During the diagnostic workup of lung adenocarcinomas (LAC), pathologists evaluate distinct histological tumor growth patterns. The percentage of each pattern on multiple slides bears prognostic significance. To assist with the quantification of growth patterns, we constructed a pipeline equipped with a convolutional neural network (CNN) and soft-voting as the decision function to recognize solid, micropapillary, acinar, and cribriform growth patterns, and non-tumor areas. Slides of primary LAC were obtained from Cedars-Sinai Medical Center (CSMC), the Military Institute of Medicine in Warsaw and the TCGA portal. Several CNN models trained with 19,924 image tiles extracted from 78 slides (MIMW and CSMC) were evaluated on 128 test slides from the three sites by F1-score and accuracy using manual tumor annotations by pathologist. The best CNN yielded F1-scores of 0.91 (solid), 0.76 (micropapillary), 0.74 (acinar), 0.6 (cribriform), and 0.96 (non-tumor) respectively. The overall accuracy of distinguishing the five tissue classes was 89.24%. Slide-based accuracy in the CSMC set (88.5%) was significantly better (p < 2.3E-4) than the accuracy in the MIMW (84.2%) and TCGA (84%) sets due to superior slide quality. Our model can work side-by-side with a pathologist to accurately quantify the percentages of growth patterns in tumors with mixed LAC patterns.

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Abnormally phosphorylated tau, an indicator of Alzheimer’s disease, begins to accumulate in the first decades of life in the locus coeruleus (LC), the primary source of cortical norepinephrine. Ensuing dysfunction in noradrenergic neuromodulation is hypothesized to contribute to Alzheimer’s progression. However, research into the role of the LC has been impeded by a lack of effective ways of assessing it in vivo. Advances in high-resolution brainstem magnetic resonance imaging (MRI) hold potential to investigate the association of locus coeruleus integrity and Alzheimer’s-related neuropathological markers in vivo.Leveraging a meta-analytical approach, we first synthesized LC localizations and dimensions across previously published studies to improve the reliability and validity of MR-based locus coeruleus detection. Next, we applied this refined volume of interest to determine whether MR-indexed LC integrity can serve as a marker for noradrenergic degeneration in early-onset Alzheimer’s disease. Eighteen participants (34.7±10.1 years; 9♀) with or known to be at-risk for mutations in genes associated with autosomal-dominant Alzheimer’s disease (ADAD) were investigated. Genotyping confirmed mutations in seven participants (PSEN1, n = 6; APP, n = 1), of which four were symptomatic. Participants underwent 3T-MRI, flortaucipir positron emission tomography (PET), and cognitive testing. LC MRI intensity, a non-invasive proxy for neuronal density, was semi-automatically extracted from high-resolution brainstem scans across the rostrocaudal extent of the nucleus.Relative to healthy controls, symptomatic participants showed lower LC intensity. This effect was pronounced in rostral segments of the nucleus that project to the mediotemporal lobe and other memory-relevant areas. Among carriers of ADAD-causing mutations, closer proximity to the mutation-specific median age of dementia diagnosis was associated with lower LC intensity. Leveraging a multivariate statistical approach, we revealed a pattern of LC-related tau pathology in occipito-temporo-parietal brain regions. Finally, higher locus intensity was closely linked to memory performance across a variety of neuropsychological tests.Our finding of diminished MR-indexed LC integrity in autosomal-dominant Alzheimer’s disease suggest a role of the noradrenergic system in this neurodegenerative disease.

The Grade of meningioma has significant implications for selecting treatment regimens ranging from observation to surgical resection with adjuvant radiation. For most patients, meningiomas are diagnosed radiologically, and Grade is not determined unless a surgical procedure is performed. The goal of this study is to train a novel auto-classification network to determine Grade I and II meningiomas using T1-contrast enhancing (T1-CE) and T2-Fluid attenuated inversion recovery (FLAIR) magnetic resonance (MR) images. Ninety-six consecutive treatment naïve patients with pre-operative T1-CE and T2-FLAIR MR images and subsequent pathologically diagnosed intracranial meningiomas were evaluated. Delineation of meningiomas was completed on both MR images. A novel asymmetric 3D convolutional neural network (CNN) architecture was constructed with two encoding paths based on T1-CE and T2-FLAIR. Each path used the same 3 × 3 × 3 kernel with different filters to weigh the spatial features of each sequence separately. Final model performance was assessed by tenfold cross-validation. Of the 96 patients, 55 (57%) were pathologically classified as Grade I and 41 (43%) as Grade II meningiomas. Optimization of our model led to a filter weighting of 18:2 between the T1-CE and T2-FLAIR MR image paths. 86 (90%) patients were classified correctly, and 10 (10%) were misclassified based on their pre-operative MRs with a model sensitivity of 0.85 and specificity of 0.93. Among the misclassified, 4 were Grade I, and 6 were Grade II. The model is robust to tumor locations and sizes. A novel asymmetric CNN with two differently weighted encoding paths was developed for successful automated meningioma grade classification. Our model outperforms CNN using a single path for single or multimodal MR-based classification.

We describe a patient with cerebral amyloid angiopathy-related inflammation (CAA-ri) presenting as Alzheimer disease (AD) with a mass lesion with symptom onset at age 59. He was found to have a nonenhancing lesion in the right temporal lobe on magnetic resonance imaging without evidence of hemorrhage. He underwent a biopsy which showed amyloid beta in blood vessel walls and a perivascular inflammatory infiltrate consistent with CAA-ri. Neurofibrillary tangles were present and a flortaucipir positron emission tomography showed bilateral signal highest in the lateral temporal and parietal cortices. A lumbar puncture showed tau, p-tau, and amyloid beta levels consistent with AD without evidence of inflammation. He was homozygous for the APOE ε4 allele. He died at age 67. A focus of CAA-ri can be present in the context of AD with a mass lesion and without evidence of hemorrhage, significant ischemic changes, or overt inflammation on cerebrospinal fluid examination.