Clinical performance of a simulated abbreviated liver magnetic resonance imaging in combination with contrast-enhanced computed tomography for the baseline evaluation of the liver in patients with colorectal cancer.

Aim: To assess the diagnostic accuracy and inter-reader agreement of a simulated abbreviated gadoxetate liver magnetic resonance imaging (MRI) protocol together with contrast-enhanced computed tomography (CE-CT) against a standard gadoxetate MRI for the detection of colorectal liver metastases at baseline.

Materials And Methods: Three readers independently evaluated two sets of images per patient, recording number and location of metastases and benign lesions. Set 1 comprised T1w, T2w, DWI, multiphase CE-T1w, and hepatobiliary phase (HBP) images (standard).

Robotic MRI/CT Guided Multiregional 'smart' Biopsy for Characterization of Tumor Heterogeneity: A Prospective Development Study.

Rationale And Objectives: Intratumoral heterogeneity means single site tumor biopsy might not be representative. Here we develop and optimize an MRI-informed robotic multiregional 'smart' biopsy technique in retroperitoneal and pelvic sarcomas (RPS). We also explore the relationship between imaging and histological biomarkers.

Advanced imaging for earlier diagnosis and morbidity prevention in multiple myeloma: A British Society of Haematology and UK Myeloma Society Good Practice Paper.

This Good Practice Paper provides recommendations for the use of advanced imaging for earlier diagnosis and morbidity prevention in multiple myeloma. It describes how advanced imaging contributes to optimal healthcare resource utilisation by in newly diagnosed and relapsed myeloma, and provides a perspective on future directions of myeloma imaging, including machine learning assisted reporting.

Prospective evaluation of quantitative response parameter in patients with Gastrointestinal Stroma Tumor undergoing tyrosine kinase inhibitor therapy-Impact on clinical outcome.

The purpose of this study was to determine if dual-energy CT (DECT) vital iodine tumor burden (ViTB), a direct assessment of tumor vascularity, allows reliable response assessment in patients with GIST compared to established CT criteria such as RECIST1.1 and modified Choi (mChoi). From 03/2014 to 12/2019, 138 patients (64 years [32-94 years]) with biopsy proven GIST were entered in this prospective, multi-center trial.

Inter- and Intra-Patient Repeatability of Radiomic Features from Multiparametric Whole-Body MRI in Patients with Metastatic Prostate Cancer.

(1) Background: We assessed the test-re-test repeatability of radiomics in metastatic castration-resistant prostate cancer (mCPRC) bone disease on whole-body diffusion-weighted (DWI) and T1-weighted Dixon MRI. (2) Methods: In 10 mCRPC patients, 1.5 T MRI, including DWI and T1-weighted gradient-echo Dixon sequences, was performed twice on the same day.

A scan-specific quality control acquisition for clinical whole-body (WB) MRI protocols.

Image quality in whole-body MRI (WB-MRI) may be degraded by faulty radiofrequency (RF) coil elements or mispositioning of the coil arrays. Phantom-based quality control (QC) is used to identify broken RF coil elements but the frequency of these acquisitions is limited by scanner and staff availability. This work aimed to develop a scan-specific QC acquisition and processing pipeline to detect broken RF coil elements, which is sufficiently rapid to be added to the clinical WB-MRI protocol.

Deep Learning for Delineation of the Spinal Canal in Whole-Body Diffusion-Weighted Imaging: Normalising Inter- and Intra-Patient Intensity Signal in Multi-Centre Datasets.

Background: Whole-Body Diffusion-Weighted Imaging (WBDWI) is an established technique for staging and evaluating treatment response in patients with multiple myeloma (MM) and advanced prostate cancer (APC). However, WBDWI scans show inter- and intra-patient intensity signal variability. This variability poses challenges in accurately quantifying bone disease, tracking changes over follow-up scans, and developing automated tools for bone lesion delineation.

Curation of myeloma observational study MALIMAR using XNAT: solving the challenges posed by real-world data.

Objectives: MAchine Learning In MyelomA Response (MALIMAR) is an observational clinical study combining "real-world" and clinical trial data, both retrospective and prospective. Images were acquired on three MRI scanners over a 10-year window at two institutions, leading to a need for extensive curation.

Methods: Curation involved image aggregation, pseudonymisation, allocation between project phases, data cleaning, upload to an XNAT repository visible from multiple sites, annotation, incorporation of machine learning research outputs and quality assurance using programmatic methods.

Deep Learning Framework with Multi-Head Dilated Encoders for Enhanced Segmentation of Cervical Cancer on Multiparametric Magnetic Resonance Imaging.

T-weighted magnetic resonance imaging (MRI) and diffusion-weighted imaging (DWI) are essential components of cervical cancer diagnosis. However, combining these channels for the training of deep learning models is challenging due to image misalignment. Here, we propose a novel multi-head framework that uses dilated convolutions and shared residual connections for the separate encoding of multiparametric MRI images.

Image quality in whole-body MRI using the MY-RADS protocol in a prospective multi-centre multiple myeloma study.

