A Primary Report 166 Cases of Abdominal or Pelvic Neuroblastoma Surgery Utilizing the International Neuroblastoma Surgical Report Form (INSRF).

BACKGROUND AND AIMS: Surgery is pivotal in the management of neuroblastoma (NB), particularly in patients with Image-Defined Risk Factors (IDRFs). The International Neuroblastoma Surgical Report Form (INSRF) was introduced to enhance surgical reporting quality and analyze the defining role of extensive surgery in NB. This study reports our experience with INSRF and explores new criteria for evaluating the extent of surgical resection. METHODS: INSRF was deployed to critically analyze 166 patients with abdominal or pelvic NB who underwent surgery at our department between October 2021 and June 2023. Patient demographics, clinical characteristics, surgical datasets, and postoperative complications were described in detail. Receiver operating characteristic (ROC) curves were used to explore a new method to evaluate the extent of resection. A questionnaire was formulated to obtain attitudes/feedback and commentary from surgical oncologists with INSRF. RESULTS: 166 neuroblastoma patients with a median disease age 36.50 months. This study collated 320 INSRF reports. Among the 166 index cases, 137 were documented by two surgeons, with a concordance rate of 16.78%. Items with high inconsistency were (i) the extent of tumor resection (29.20%), (ii) renal vein involvement (25.55%), (iii) abdominal aorta encasement (16.79%), and (iv) mesenteric infiltration (17.52%). According to INSRF, the extent of resection was complete excision in 86 (51.81%) patients, minimal residual tumor < 5 cm3 in 67 (40.36%) patients, and incomplete excision > 5 cm3 in 13 (7.83%) patients. In ROC curve analysis, the number of vessels encased by tumors > 3 had a high predictive value in determining that a tumor could not be completely resected (AUC 0.916, sensitivity 0.838, specificity 0.826) using INSRF as the gold standard reference. The questionnaires showed that surgeons agreed that the extent of resection and tumor involvement of organ/vascular structures were important, while the definition and intervention(s) of intraoperative complications were less operational and understandable. CONCLUSIONS: INSRF has significant clinical application in neuroblastoma surgery. The extent of resection can be predicted based on the number of tumor-encased blood vessels. Supplementary information should be considered with the INSRF to aid practitioner reporting. Multicenter studies are needed to explore the defining role of INSRF in NB surgical management.

Risk factors, impact and treatment of postoperative lymphatic leakage in children with abdominal neuroblastoma operated on by laparotomy.

BACKGROUND: Lymphatic leakage is one of the postoperative complications of neuroblastoma. The purpose of this study is to summarize the clinical characteristics and risk factors of lymphatic leakage and try to find effective prevention and treatment measures. METHODS: A retrospective study included 186 children with abdominal neuroblastoma, including 32 children of lymphatic leakage and 154 children of non-lymphatic leakage. The clinical information, surgical data, postoperative abdominal drainage, treatment of lymphatic leakage and prognosis of the two groups were collected and analyzed. RESULTS: The incidence of lymphatic leakage in this cohort was 14% (32 children). Through univariate analysis of lymphatic leakage group and non-lymphatic leakage group, we found that lymphatic leakage increased the complications, prolonged the time of abdominal drainage and hospitalization, and delayed postoperative chemotherapy (p < 0.05). In this cohort, the median follow-up time was 46 (95% CI: 44-48) months. The follow-up data of 7 children were partially missing. 147 children survived, of which 23 had tumor recurrence (5 children recurred in the surgical area). 37 children died, of which 32 had tumor recurrence (9 children recurred in the operation area). In univariate analysis, there was no statistical difference in overall survival (p = 0.21) and event-free survival (p = 0.057) between lymphatic leakage group and non-lymphatic leakage group, while 3-year cumulative incidence of local progression was higher in lymphatic leakage group (p = 0.015). However, through multivariate analysis, we found that lymphatic leakage did not affect event-free survival, overall survival and cumulative incidence of local progression in children with neuroblastoma. Resection of 5 or more lymphatic regions was an independent risk factor for lymphatic leakage after neuroblastoma surgery. All 32 children with lymphatic leakage were cured by conservative treatment without surgery. Of these, 75% (24/32) children were cured by fat-free diet or observation, 25% (8/32) children were cured by total parenteral nutrition. The median drain output at diagnosis in total parenteral nutrition group was higher than that in non-total parenteral nutrition group (p < 0.001). The cut-off value was 17.2 ml/kg/day. CONCLUSIONS: Lymphatic leakage does not affect the prognosis of children with neuroblastoma, but long-term drain output caused by lymphatic leakage will still adversely affect postoperative complications and follow-up treatment, which requires attention and active treatment measures. More attention should be paid to the children with 5 or more lymphatic regions resection, and the injured lymphatic vessels should be actively found and ligated after tumor resection to reduce the postoperative lymphatic leakage. Early application of total parenteral nutrition is recommended for those who have drain output at diagnosis of greater than 17.2 ml/kg/day. LEVEL OF EVIDENCE: Level III, Treatment study (Retrospective comparative study).

