Staircase Lamellar Macular Hole in a Male Patient Aged 54 Years.

This case report discusses a diagnosis of X-linked Alport syndrome in a 54-year-old male patient who presented with a lamellar macular hole in his left eye.

Race and ethnic representation among clinical trials for diabetic retinopathy and diabetic macular edema within the United States: A review.

PURPOSE: Evaluate racial and ethnic representation in clinical trials compared to the disease burden for diabetic retinopathy (DR) and diabetic macular edema (DME) within the United States (US). Diabetic retinopathy (DR) is currently the leading cause of blindness in American adults, affecting over 7.7 million individuals and disproportionately affecting Black Americans. Black patients represent 38.3 ± 16.5% of DME within the US population while White patients represented 44.6 ± 18.3% of the DME population in the US. METHODS: All completed interventional clinical trials involving the conditions "Macular Edema" or "Diabetic Retinopathy" between 2001 and 2020. Excluded studies had fewer than 50 participants, terminated early, did not have published results, or involved locations outside the US. RESULTS: Twenty-five clinical trials were included in this review. In National Institute of Health (NIH) and industry-sponsored clinical trials for DME, the proportion of Black patients was 12.6 ± 3.3% (p < 0.05) and 8.6 ± 2.9% (p < 0.05), respectively. White patients' representation in NIH and industry-sponsored trials was significantly greater at 69.5 ± 4.4% (p < 0.05) and 80.0 ± 2.2% (p < 0.05), respectively. For DR trials, the proportion of Black patients in NIH and industry was 23.3 ± 11.7% and 11.2 ± 2.2%, respectively. CONCLUSIONS: Black patients are under-represented by a 3.0-fold disparity in NIH trials and 4.5-fold disparity in industry trials for DME, while White patients are overrepresented. In industry-funded DR trials, there is a 2.1-fold disparity compared to disease burden. Clinical trials for diabetic eye disease should aim to recruit patients based on the disease burden, which enables measurements of treatment outcomes by race and promotes health equity.

Comparing Deep Learning and Immunohistochemistry in Determining the Site of Origin for Well-Differentiated Neuroendocrine Tumors.

BACKGROUND: Determining the site of origin for metastatic well-differentiated neuroendocrine tumors (WDNETs) is challenging, and immunohistochemical (IHC) profiles do not always lead to a definitive diagnosis. We sought to determine if a deep-learning convolutional neural network (CNN) could improve upon established IHC profiles in predicting the site of origin in a cohort of WDNETs from the common primary sites. MATERIALS AND METHODS: Hematoxylin and eosin (H&E)-stained tissue microarrays (TMAs) were created using 215 WDNETs arising from the known primary sites. A CNN trained and tested on 60% (n = 130) and 40% (n = 85) of these cases, respectively. One hundred and seventy-nine cases had TMA tissue remaining for the IHC analysis. These cases were stained with IHC markers pPAX8, CDX2, SATB2, and thyroid transcription factor-1 (markers of pancreas/duodenum, ileum/jejunum/duodenum, colorectum/appendix, and lung WDNET sites of origin, respectively). The CNN diagnosis was deemed correct if it designated a majority or plurality of the tumor area as the known site of origin. The IHC diagnosis was deemed correct if the most specific marker for a particular site of origin met an H-score threshold determined by two pathologists. RESULTS: When all cases were considered, the CNN correctly identified the site of origin at a lower rate compared to IHC (72% vs. 82%, respectively). Of the 85 cases in the CNN test set, 66 had sufficient TMA material for IHC stains, thus 66 cases were available for a direct case-by-case comparison of IHC versus CNN. The CNN correctly identified 70% of these cases, while IHC correctly identified 76%, a finding that was not statistically significant (P = 0.56). CONCLUSION: A CNN can identify WDNET site of origin at an accuracy rate close to the current gold standard IHC methods.

Clinical evaluation of CAIPIRINHA: comparison against a GRAPPA standard.

PURPOSE: To evaluate image quality when using a CAIPIRINHA sampling pattern in comparison to a standard GRAPPA sampling pattern in patients undergoing a routine three-dimensional (3D) breathheld liver exam. CAIPIRINHA uses an optimized phase encoding sampling strategy to alter aliasing artifacts in 3D acquisitions to improve parallel imaging reconstruction. MATERIALS AND METHODS: Twenty patient volunteers were scanned using a 3D VIBE acquisition with an acceleration factor of four using a CAIPIRINHA and standard GRAPPA sampling pattern. CAIPIRINHA and GRAPPA images were evaluated by three radiologists in a two alternative forced choice test, and the Wilcoxon signed rank test was performed. RESULTS: The CAIPIRINHA sampling pattern was preferred in an average of 68% of the comparisons, and the Wilcoxon signed rank test showed a significant improvement in CAIPIRINHA images (P = 0.014). This analysis indicates that in the given sample set, CAIPIRINHA preference over the GRAPPA standard was statistically significant. CONCLUSION: This work shows that for an acceleration factor of four, a CAIPIRINHA accelerated VIBE acquisition provides significantly improved image quality in comparison to the current GRAPPA standard. This allows a further reduction in imaging time for similar spatial resolutions, which can reduce long breathhold requirements in abdominal imaging, and may be particularly helpful in patients who cannot provide requisite breathholds with current protocols.