中国抗癌协会神经内分泌肿瘤诊治指南（2022年版）

神经内分泌肿瘤（neuroendocrine neoplasm,NEN）是一类起源于肽能神经元和神经内分泌细胞,具有神经内分泌分化并表达神经内分泌标志物的少见肿瘤,可发生于全身各处,以肺及胃肠胰NEN（gastroenteropancreatic neuroendocrine neoplasm, GEP-NEN）最常见。国内外研究数据均提示,NEN的发病率在不断上升。美国流行病学调查结果显示,与其他类型肿瘤相比,NEN的发病率上升趋势更为显著。中国抗癌协会神经内分泌肿瘤专委会在现有循证医学证据基础上,结合已有国内外指南和共识,制订了首版中国抗癌协会神经内分泌肿瘤诊治指南,为临床工作者提供参考。     

Étude de faisabilité : l’utilisation de l’imagerie médicale en éducation thérapeutique en radiothérapie

PurposeAssess the feasibility of a randomized controlled trial (RCT) exploring the use of medical imaging as a therapeutic education (TPE) intervention in external radiation therapy.Materials and methodsExperimental feasibility trial of “RCT” type carried out in a single-center, between November 2019 and March 2020, following adult patients treated by thoracic radiotherapy. In addition to the information usually given, the experimental group benefited from an intervention consisting in the visualization of their own medical images using the open-source software “Stone of Orthanc”.ResultsForty-nine patients were recruited with a refusal rate of 8.16% (4/49). 20 patients were withdrawn from the study for health reasons (COVID), 10 for medical reasons. All the remaining 15 participants completed the process. Although not significant, the experimental group showed a median gain in the perception of knowledge compared to the control group (+ 1.9 (1.6 – 2.2)) vs (+ 1.4 (1.4 – 1.8)), as well as a decrease in scores related to anxiety (? 3.0 (?4.5 - (?2.0)) vs ? 1.0 (?5.0 - 0.0)) and emotional distress ((? 5.0 (? 7.5 - (? 3.5)) vs (? 2.0 (? 5.0 - (? 1.0)) A significant reduction (p = 0.043) is observed for the depression score ((? 2.0 (?3.0 - (?1.5)) vs (0.0 (0.0 – 0.0)).ConclusionThis study demonstrates the feasibility of the project, with promising preliminary results. Some adaptations in order to conduct a larger-scale RCT are highlighted.     

Preoperative comprehensive malignancy risk estimation for thyroid nodules: Development and verification of a network-based prediction model

BackgroundIn order to avoid excessive treatment of thyroid nodules in the clinic, it is necessary to find a simple and practical analysis method to comprehensively and accurately reflect benign or malignant thyroid nodules. This study aimed to construct and validate a comprehensive and reliable network-based predictive model using a variety of imaging and laboratory criteria for thyroid nodules to stratify the risk of malignancy prior to surgery.MethodsWe retrospectively analyzed data from patients who underwent surgical treatment for thyroid nodules at the Thyroid and Breast Diagnosis and Treatment Center of Weifang Hospital of Traditional Chinese Medicine between January 2018 and December 2020. Binary logical regression analysis was performed to predict whether nodules were malignant or benign. The developmental dataset included 457 patients (January 2018–December 2020). The validation set included separate data points (n = 225, January 2018–December 2020).ResultsIn this study, criteria that showed significant predictive value for malignant nodules included TI-RADS: 4b (p = 0.065); Bethesda IV, Bethesda V, Bethesda VI (P < 0.0001); BRAF^V600E mutation (P < 0.0001); Calcitonin>5 pg/ml (p = 0.0037); and FNA-Tg>30 ng/ml (p = 0.0003). A 10-grade risk scoring system was developed. The risk of malignancy risk ranged from 2.06% to 100% and was positively associated with increasing risk grade. The areas under the receiver-operating characteristic curve of the development and validation sets were 0.972 and 0.946, respectively.ConclusionA simple, comprehensive and reliable web-based predictive model was designed using a variety of imaging and laboratory criteria to stratify thyroid nodules by probability of malignancy.     