Exploring new frontiers: a rare case of catheter ablation for persistent atrial fibrillation in a patient with cor triatriatum sinister guided by intracardiac echocardiography.

BACKGROUND: Cor triatriatum sinister (CTS) is an uncommon congenital cardiac anomaly. Atrial fibrillation (AF) is commonly the initial symptom in patients with CTS, occurring in approximately 32% of the cases. The complexity of performing AF catheter ablation, particularly in cases with persistent AF, increases in patients with CTS due to its unique structural challenges. CASE PRESENTATION: We report the treatment course of a 60-year-old male patient diagnosed with CTS, who underwent catheter ablation of drug-refractory, persistent AF. The complex anatomical structure of the condition made catheter ablation of AF challenging. To navigate these challenges, we performed comprehensive assessments using transthoracic echocardiography and transesophageal echocardiography, along with cardiac computed tomography angiography, prior to treatment initiation. The intricate anatomy of CTS was further clarified during the procedure via intracardiac echocardiography (ICE). Additionally, the complexity of catheter manipulation was further reduced with the aid of the VIZIGO sheath and the vein of Marshall ethanol infusion to achieve effective mitral isthmus blockage, thereby circumventing the impact of the CTS membrane. CONCLUSIONS: This case underscores the complexity and potential of advanced ablation techniques in managing cardiac arrhythmias associated with unusual cardiac anatomies. During the procedure, ICE facilitated detailed modeling of the left atrium, including the membranous structure and its openings, thus providing a clearer understanding of CTS. It is noteworthy that the membrane within the CTS may serve as a potential substrate for arrhythmias, which warrants further validation through larger sample studies.

Deep learning modeling using mammography images for predicting estrogen receptor status in breast cancer.

BACKGROUND: The estrogen receptor (ER) serves as a pivotal indicator for assessing endocrine therapy efficacy and breast cancer prognosis. Invasive biopsy is a conventional approach for appraising ER expression levels, but it bears disadvantages due to tumor heterogeneity. To address the issue, a deep learning model leveraging mammography images was developed in this study for accurate evaluation of ER status in patients with breast cancer. OBJECTIVES: To predict the ER status in breast cancer patients with a newly developed deep learning model leveraging mammography images. MATERIALS AND METHODS: Datasets comprising preoperative mammography images, ER expression levels, and clinical data spanning from October 2016 to October 2021 were retrospectively collected from 358 patients diagnosed with invasive ductal carcinoma. Following collection, these datasets were divided into a training dataset (n = 257) and a testing dataset (n = 101). Subsequently, a deep learning prediction model, referred to as IP-SE-DResNet model, was developed utilizing two deep residual networks along with the Squeeze-and-Excitation attention mechanism. This model was tailored to forecast the ER status in breast cancer patients utilizing mammography images from both craniocaudal view and mediolateral oblique view. Performance measurements including prediction accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curves (AUCs) were employed to assess the effectiveness of the model. RESULTS: In the training dataset, the AUCs for the IP-SE-DResNet model utilizing mammography images from the craniocaudal view, mediolateral oblique view, and the combined images from both views, were 0.849 (95% CIs: 0.809-0.868), 0.858 (95% CIs: 0.813-0.872), and 0.895 (95% CIs: 0.866-0.913), respectively. Correspondingly, the AUCs for these three image categories in the testing dataset were 0.835 (95% CIs: 0.790-0.887), 0.746 (95% CIs: 0.793-0.889), and 0.886 (95% CIs: 0.809-0.934), respectively. A comprehensive comparison between performance measurements underscored a substantial enhancement achieved by the proposed IP-SE-DResNet model in contrast to a traditional radiomics model employing the naive Bayesian classifier. For the latter, the AUCs stood at only 0.614 (95% CIs: 0.594-0.638) in the training dataset and 0.613 (95% CIs: 0.587-0.654) in the testing dataset, both utilizing a combination of mammography images from the craniocaudal and mediolateral oblique views. CONCLUSIONS: The proposed IP-SE-DResNet model presents a potent and non-invasive approach for predicting ER status in breast cancer patients, potentially enhancing the efficiency and diagnostic precision of radiologists.