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).

Accuracy of an Artificial Intelligence System for Interval Breast Cancer Detection at Screening Mammography.

Background Artificial intelligence (AI) systems can be used to identify interval breast cancers, although the localizations are not always accurate. Purpose To evaluate AI localizations of interval cancers (ICs) on screening mammograms by IC category and histopathologic characteristics. Materials and Methods A screening mammography data set (median patient age, 57 years [IQR, 52-64 years]) that had been assessed by two human readers from January 2011 to December 2018 was retrospectively analyzed using a commercial AI system.

Breast density effect on the sensitivity of digital screening mammography in a UK cohort.

Objectives: To assess the performance of breast cancer screening by category of breast density and age in a UK screening cohort.

Methods: Raw full-field digital mammography data from a single site in the UK, forming a consecutive 3-year cohort of women aged 50 to 70 years from 2016 to 2018, were obtained retrospectively. Breast density was assessed using Volpara software.

High-resolution and highly accelerated MRI T2 mapping as a tool to characterise renal tumour subtypes and grades.

Background: Clinical imaging tools to probe aggressiveness of renal masses are lacking, and T2-weighted imaging as an integral part of magnetic resonance imaging protocol only provides qualitative information. We developed high-resolution and accelerated T2 mapping methods based on echo merging and using k-t undersampling and reduced flip angles (TEMPURA) and tested their potential to quantify differences between renal tumour subtypes and grades.

Methods: Twenty-four patients with treatment-naïve renal tumours were imaged: seven renal oncocytomas (RO); one eosinophilic/oncocytic renal cell carcinoma; two chromophobe RCCs (chRCC); three papillary RCCs (pRCC); and twelve clear cell RCCs (ccRCC).

Highly accelerated parameter mapping using model-based alternating reconstruction coupling fitting.

A model-based alternating reconstruction coupling fitting, termed Model-based Alternating Reconstruction COupling fitting (MARCO), is proposed for accurate and fast magnetic resonance parameter mapping.MARCO utilizes the signal model as a regularization by minimizing the bias between the image series and the signal produced by the suitable signal model based on iteratively updated parameter maps when reconstructing. The technique can incorporate prior knowledge of both image series and parameters by adding sparsity constraints.

MRI assessment of seminal vesicle involvement by prostate cancer using T2 signal intensity and volume.

Background: Seminal vesicle involvement (SVI) in patients with newly diagnosed prostate cancer is associated with high rates of treatment failure and tumor recurrence; correct identification of SVI allows for effective management decisions and surgical planning.

Methods: This single-center retrospective study analyzed MR images of the seminal vesicles from patients undergoing radical prostatectomy with confirmed T3b disease, comparing them to a control group without SVI matched for age and Gleason grade with a final stage of T2 or T3a. Seminal vesicles were segmented by an experienced uroradiologist, "raw" and bladder-normalized T2 signal intensity, as well as SV volume, were obtained.

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.

Improvements in Between-Vendor MRI Harmonization of Renal T Mapping using Stimulated Echo Compensation.

Background: T mapping is valuable to evaluate pathophysiology in kidney disease. However, variations in T relaxation time measurements across MR scanners and vendors may occur requiring additional correction.

Purpose: To harmonize renal T measurements between MR vendor platforms, and use an extended-phase-graph-based fitting method ("StimFit") to correct stimulated echoes and reduce between-vendor variations.

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.

A Phase II study of neoadjuvant axitinib for reducing the extent of venous tumour thrombus in clear cell renal cell cancer with venous invasion (NAXIVA).

Background: Surgery for renal cell carcinoma (RCC) with venous tumour thrombus (VTT) extension into the renal vein (RV) and/or inferior vena cava (IVC) has high peri-surgical morbidity/mortality. NAXIVA assessed the response of VTT to axitinib, a potent tyrosine kinase inhibitor.

Methods: NAXIVA was a single-arm, multi-centre, Phase 2 study.

Quantification and reduction of cross-vendor variation in multicenter DWI MR imaging: results of the Cancer Core Europe imaging task force.

Objectives: In the Cancer Core Europe Consortium (CCE), standardized biomarkers are required for therapy monitoring oncologic multicenter clinical trials. Multiparametric functional MRI and particularly diffusion-weighted MRI offer evident advantages for noninvasive characterization of tumor viability compared to CT and RECIST. A quantification of the inter- and intraindividual variation occurring in this setting using different hardware is missing.

Hyperpolarised C-MRI identifies the emergence of a glycolytic cell population within intermediate-risk human prostate cancer.

Hyperpolarised magnetic resonance imaging (HP C-MRI) is an emerging clinical technique to detect [1-C]lactate production in prostate cancer (PCa) following intravenous injection of hyperpolarised [1-C]pyruvate. Here we differentiate clinically significant PCa from indolent disease in a low/intermediate-risk population by correlating [1-C]lactate labelling on MRI with the percentage of Gleason pattern 4 (%GP4) disease. Using immunohistochemistry and spatial transcriptomics, we show that HP C-MRI predominantly measures metabolism in the epithelial compartment of the tumour, rather than the stroma.

Hyperpolarized C-Pyruvate Metabolism as a Surrogate for Tumor Grade and Poor Outcome in Renal Cell Carcinoma-A Proof of Principle Study.

