Integrating Clinical Data and Radiomics and Deep Learning Features for End-to-End Delayed Cerebral Ischemia Prediction on Noncontrast CT.

Background And Purpose: Delayed cerebral ischemia is hard to diagnose early due to gradual, symptomless development. This study aimed to develop an automated model for predicting delayed cerebral ischemia following aneurysmal SAH on NCCT.

Materials And Methods: This retrospective study included 400 patients with aneurysmal SAH (156 with delayed cerebral ischemia) who underwent NCCT.

Atypical teratoid/rhabdoid tumor in adult: case series and an integrated survival analysis.

Background: Atypical teratoid/rhabdoid tumor (AT/RT) is well documented in children but less so in adults because of its rarity.

Method: We report a series of five cases, a literature review and quantitative analysis of the survival outcome of adult AT/RT patients.

Results: Seventy-four patients including our five cases (male: female = 16: 58) were evaluated, whose median age was 32.

Compared with conventional procedures, an intraoperative navigation system for ventriculoperitoneal shunting via the occipital horn improves outcomes in patients with hydrocephalus.

Background: Ventriculoperitoneal shunting (VPS) is a common neurosurgical procedure used to treat hydrocephalus. Although the use of a navigation system in VPS achieves superior results compared with conventional surgery, the relationships among clinical symptoms, ventricular catheter placement, catheter obstruction, and the postoperative Evans index have not been clearly reported.

Methods: We performed a retrospective study of 40 patients with VPS (the navigation surgery group) and 31 patients with VPS (the conventional surgery group).

Infantile Giant Intracranial Aneurysm Resection and In Situ Anastomosis.

Background: Infantile intracranial aneurysms (IAs) are extremely rare. IA clipping and embolization have been the most common treatment options. Infantile giant IAs treated by surgical resection and in situ anastomosis have rarely been reported.

A machine learning model to precisely immunohistochemically classify pituitary adenoma subtypes with radiomics based on preoperative magnetic resonance imaging.

Purpose: The type of pituitary adenoma (PA) cannot be clearly recognized with preoperative magnetic resonance imaging (MRI) but can be classified with immunohistochemical staining after surgery. In this study, a model to precisely immunohistochemically classify the PA subtypes by radiomic features based on preoperative MR images was developed.

Methods: Two hundred thirty-five pathologically diagnosed PAs, including t-box pituitary transcription factor (Tpit) family tumors (n = 55), pituitary transcription factor 1 (Pit-1) family tumors (n = 110), and steroidogenic factor 1 (SF-1) family tumors (n = 70), were retrospectively studied.

Case report: neonatal giant forehead hemangiopericytoma with a 5-year follow-up.

Rationale: Hemangiopericytoma (HPC) is a rare pediatric neoplasm with a high risk of bleeding, aggressive growth and high early relapse rates. Surgical excision remains the mainstream treatment, while the functions of chemotherapy and radiotherapy remain controversial. In particular, an infantile giant extracranial HPC located in the forehead has never been reported.