Background: The Myeloma Response Assessment and Diagnosis System (MY-RADS) guidelines establish a standardised acquisition and analysis pipeline for whole-body MRI (WB-MRI) in patients with myeloma. This is the first study to assess image quality in a multi-centre prospective trial using MY-RADS.

Methods: The cohort consisted of 121 examinations acquired across ten sites with a range of prior WB-MRI experience, three scanner manufacturers and two field strengths.

Multimodal analysis and the oncology patient: Creating a hospital system for integrated diagnostics and discovery.

We propose that an information technology and computational framework that would unify access to hospital digital information silos, and enable integration of this information using machine learning methods, would bring a new paradigm to patient management and research. This is the core principle of Integrated Diagnostics (ID): . This has the potential to transform the practice of personalized oncology at a time at which it is very much needed.

Relative fat fraction of malignant bone lesions from breast cancer, prostate cancer and myeloma are significantly lower than normal bone marrow and shows excellent interobserver agreement.

Objectives: To compare relative fat fraction (rFF) of active bone lesions from breast, prostate and myeloma malignancies and normal bone marrow; to assess its inter-reader agreement.

Methods: Patients with breast ( = 26), myeloma ( = 32) and prostate cancer ( = 52) were retrospectively evaluated. 110 baseline rFF maps from whole-body MRI were reviewed by two radiologists.

Repeatability of quantitative individual lesion and total disease multiparametric whole-body MRI measurements in prostate cancer bone metastases.

Objectives: To assess the repeatability of quantitative multiparametric whole-body MRI (mpWB-MRI) parameters in advanced prostate cancer (APC) bone metastases.

Methods: 1.5T MRI was performed twice on the same day in 10 APC patients.

Pseudoprogression in patients with uterine leiomyosarcoma treated with first-line single-agent doxorubicin.

Aim: To evaluate the incidence of pseudoprogression in patients with metastatic or inoperable uterine leiomyosarcoma (LMS) treated with first-line single-agent doxorubicin.

Methods: The Royal Marsden NHS Foundation Trust Sarcoma Unit database was searched to identify all patients with metastatic or inoperable LMS treated with first-line doxorubicin from January 2006 to January 2022. Patients with available computed tomography scans performed at baseline and during doxorubicin therapy were included.

Development and Evaluation of Machine Learning in Whole-Body Magnetic Resonance Imaging for Detecting Metastases in Patients With Lung or Colon Cancer: A Diagnostic Test Accuracy Study.

Objectives: Whole-body magnetic resonance imaging (WB-MRI) has been demonstrated to be efficient and cost-effective for cancer staging. The study aim was to develop a machine learning (ML) algorithm to improve radiologists' sensitivity and specificity for metastasis detection and reduce reading times.

Materials And Methods: A retrospective analysis of 438 prospectively collected WB-MRI scans from multicenter Streamline studies (February 2013-September 2016) was undertaken.

Smartphone accessibility: understanding the lived experience of users with cervical spinal cord injuries.

Purpose: To explore accessibility challenges encountered by smartphone users with cervical spinal cord injuries (C1-C8). To investigate the suitability of current technology and make recommendations to help future technology meet user needs.

Methods: The study uses a mixed-method approach combining an inductive thematic analysis of nine semi-structured interviews with a quantitative analysis of thirty-nine questionnaires.

Late-Stage Metastatic Melanoma Emerges through a Diversity of Evolutionary Pathways.

Unlabelled: Understanding the evolutionary pathways to metastasis and resistance to immune-checkpoint inhibitors (ICI) in melanoma is critical for improving outcomes. Here, we present the most comprehensive intrapatient metastatic melanoma dataset assembled to date as part of the Posthumous Evaluation of Advanced Cancer Environment (PEACE) research autopsy program, including 222 exome sequencing, 493 panel-sequenced, 161 RNA sequencing, and 22 single-cell whole-genome sequencing samples from 14 ICI-treated patients. We observed frequent whole-genome doubling and widespread loss of heterozygosity, often involving antigen-presentation machinery.

Controversies in the management of patients with soft tissue sarcoma: Recommendations of the Conference on State of Science in Sarcoma 2022.

Background: Owing to the rarity and heterogeneity in biology and presentation, there are multiple areas in the diagnosis, treatment and follow-up of soft tissue sarcoma (STS), with no, low-level or conflicting evidence.

Methods: During the first Consensus Conference on the State of Science in Sarcoma (CSSS), we used a modified Delphi process to identify areas of controversy in the field of sarcoma, to name topics with limited evidence-based data in which a scientific and knowledge gap may remain and a consensus statement will help to guide patient management. We determined scientific questions which need to be addressed in the future in order to generate evidence and to inform physicians and caregivers in daily clinical practice in order to improve the outcomes of patients with sarcoma.

Oncologic outcomes of surgically managed primary pelvic soft tissue sarcoma; tumour biology or surgical constraints of the true pelvis?

Background: Pelvic soft tissue sarcomas are rare. Potentially curative resection remains challenging due to anatomical constraints of true pelvis and tumour spread through various anatomical hiatus. We sought to review the oncological outcomes of surgically managed cases at our centre and determine whether outcomes differ for patients with localised (limited to pelvis) versus extensive disease (with extra-pelvic extension).