Differentiating aggressive clear cell renal cell carcinoma (ccRCC) from indolent lesions is challenging using conventional imaging. This work prospectively compared the metabolic imaging phenotype of renal tumors using carbon-13 MRI following injection of hyperpolarized [1-C]pyruvate (HP-C-MRI) and validated these findings with histopathology. Nine patients with treatment-naïve renal tumors (6 ccRCCs, 1 liposarcoma, 1 pheochromocytoma, 1 oncocytoma) underwent pre-operative HP-C-MRI and conventional proton (H) MRI.

Multiparametric MRI for assessment of early response to neoadjuvant sunitinib in renal cell carcinoma.

Purpose: To detect early response to sunitinib treatment in metastatic clear cell renal cancer (mRCC) using multiparametric MRI.

Method: Participants with mRCC undergoing pre-surgical sunitinib therapy in the prospective NeoSun clinical trial (EudraCtNo: 2005-004502-82) were imaged before starting treatment, and after 12 days of sunitinib therapy using morphological MRI sequences, advanced diffusion-weighted imaging, measurements of R2* (related to hypoxia) and dynamic contrast-enhanced imaging. Following nephrectomy, participants continued treatment and were followed-up with contrast-enhanced CT.

Hyperpolarized Carbon-13 MRI for Early Response Assessment of Neoadjuvant Chemotherapy in Breast Cancer Patients.

Hyperpolarized C-MRI is an emerging tool for probing tissue metabolism by measuring C-label exchange between intravenously injected hyperpolarized [1-C]pyruvate and endogenous tissue lactate. Here, we demonstrate that hyperpolarized C-MRI can be used to detect early response to neoadjuvant therapy in breast cancer. Seven patients underwent multiparametric H-MRI and hyperpolarized C-MRI before and 7-11 days after commencing treatment.

Multiparametric MRI of early tumor response to immune checkpoint blockade in metastatic melanoma.

Background: Immune checkpoint inhibitors are now standard of care treatment for many cancers. Treatment failure in metastatic melanoma is often due to tumor heterogeneity, which is not easily captured by conventional CT or tumor biopsy. The aim of this prospective study was to investigate early microstructural and functional changes within melanoma metastases following immune checkpoint blockade using multiparametric MRI.

Dynamic biomarker and imaging changes from a phase II study of pre- and post-surgical sunitinib.

Objective: To explore translational biological and imaging biomarkers for sunitinib treatment before and after debulking nephrectomy in the NeoSun (European Union Drug Regulating Authorities Clinical Trials Database [EudraCT] number: 2005-004502-82) single-centre, single-arm, single-agent, Phase II trial.

Patients And Methods: Treatment-naïve patients with metastatic renal cell carcinoma (mRCC) received 50 mg once daily sunitinib for 12 days pre-surgically, then post-surgery on 4 week-on, 2 week-off, repeating 6-week cycles until disease progression in a single arm phase II trial. Structural and dynamic contrast-enhanced magnet resonance imaging (DCE-MRI) and research blood sampling were performed at baseline and after 12 days.

Federated learning for predicting clinical outcomes in patients with COVID-19.

Federated learning (FL) is a method used for training artificial intelligence models with data from multiple sources while maintaining data anonymity, thus removing many barriers to data sharing. Here we used data from 20 institutes across the globe to train a FL model, called EXAM (electronic medical record (EMR) chest X-ray AI model), that predicts the future oxygen requirements of symptomatic patients with COVID-19 using inputs of vital signs, laboratory data and chest X-rays. EXAM achieved an average area under the curve (AUC) >0.

Investigating the relationship between diffusion kurtosis tensor imaging (DKTI) and histology within the normal human brain.

Measurements of water diffusion with MRI have been used as a biomarker of tissue microstructure and heterogeneity. In this study, diffusion kurtosis tensor imaging (DKTI) of the brain was undertaken in 10 healthy volunteers at a clinical field strength of 3 T. Diffusion and kurtosis metrics were measured in regions-of-interest on the resulting maps and compared with quantitative analysis of normal post-mortem tissue histology from separate age-matched donors.

Highly accelerated subtractive femoral non-contrast-enhanced MRA using compressed sensing with k-space subtraction, phase and intensity correction.

Purpose: To develop an improved reconstruction method, k-space subtraction with phase and intensity correction (KSPIC), for highly accelerated, subtractive, non-contrast-enhanced MRA.

Methods: The KSPIC method is based on k-space subtraction of complex raw data. It applies a phase-correction procedure to restore the polarity of negative signals caused by subtraction and an intensity-correction procedure to improve background suppression and thereby sparsity.

MRI features of the normal prostatic peripheral zone: the relationship between age and signal heterogeneity on T2WI, DWI, and DCE sequences.

Objectives: To assess the multiparametric MRI (mpMRI) appearances of normal peripheral zone (PZ) across age groups in a biopsy-naïve population, where prostate cancer (PCa) was subsequently excluded, and propose a scoring system for background PZ changes.

Methods: This retrospective study included 175 consecutive biopsy-naïve patients (40-74 years) referred with a suspicion of PCa, but with subsequent negative investigations. Patients were grouped by age into categories ≤ 54, 55-59, 60-64, and ≥ 65 years.

Three-Dimensional Printed Molds for Image-Guided Surgical Biopsies: An Open Source Computational Platform.

Purpose: Spatial heterogeneity of tumors is a major challenge in precision oncology. The relationship between molecular and imaging heterogeneity is still poorly understood because it relies on the accurate coregistration of medical images and tissue biopsies. Tumor molds can guide the localization of biopsies, but their creation is time consuming, technologically challenging, and difficult to interface with routine clinical practice.