MRI-Based Prediction of Clinical Improvement Following Ventricular Shunt Placement for Normal Pressure Hydrocephalus (NPH): Development and Evaluation of an Integrated Multi-Sequence Machine Learning Algorithm.

BACKGROUND AND PURPOSE: Symptoms of normal pressure hydrocephalus (NPH) are sometimes refractory to shunt placement, with limited ability to predict improvement for individual patients. We evaluated an MRI-based artificial intelligence method to predict post-shunt NPH symptom improvement. MATERIALS AND METHODS: NPH patients who underwent magnetic resonance imaging (MRI) prior to shunt placement at a single center (2014-2021) were identified. Twelve-month post-shunt improvement in modified Rankin Scale (mRS), incontinence, gait, and cognition were retrospectively abstracted from clinical documentation. 3D deep residual neural networks were built on skull stripped T2-weighted and fluid attenuated inversion recovery (FLAIR) images. Predictions based on both sequences were fused by additional network layers. Patients from 2014-2019 were used for parameter optimization, while those from 2020-2021 were used for testing. Models were validated on an external validation dataset from a second institution (n=33). RESULTS: Of 249 patients, n=201 and n=185 were included in the T2-based and FLAIR-based models according to imaging availability. The combination of T2-weighted and FLAIR sequences offered the best performance in mRS and gait improvement predictions relative to models trained on imaging acquired using only one sequence, with AUROC values of 0.7395 [0.5765-0.9024] for mRS and 0.8816 [0.8030-0.9602] for gait. For urinary incontinence and cognition, combined model performances on predicting outcomes were similar to FLAIR-only performance, with AUROC values of 0.7874 [0.6845-0.8903] and 0.7230 [0.5600-0.8859]. CONCLUSIONS: Application of a combined algorithm using both T2-weighted and FLAIR sequences offered the best image-based prediction of post-shunt symptom improvement, particularly for gait and overall function in terms of mRS. ABBREVIATIONS: NPH = normal pressure hydrocephalus; iNPH = idiopathic NPH; sNPH = secondary NPH; AI = artificial intelligence; ML = machine learning; CSF = cerebrospinal fluid; AUROC = area under the receiver operating characteristic; FLAIR = fluid attenuated inversion recovery; BMI = body mass index; CCI = Charlson Comorbidity Index; SD = standard deviation; IQR = interquartile range.

Eight new flavonoids from the fruits of Daemonorops draco.

Eight new flavonoids daemoflavans A-H, including two dimeric proanthocyanidins (1 and 2), four flavans (3-6), two 2-arylbenzofurans (7 and 8), along with nine known compounds (9-17), were isolated from the fruit of Daemonorops draco. Their structures, including the absolute configurations, were elucidated by extensive spectroscopic data, ECD analysis, and X-ray crystal diffraction. Besides, the X-ray crystal data of a known compound dracoflavan B1 (9) was firstly reported. Daemoflavan G (7) represents a rare example of C-5 methylated 2-arylbenzofuran in natural products. Among the known compounds, 15, 16, 17 were reported from this species for the first time. All the compounds were evaluated for their cytotoxicity against HepG2 cell line. Among them, compounds 1, 9 and 10 exhibited modest cytotoxic activity with IC50 values of 12.4, 12.0 and 13.2 µM, respectively.