Biopsia selectiva de ganglio centinela en cáncer de mama, ¿está justificada la espera al resultado intraoperatorio?

IntroductionIn our institution, the study of selective sentinel node biopsy (SLNB) is performed intraoperatively. The main objective of our study is to know the proportion of patients who benefits from the waiting of the results of SLNB.MethodsA retrospective analysis of patients operated on our center between January 1 st, 2018 and June 30, 2019 was carried out. We included women diagnosed with T1–T2 tumors, treated by lumpectomy and SLNB studied using OSNA method.ResultsOur study included 149 women. There were not statistically significant differences in terms of demographic data between the group treated with axillary lymph node dissection (ALND) and exclusively SLNB group. After analysis of SLN intraoperatively, there were performed 18 axillary lymphadenectomies. Only in six of these 18 cases, three or more sentinel nodes were founded. The location of the tumor, the presence of lymphovascular permeation and the total tumor load (TTL) showed statistically significant differences between groups. Only the TTL was established as the independent factor of the need for ALND.ConclusionsObtaining a deferred result of the SLNB allowed reducing the time of anesthesia and occupation of the operating room, since in a high percentage of cases an additional procedure is not performed.     

脑转移瘤影像组学研究进展

脑转移瘤是成人最常见的颅内肿瘤,发病率呈上升趋势。影像组学可对医学影像进行定量分析处理来指导临床实践。近年来,基于CT、MRI的影像组学逐渐应用于脑转移瘤的精准诊疗,如肿瘤精准检测和分割、与其他脑肿瘤的鉴别诊断、原发肿瘤的判别、疗效评价及预后预测等。本文就脑转移瘤影像组学研究现状予以综述。     

Islanded facial artery osteomyomucosal/osseous flap in head and neck reconstruction

A local pedicled vascularized bone flap can prevent the morbidity and cost of free bone flap surgery in small segmental bone defects or long cartilaginous defects of the head and neck. Such flaps can also be useful in patients who are high risk for surgery. The periosteal vascularity of the mandible can be used to design islanded facial artery-based bone flaps, which can be utilized to that extent. Two patients with a small segmental mandibulectomy defect and one patient with a long cricotracheal resection defect underwent reconstruction using three different designs of islanded facial artery osteomyomucosal/osseous flap (iFOMM). The patients had a minimum follow-up period of 18 months. All flaps were successful, with satisfactory healing and without any functional deficit or disease at last follow-up.     

Deep learning radiomics based on contrast enhanced computed tomography predicts microvascular invasion and survival outcome in early stage hepatocellular carcinoma

ObjectiveTo evaluate the performance of a deep learning (DL)-based radiomics strategy on contrast-enhanced computed tomography (CT) to predict microvascular invasion (MVI) status and clinical outcomes, recurrence-free survival (RFS) and overall survival (OS) in patients with early stage hepatocellular carcinoma (HCC) receiving surgical resection.MethodsAll 283 eligible patients were included retrospectively between January 2008 and December 2015, and assigned into the training cohort (n = 198) and the testing cohort (n = 85). We extracted radiomics features via handcrafted radiomics analysis manually and DL analysis of pretrained convolutional neural networks via transfer learning automatically. Support vector machine was adopted as the classifier. A clinical-radiological model for MVI status integrated significant clinical features and the radiological signature generated from the radiological model with the optimal area under the receiver operating characteristics curve (AUC) in the testing cohort. Otherwise, DL-based prognostic models were constructed in prediction of recurrence and mortality via Cox proportional hazard analysis.ResultsThe clinical-radiological model for MVI represented an AUC of 0.909, accuracy of 96.47%, sensitivity of 90.91%, specificity of 97.30%, positive predictive value of 83.33%, and negative predictive value of 98.63% in the testing cohort. The clinical-radiological models for identification of RFS and OS outperformed prediction performance of the clinical model or the DL signature alone. The DL-based integrated model for prognostication showed great predictive value with significant classification and discrimination abilities after validation.ConclusionsThe integrated DL-based radiomics models achieved accurate preoperative prediction of MVI status, and might facilitate predicting tumor recurrence and mortality in order to optimize clinical decisions for patients with early stage HCC.