Application of deep learning techniques for breath-hold, high-precision T2-weighted magnetic resonance imaging of the abdomen.

Purpose: To evaluate the feasibility of a high-precision single-shot fast spin-echo (SS-FSE) sequence using the deep learning-based Precise IQ Engine (PIQE) algorithm in comparison with standard SS-FSE for T2-weighted MR imaging of the abdomen, and to compare the image quality with a multi-shot (MS)-FSE sequence using the PIQE algorithm.

Methods: This retrospective study included 105 patients who underwent abdominal MR including T2-weighted sequences using the PIQE reconstruction algorithm. The image quality, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) in high-precision SS-FSE sequences using PIQE were compared to those in standard SS-FSE without PIQE and MS-FSE sequences using PIQE.

HPV 16-E6-mediated degradation of intrinsic p53 is compensated by upregulation of p53 gene expression in normal cervical keratinocytes.

In this study we investigated the relationship between the development of either HSILs (high-grade squamous intraepithelial lesions) or invasive cancers of the uterine cervix and the p53 codon 72 polymorphisms consisting of arginine (Arg)- or proline (Pro)-encoded allele in Japanese populations. Furthermore, we determined if intrinsic p53 is affected by the p53-degradation activities of human papillomavirus type 16 (HPV 16)-E6 in normal cervical keratinocytes with each p53 codon 72 genotype. Using PCR with p53 codon 72 polymorphic allele-specific primers, p53 genotypes of 112 normal cervical specimens and 88 cervical lesions including 44 HSILs and 44 invasive cancers were determined.