Background: Promptable foundation auto-segmentation models like Segment Anything (SA, Meta AI, New York, USA) represent a novel class of universal deep learning auto-segmentation models that could be employed for interactive tumor auto-contouring in RT treatment planning. Methods: Segment Anything was evaluated in an interactive point-to-mask auto-segmentation task for glioma brain tumor auto-contouring in 16,744 transverse slices from 369 MRI datasets (BraTS 2020 dataset). Up to nine interactive point prompts were automatically placed per slice. Tumor boundaries were auto-segmented on contrast-enhanced T1w sequences. Out of the three auto-contours predicted by SA, accuracy was evaluated for the contour with the highest calculated IoU (Intersection over Union, “oracle mask,” simulating interactive model use with selection of the best tumor contour) and for the tumor contour with the highest model confidence (“suggested mask”). Results: Mean best IoU (mbIoU) using the best predicted tumor contour (oracle mask) in full MRI slices was 0.762 (IQR 0.713–0.917). The best 2D mask was achieved after a mean of 6.6 interactive point prompts (IQR 5–9). Segmentation accuracy was significantly better for high- compared to low-grade glioma cases (mbIoU 0.789 vs. 0.668). Accuracy was worse using the suggested mask (0.572). Stacking best tumor segmentations from transverse MRI slices, mean 3D Dice score for tumor auto-contouring was 0.872, which was improved to 0.919 by combining axial, sagittal, and coronal contours. Conclusion: The Segment Anything foundation segmentation model can achieve high accuracy for glioma brain tumor segmentation in MRI datasets. The results suggest that foundation segmentation models could facilitate RT treatment planning when properly integrated in a clinical application.

The loss of the swallow-tail sign of the substantia nigra has been proposed for diagnosis of Parkinson’s disease. Aim was to evaluate, if the sign occurs consistently in healthy subjects and if it can be reliably detected with high-resolution 7T susceptibility weighted imaging (SWI). Thirteen healthy adults received SWI at 7T. 3 neuroradiologists, who were blinded to patients’ diagnosis, independently classified subjects regarding the swallow-tail sign to be present or absent. Accuracy, positive and negative predictive values (PPV and NPV) as well as inter- and intra-rater reliability and internal consistency were analyzed. The sign could be detected in 81% of the cases in consensus reading. Accuracy to detect the sign compared to the consensus was 100, 77 and 96% for the three readers with PPV reader 1/2/3 = 1/0.45/0.83 and NPV = 1/1/1. Inter-rater reliability was excellent (inter-class correlation coefficient = 0.844, alpha = 0.871). Intra-rater reliability was good to excellent (reader 1 R/L = 0.625/0.786; reader 2 = 0.7/0.64; reader 3 = 0.9/1). The swallow-tail sign can be reliably detected. However, our data suggest its occurrence is not consistent in healthy subjects. It may be possible that one reason is an individually variable molecular organization of nigrosome 1 so that it does not return a uniform signal in SWI.

There is evidence that glaucoma is a neurodegenerative disease involving the whole visual pathway. We prospectively examined potential benefits of volumetry of the lateral geniculate nucleus (LGN) and diffusion tensor imaging (DTI) using a new 7T scanner. 20 patients with normal tension glaucoma and 16 control individuals were examined. LGN volume and fractional anisotropy (FA) of the optic tract (OT) and the optic radiation (OR) and their correlation with RNFL (retinal nerve fiber layer) thickness were analyzed. LGN volume was significantly reduced in NTG (60.9 vs 88.3; p < 0.05). FA of the OT (right: 0.35 vs 0.66, left: 0.36 vs 0.67; p < 0.05) and of the OR (right: 0.41 vs 0.70, left: 0.41 vs 0.69; p < 0.05) was also significantly reduced. Nasal RNFL thickness correlated with the volume of the contralateral LGN (r = 0.471, p = 0.05). Temporal RNFL thickness correlated with the volume of the ipsilateral LGN (r = 0.603, p = 0.015). NTG leads to significant atrophy of the LGN compared to controls. FA of the optic tract and the optic radiation is reduced in NTG as sign of axonal degeneration. RNFL thickness but not FA correlates with LGN volume.

