Fibroglandular Tissue Segmentation in Breast MRI using Vision Transformers -- A multi-institutional evaluation

Accurate and automatic segmentation of fibroglandular tissue in breast MRI screening is essential for the quantification of breast density and background parenchymal enhancement. In this retrospective study, we developed and evaluated a transformer-based neural network for breast segmentation (TraBS) in multi-institutional MRI data, and compared its performance to the well established convolutional neural network nnUNet. TraBS and nnUNet were trained and tested on 200 internal and 40 external breast MRI examinations using manual segmentations generated by experienced human readers. Segmentation performance was assessed in terms of the Dice score and the average symmetric surface distance. The Dice score for nnUNet was lower than for TraBS on the internal testset (0.909$\pm$0.069 versus 0.916$\pm$0.067, P<0.001) and on the external testset (0.824$\pm$0.144 versus 0.864$\pm$0.081, P=0.004). Moreover, the average symmetric surface distance was higher (=worse) for nnUNet than for TraBS on the internal (0.657$\pm$2.856 versus 0.548$\pm$2.195, P=0.001) and on the external testset (0.727$\pm$0.620 versus 0.584$\pm$0.413, P=0.03). Our study demonstrates that transformer-based networks improve the quality of fibroglandular tissue segmentation in breast MRI compared to convolutional-based models like nnUNet. These findings might help to enhance the accuracy of breast density and parenchymal enhancement quantification in breast MRI screening

The Promise and Pitfalls of Facebook Advertising: a Genetic Counselor’s Perspective

Facebook advertising is a powerful tool for increasing the outreach and recruitment of research participants. We describe our experience as genetic counselors within the context of an internet-based research study, recruiting subjects for a Parkinson disease (PD) biomarker study

Expression of Wnt gene family and frizzled receptors in head and neck squamous cell carcinomas

[Abstract] Genes of the Wnt and Frizzled class, expressed in HNSCC tissue and cell lines, have an established role in cell morphogenesis and differentiation, and also they have oncogenic properties. We studied Wnt and Fz genes as potential tumor-associated markers in HNSCC by qPCR. Expression levels of Wnt and Fz genes in 22 unique frozen samples from HNSCC were measured. We also assessed possible correlation between the expression levels obtained in cancer samples in relation to clinicopathologic outcome. Wnt-1 was not expressed in the majority of the HNSCC studied, whereas Wnt-5A was the most strongly expressed by the malignant tumors. Wnt-10B expression levels were related with higher grade of undifferentiation. Related to Fz genes, Fz-5 showed more expression levels in no-affectation of regional lymph nodes. Kaplan–Meier survival analyses suggest a reduced time of survival for low and high expression of Wnt-7A and Fz-5 mRNA, respectively. qPCR demonstrated that HNSCC express Wnt and Fz members, and suggested that Wnt and Fz signaling is activated in HNSCC cells

MRI-Based Quantitation of Hepatic Steatosis Does Not Predict Hypertrophy Rate after Portal Vein Embolization in Patients with Colorectal Liver Metastasis and Normal to Moderately Elevated Fat Fraction

The aim of this study was to correlate the pre-procedural magnetic-resonance-imaging-based hepatic fat fraction (hFF) with the degree of hypertrophy after portal vein embolization (PVE) in patients with colorectal cancer liver metastases (CRCLM). Between 2011 November and 2020 February, 68 patients with CRCLM underwent magnetic resonance imaging (MRI; 1.5 Tesla) of the liver before PVE. Using T1w chemical shift imaging (DUAL FFE), the patients were categorized as having a normal (&lt;5%) or an elevated (&gt;5%) hFF. The correlation of hFF, age, gender, initial tumor mass, history of chemotherapy, degree of liver hypertrophy, and kinetic growth rate after PVE was investigated using multiple regression analysis and Spearman’s test. A normal hFF was found in 43/68 patients (63%), whereas 25/68 (37%) patients had an elevated hFF. The mean hypertrophy and kinetic growth rates in patients with normal vs. elevated hFF were 24 ± 31% vs. 28 ± 36% and 9 ± 9 % vs. 8 ± 10% (p &gt; 0.05), respectively. Spearman’s test showed no correlation between hFF and the degree of hypertrophy (R = −0.04). Multivariable analysis showed no correlation between hFF, history of chemotherapy, age, baseline tumor burden, or laterality of primary colorectal cancer, and only a poor inverse correlation between age and kinetic growth rate after PVE. An elevated hFF in a pre-procedural MRI does not correlate with the hypertrophy rate after PVE and should therefore not be used as a contraindication to the procedure in patients with CRCLM