HR = 0.586, 95% CI, 0.500-0.686, P < .001) was independently prolonged survival compared with non-ERR ones. Besides, ERR was significantly correlated with the BRR (Kappa: 0.73; Pearson: 0.74, P < .001), and had significantly longer OS and PFS than patients with subsequent response, respectively. CONCLUSION: ERR is an independent prognostic factor in determining survival in mNPC patients received first-line platinum-containing chemotherapy, which may be a more sensitive predictor to assess overall efficacy of systemic treatment than BRR in mNPC. Prospective validation studies are needed.

[Application of dynamic contrast enhancement MRI and post-processing technique for diagnosis of breast cancer].

BACKGROUND AND OBJECTIVE: Magnetic resonance imaging (MRI), an advanced non-invasive technique, is regarded as one of the potential modalities in the diagnosis of breast cancer. This study was to investigate the application of dynamic contrast enhancement MRI and 3D reconstruction images in diagnosing breast tumors. METHODS: From May 2006 to September 2007, 30 patients with breast diseases were scanned with MRI in Sun Yat-sen University Cancer Center. MR plain scans, dynamic contrast enhancement scans were performed, and 3D reconstruction images were obtained. The normal breast tissue was used as control, and the maximum slope ratio was calculated. RESULTS: Forty-nine lesions were found in 30 patients, with an accuracy rate of 93.3%. CONCLUSION: MRI scan is an effective and specific modality for the diagnosis of breast diseases with high sensitivity and accuracy. Dynamic contrast enhancement MRI, image subtraction, time-signal intensity curve, 3D reconstruction images and the maximum slope ratio are helpful to make the correct diagnosis of breast lesions.