Classification of brain arteriovenous malformations located in motor-related areas based on location and anterior choroidal artery feeding

Timing of diffusion tensor imaging in the management of a ruptured pediatric arteriovenous malformation: illustrative case

BACKGROUND

Diffusion tensor imaging (DTI) can characterize eloquent white matter tracts affected by brain arteriovenous malformations (AVMs). However, DTI interpretation can be difficult in ruptured cases due to the presence of blood products. The authors present the case of a ruptured pediatric AVM in the corticospinal tract (CST) and discuss how DTI at different time points informed the treatment.

OBSERVATIONS

A 9-year-old female presented with a sudden headache and left hemiparesis. She was found to have a Spetzler-Martin grade III, Supplementary grade I AVM in the right caudate and centrum semiovale, with obliteration and corresponding reduced fractional anisotropy (FA), fiber density (FD), and tract count (TC) of the adjacent CST on DTI. The patient remained stable and was scheduled for elective resection following a 6-week period to facilitate hematoma resorption. After 6 weeks, repeat DTI showed part of the nidus within intact CST fibers with concordant improvement in FA, FD, and TC. Considering the nidus location, CST integrity, and motor function recovery, surgery was deferred in favor of stereotactic radiosurgery.

LESSONS

In ruptured AVMs, DTI may initially create an incomplete picture and false assumptions about white matter tract integrity. DTI should be repeated if delayed treatment is appropriate to ensure informed decision-making and prevent avoidable permanent neurological deficits. https://thejns.org/doi/10.3171/CASE24225.

Enhancing the quality of evidence, comparability, and reproducibility in brain arteriovenous malformations treated with open surgery research: a systematic review and proposal of a reporting guideline for surgical and clinical outcomes

Brain Arteriovenous Malformations (bAVMs) are rare but high-risk developmental anomalies of the vascular system. Microsurgery through craniotomy is believed to be the mainstay standard treatment for many grades of bAVMs. However, a significant challenge emerges in the existing body of clinical studies on open surgery for bAVMs: the lack of reproducibility and comparability. This study aims to assess the quality of studies reporting clinical and surgical outcomes for bAVMs treated by open surgery and develop a reporting guideline checklist focusing on essential elements to ensure comparability and reproducibility. This is a systematic literature review that followed the PRISMA guidelines with the search in Medline, Embase, and Web of Science databases, for studies published between January 1, 2018, and December 1, 2023. Included studies were scrutinized focusing on seven domains: (1) Assessment of How Studies Reported on the Baseline Characteristics of the Patient Sample; (2) Assessment and reporting on bAVMs grading, anatomical characteristics, and radiological aspects; (3) Angioarchitecture Assessment and Reporting; (4) Reporting on Pivotal Concepts Definitions; (5) Reporting on Neurosurgeon(s) and Staff Characteristics; (6) Reporting on Surgical Details; (7) Assessing and Reporting Clinical and Surgical Outcomes and AEs. A total of 47 studies comprising 5,884 patients were included. The scrutiny of the studies identified that the current literature in bAVM open surgery is deficient in many aspects, ranging from fundamental pieces of information of methodology to baseline characteristics of included patients and data reporting. Included studies demonstrated a lack of reproducibility that hinders building cumulative evidence. A bAVM Open Surgery Reporting Guideline with 65 items distributed across eight domains was developed and is proposed in this study aiming to address these shortcomings. This systematic review identified that the available literature regarding microsurgery for bAVM treatment, particularly in studies reporting clinical and surgical outcomes, lacks rigorous scientific methodology and quality in reporting. The proposed bAVM Open Surgery Reporting Guideline covers all essential aspects and is a potential solution to address these shortcomings and increase transparency, comparability, and reproducibility in this scenario. This proposal aims to advance the level of evidence and enhance knowledge regarding the Open Surgery treatment for bAVMs.

Artificial Intelligence-Assisted Evaluation of the Spatial Relationship between Brain Arteriovenous Malformations and the Corticospinal Tract to Predict Postsurgical Motor Defects

BACKGROUND AND PURPOSE

Preoperative evaluation of brain AVMs is crucial for the selection of surgical candidates. Our goal was to use artificial intelligence to predict postsurgical motor defects in patients with brain AVMs involving motor-related areas.

MATERIALS AND METHODS

Eighty-three patients who underwent microsurgical resection of brain AVMs involving motor-related areas were retrospectively reviewed. Four artificial intelligence-based indicators were calculated with artificial intelligence on TOF-MRA and DTI, including FN5mm/50mm (the proportion of fiber numbers within 5-50mm from the lesion border), FN10mm/50mm (the same but within 10-50mm), FP5mm/50mm (the proportion of fiber voxel points within 5-50mm from the lesion border), and FP10mm/50mm (the same but within 10-50mm). The association between the variables and long-term postsurgical motor defects was analyzed using univariate and multivariate analyses. Least absolute shrinkage and selection operator regression with the Pearson correlation coefficient was used to select the optimal features to develop the machine learning model to predict postsurgical motor defects. The area under the curve was calculated to evaluate the predictive performance.

RESULTS

In patients with and without postsurgical motor defects, the mean FN5mm/50mm, FN10mm/50mm, FP5mm/50mm, and FP10mm/50mm were 0.24 (SD, 0.24) and 0.03 (SD, 0.06), 0.37 (SD, 0.27) and 0.06 (SD, 0.08), 0.06 (SD, 0.10) and 0.01 (SD, 0.02), and 0.10 (SD, 0.12) and 0.02 (SD, 0.05), respectively. Univariate and multivariate logistic analyses identified FN10mm/50mm as an independent risk factor for long-term postsurgical motor defects (P = .002). FN10mm/50mm achieved a mean area under the curve of 0.86 (SD, 0.08). The mean area under the curve of the machine learning model consisting of FN10mm/50mm, diffuseness, and the Spetzler-Martin score was 0.88 (SD, 0.07).

CONCLUSIONS

The artificial intelligence-based indicator, FN10mm/50mm, can reflect the lesion-fiber spatial relationship and act as a dominant predictor for postsurgical motor defects in patients with brain AVMs involving motor-related areas.