Deep Learning Algorithms for Breast Cancer Detection in a UK Screening Cohort: As Stand-alone Readers and Combined with Human Readers.

Background Deep learning (DL) algorithms have shown promising results in mammographic screening either compared to a single reader or, when deployed in conjunction with a human reader, compared with double reading. Purpose To externally validate the performance of three DL algorithms as mammographic screen readers in an independent UK data set. Materials and Methods Three commercial DL algorithms (DL-1, DL-2, and DL-3) were retrospectively investigated from January 2022 to June 2022 using consecutive full-field digital mammograms collected at two UK sites during 1 year (2017).

Mammography Breast Cancer Screening Triage Using Deep Learning: A UK Retrospective Study.

Background Breast screening enables early detection of cancers; however, most women have normal mammograms, resulting in repetitive and resource-intensive reading tasks. Purpose To investigate if deep learning (DL) algorithms can be used to triage mammograms by identifying normal results to reduce workload or flag cancers that may be overlooked. Materials and Methods In this retrospective study, three commercial DL algorithms were investigated using consecutive mammograms from two UK Breast Screening Program sites from January 2015 to December 2017 and January 2017 to December 2018 on devices from two mammography vendors.

An investigation into the effects of temporal resolution on hepatic dynamic contrast-enhanced MRI in volunteers and in patients with hepatocellular carcinoma.

This study investigated the effect of temporal resolution on the dual-input pharmacokinetic (PK) modelling of dynamic contrast-enhanced MRI (DCE-MRI) data from normal volunteer livers and from patients with hepatocellular carcinoma. Eleven volunteers and five patients were examined at 3 T. Two sections, one optimized for the vascular input functions (VIF) and one for the tissue, were imaged within a single heart-beat (HB) using a saturation-recovery fast gradient echo sequence.

Constrained surface controllers for three-dimensional image data reformatting.

This study did not require ethical approval in the United Kingdom. The aim of this work was to create two controllers for navigating a two-dimensional image plane through a volumetric data set, providing two important features of the ultrasonographic paradigm: orientation matching of the navigation device and the desired image plane in the three-dimensional (3D) data and a constraining surface to provide a nonvisual reference for the image plane location in the 3D data. The first constrained surface controller (CSC) uses a planar constraining surface, while the second CSC uses a hemispheric constraining surface.

Slice offset frequency and shim adjustment for interactive steady-state free-precession (SSFP) imaging.

Purpose: To devise a method allowing real-time optimization of center frequency (CF) and shim for an interactive steady-state free-precession (SSFP) sequence by reformatting a previously acquired field map in the same orientation as the interactive acquisition.

Materials And Methods: Field maps were acquired in a rectangular parallel-piped phantom and a normal volunteer. An SSFP sequence was modified to communicate the current slice offset and rotation to an external program that reformatted the field map into the same plane, calculated the CF and shim offsets, and passed them back to the sequence.

MR-guided direct arthrography of the hip.

Purpose: To develop an MR-guided technique for direct magnetic resonance arthrography (DMRA) of the hip using a conventional 1.5 Tesla (T) MRI scanner.

Materials And Methods: Interactive versions of standard single-shot fast spin echo, coherent gradient echo, and fully balanced steady-state free precession sequences were developed, together with the ability to operate the scanner from within the magnet room.

Interactive magnetic resonance cholangiography (MRC) with adaptive averaging.

Purpose: To implement and evaluate a technique for adaptively averaging 2D magnetic resonance cholangiography (MRC) images obtained using an interactive imaging system with a view to improving image quality at reduced fields of view (FOVs).

Materials And Methods: Images were obtained using an interactive implementation of a single-shot half-Fourier rapid acquisition with relaxation enhancement (RARE) technique. Software was developed for adaptively averaging images, and an evaluation was performed in a phantom and a cohort of 10 patients referred for standard MRC.