The objective of the current study was to optimize the postprocessing pipeline of 7 T chemical exchange saturation transfer (CEST) imaging for reproducibility and to prove this optimization for the detection of age differences and differences between patients with Parkinson's disease versus normal subjects. The following 7 T CEST MRI experiments were analyzed: repeated measurements of a healthy subject, subjects of two age cohorts (14 older, seven younger subjects), and measurements of 12 patients with Parkinson's disease. A slab‐selective, ‐homogeneous parallel transmit protocol was used. The postprocessing, consisting of motion correction, smoothing, ‐correction, normalization, denoising, ‐correction and Lorentzian fitting, was optimized regarding the intrasubject and intersubject coefficient of variation (CoV) of the amplitudes of the amide pool and the aliphatic relayed nuclear Overhauser effect (rNOE) pool within the brain. Seven “tricks” for postprocessing accomplished an improvement of the mean voxel CoV of the amide pool and the aliphatic rNOE pool amplitudes of less than 5% and 3%, respectively. These postprocessing steps are: motion correction with interpolation of the motion of low‐signal offsets (1) using the amide pool frequency offset image as reference (2), normalization of the Z‐spectrum using the outermost saturated measurements (3), correction of the Z‐spectrum with moderate spline smoothing (4), denoising using principal component analysis preserving the 11 highest intensity components (5), correction using a linear fit (6) and Lorentzian fitting using the five‐pool fit model (7). With the optimized postprocessing pipeline, a significant age effect in the amide pool can be detected. Additionally, for the first time, an aliphatic rNOE contrast between subjects with Parkinson's disease and age‐matched healthy controls in the substantia nigra is detected. We propose an optimized postprocessing pipeline for CEST multipool evaluation. It is shown that by the use of these seven “tricks”, the reproducibility and, thus, the statistical power of a CEST measurement, can be greatly improved and subtle changes can be detected.

Purpose: If routine diagnostics are inconclusive, neurologic deterioration and death of patients with brain cancer are attributed to tumor or therapy. Therefore, diagnosing symptoms of encephalopathy caused by human cytomegalovirus (HCMV) reactivation remains uncommon. We investigated the role of HCMV reactivation in neurologic decline and clinical outcome after the start of radiochemotherapy. Experimental Design: HCMV analyses and extended MRI studies including additional independent retrospective neuroradiologic evaluation were performed at predetermined intervals and in case of sudden neurologic decline for 118 adult patients: 63 histologically proven high-grade gliomas, 55 with brain metastases. Immunophenotyping from simultaneously taken whole-blood samples was carried out to detect immune cells serving as prognostic marker for HCMV-associated complications. Symptomatic viremia and overall survival (OS) were the endpoints. Results: Twenty-four percent (28/118) of all patients (12/44 glioblastoma, 3/13 anaplastic astrocytoma; 8/31 non–small cell lung cancer (NSCLC), 13/24 other brain metastases) developed HCMV-viremia during or within 4 weeks after radiotherapy; 21 of 28 patients experienced concurrent major neurologic decline, reversible by antiviral treatment. Identified by immunophenotyping, pretherapeutically low basophil counts predicted a high-risk for HCMV-associated encephalopathy (glioblastoma: P = 0.002, NSCLC: P = 0.02). Median OS was substantially reduced after HCMV-associated encephalopathy without MRI signs of tumor progression [glioblastoma: 99 vs. 570 days (calculated 1-year OS: 22% vs. 69%; P = 0.01) and NSCLC: 47 vs. 219 days (calculated 1-year OS: 0% vs. 32%; P = 0.02)]. Conclusions: For patients with brain cancer, HCMV reactivation after the start of radiochemotherapy is a frequent risk for cognitively detrimental but treatable encephalopathy and premature death. Routinely performed HCMV diagnostics, assessing basophil counts and study-based anti-viral regimens, are necessary to combat this hidden threat. See related commentary by Lawler et al., p. 3077

This study aimed to differentiate primary central nervous system lymphoma (PCNSL) and glioblastoma (GBM) via multimodal MRI featuring radiomic analysis. MRI data sets of patients with histological proven PCNSL and GBM were analyzed retrospectively. Diffusion-weighted imaging (DWI) and dynamic susceptibility contrast (DSC) perfusion imaging were evaluated to differentiate contrast enhancing intracerebral lesions. Selective (contrast enhanced tumor area with the highest mean cerebral blood volume (CBV) value) and unselective (contouring whole contrast enhanced lesion) Apparent diffusion coefficient (ADC) measurement was performed. By multivariate logistic regression, a multiparametric model was compiled and tested for its diagnostic strength. A total of 74 patients were included in our study. Selective and unselective mean and maximum ADC values, mean and maximum CBV and ratio_CBV as quotient of tumor CBV and CBV in contralateral healthy white matter were significantly larger in patients with GBM than PCNSL; minimum CBV was significantly lower in GBM than in PCNSL. The highest AUC for discrimination of PCNSL and GBM was obtained for selective mean and maximum ADC, mean and maximum CBV and ratio_CBV. By integrating these five in a multiparametric model 100% of the patients were classified correctly. The combination of perfusion imaging (CBV) and tumor hot-spot selective ADC measurement yields reliable radiological discrimination of PCNSL from GBM with highest accuracy and is readily available in clinical routine.