Purpose: Retroperitoneal lymph node metastases are rare in colorectal cancer. Optimal treatment strategies are still unknown. Patients and Methods: We retrospectively enrolled colorectal cancer patients who had received radiotherapy for retroperitoneal lymph node metastases from 2009 to 2018. Patients with isolated retroperitoneal lymph node metastases or retroperitoneal lymph nodes with extra-retroperitoneal metastases were all included. A median dose of 60 Gy was delivered. Results: A total of 68 patients were enrolled in this study; 28 (41%) of them had extraretroperitoneal metastases. In the isolated retroperitoneal lymph node metastases group, complete response was found in 5 patients (12.5%), partial response was achieved in 20 patients (50%), 9 patients (22.5%) had stable disease. The 1-, 2-and 3-year local control rates were 87.5%, 77.5%, and 70%. In the extra-retroperitoneal metastases group, the disease control rate was 75%, including complete response in 1 patient (3.6%), partial response in 4 patients (14.3%) and stable disease in 16 patients (57.1%). The 1-, 2-and 3-year local control rates were 57.1%, 42.8%, and 0%. The median overall survival was 59.4 months and 19 months in the isolated retroperitoneal lymph node metastases group and extra-retroperitoneal metastases group, respectively. In the isolated retroperitoneal lymph node metastases group, the 1-year and 3-year overall survival values were 90.2% and 75.8%, respectively. The 1-year and 3-year progression-free survival values were 57.9% and 0%, respectively. The extra-retroperitoneal metastases group experienced worse survival outcome (1-year overall survival: 57.9%, P<0.05; and 1-year progression-free survival: 22.5%, P<0.05). Conclusion: For patients with isolated retroperitoneal lymph node metastases, radiotherapy combined with systemic treatment can be used as a method to achieve no evidence of disease and can result in good local control and survival. For patients with extra-retroperitoneal metastases, although the survival is much worse than that of isolated retroperitoneal lymph node metastases, radiotherapy is an effective palliative treatment to relieve pain and obstruction based on systemic treatment.
Purpose: To investigate the potential value of magnetic resonance imaging (MRI) in predicting response relevance to total neoadjuvant treatment (TNT) in locally advanced rectal cancer. Methods: We analyzed MRI of 71 patients underwent TNT from 2015 to 2017 retrospectively. We categorized the response of TNT as CR (complete response) vs non-CR, and high vs moderate vs low sensitivity. Logistic regression analysis was used to identify the best predictors of response. Diagnostic performance was assessed using receiver operating characteristic curve analysis. Results: Post-ICT (induction chemotherapy) ∆TL (tumor length), post-CRT (concurrent chemoradiotherapy) ∆LNN (the numbers of lymph node metastases), post-CCT (consolidation chemotherapy) ∆S DWI (maximum cross-sectional area of tumor on diffusion-weighted imaging), post-CCT ADC T (the mean apparent diffusion coefficient values of tumor) and post-CCT ∆LNV (volume of lymph node) were the best CR predictors. Post-ICT ∆TL, post-CRT EMVI (extramural vascular invasion) and post-CCT ∆S T2 (S on T2-weight) were the best significant factors for high sensitivity. Conclusion: Post-ICT ∆TL may be an early predictor of CR and high sensitivity to TNT. Dynamic analysis based on MRI between baseline and post-CCT could provide the most valuable prediction of CR. The grouping modality of CR vs non-CR may be more suitable for treatment response prediction than high vs moderate vs low sensitivity.
Purpose To develop a model for predicting response to total neoadjuvant treatment (TNT) for patients with locally advanced rectal cancer (LARC) based on baseline magnetic resonance imaging (MRI) and clinical data using artificial intelligence methods. Methods Baseline MRI and clinical data were curated from patients with LARC and analyzed using logistic regression (LR) and deep learning (DL) methods to predict TNT response retrospectively. We defined two groups of response to TNT as pathological complete response (pCR) versus non-pCR (Group 1), and high sensitivity [tumor regression grade (TRG) 0 and TRG 1] versus moderate sensitivity (TRG 2 or patients with TRG 3 and a reduction in tumor volume of at least 20% compared to baseline) versus low sensitivity (TRG 3 and a reduction in tumor volume <20% compared to baseline) (Group 2). We extracted and selected clinical and radiomic features on baseline T2WI. Then we built LR models and DL models. Receiver operating characteristic (ROC) curves analysis was performed to assess predictive performance of models. Results Eighty-nine patients were assigned to the training cohort, and 29 patients were assigned to the testing cohort. The area under receiver operating characteristics curve (AUC) of LR models, which were predictive of high sensitivity and pCR, were 0.853 and 0.866, respectively. Whereas the AUCs of DL models were 0.829 and 0.838, respectively. After 10 rounds of cross validation, the accuracy of the models in Group 1 is higher than in Group 2. Conclusion There was no significant difference between LR model and DL model. Artificial Intelligence-based radiomics biomarkers may have potential clinical implications for adaptive and personalized therapy.
Purpose Regional lymph node recurrence (RLNR) in gastric cancer is uncommon. We investigated the effects of radiotherapy combined with chemotherapy against limited RLNR and analyzed the regularity of regional lymph node recurrence and metastasis. Patients and Methods This retrospective study included 34 gastric cancer patients with limited RLNR after D2 lymphadenectomy between January 2012 and May 2018. All patients received systemic chemotherapy and local radiotherapy with median dose of 52.5 Gy (30–66 Gy in fractions of 1.8–3.0 Gy daily, five times weekly). All sites of recurrent and metastatic lymph nodes were collected and analyzed. Results The median follow-up was 19 months (range 7–60 months). After treatment, complete response and partial response were observed in 32.4% and 55.9% of patients, respectively. The median overall survival (OS) and progression-free survival (PFS) were 18 months and 13 months. On multivariate analysis, age (≤60 vs >60) was associated with a significantly better OS (p = 0.025) and radiation dose (<54 Gy vs ≥54 Gy) was considered as an independent prognostic factor for PFS (p = 0.000). During radiotherapy, three patients developed grade 3 gastrointestinal toxicity, and no deaths were related to the treatments. The most commonly metastatic lymph nodes were the No. 4, No. 3, No. 6, No. 5, No. 7, No. 9, and No. 8 nodes; the recurrent lymph nodes were mainly located in the No. 16b, No. 16a, No. 9, No. 14, No. 7, No. 13, and No. 8 nodes. Conclusion The selected gastric cancer patients with limited RLNR may benefit from radiotherapy combined with chemotherapy. High-dose radiotherapy (≥54 Gy) lead to better PFS and tend to extend OS. The major lymph node recurrence sites were in the gastric vascular region (especially No. 16a/b nodes).
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