Self-supervised motion descriptor for cardiac phase detection in 4D CMR based on discrete vector field estimations

Cardiac magnetic resonance (CMR) sequences visualise the cardiac function voxel-wise over time. Simultaneously, deep learning-based deformable image registration is able to estimate discrete vector fields which warp one time step of a CMR sequence to the following in a self-supervised manner. However, despite the rich source of information included in these 3D+t vector fields, a standardised interpretation is challenging and the clinical applications remain limited so far. In this work, we show how to efficiently use a deformable vector field to describe the underlying dynamic process of a cardiac cycle in form of a derived 1D motion descriptor. Additionally, based on the expected cardiovascular physiological properties of a contracting or relaxing ventricle, we define a set of rules that enables the identification of five cardiovascular phases including the end-systole (ES) and end-diastole (ED) without the usage of labels. We evaluate the plausibility of the motion descriptor on two challenging multi-disease, -center, -scanner short-axis CMR datasets. First, by reporting quantitative measures such as the periodic frame difference for the extracted phases. Second, by comparing qualitatively the general pattern when we temporally resample and align the motion descriptors of all instances across both datasets. The average periodic frame difference for the ED, ES key phases of our approach is $0.80\pm{0.85}$, $0.69\pm{0.79}$ which is slightly better than the inter-observer variability ($1.07\pm{0.86}$, $0.91\pm{1.6}$) and the supervised baseline method ($1.18\pm{1.91}$, $1.21\pm{1.78}$). Code and labels will be made available on our GitHub repository. https://github.com/Cardio-AI/cmr-phase-detectionComment: accepted for the STACOM2022 workshop @ MICCAI202

Identification of Small Molecule Inhibitors of Tau Aggregation by Targeting Monomeric Tau As a Potential Therapeutic Approach for Tauopathies.

A potential strategy to alleviate the aggregation of intrinsically disordered proteins (IDPs) is to maintain the native functional state of the protein by small molecule binding. However, the targeting of the native state of IDPs by small molecules has been challenging due to their heterogeneous conformational ensembles. To tackle this challenge, we applied a high-throughput chemical microarray surface plasmon resonance imaging screen to detect the binding between small molecules and monomeric full-length Tau, a protein linked with the onset of a range of Tauopathies. The screen identified a novel set of drug-like fragment and lead-like compounds that bound to Tau. We verified that the majority of these hit compounds reduced the aggregation of different Tau constructs in vitro and in N2a cells. These results demonstrate that Tau is a viable receptor of drug-like small molecules. The drug discovery approach that we present can be applied to other IDPs linked to other misfolding diseases such as Alzheimer's and Parkinson's diseases.We thank the Wellcome Trust (UK), Medical Research Council (UK), Elan Pharmaceuticals (USA), the Canadian Institutes of Health Research (Canada) and the Alzheimer Society of Ontario (Canada), and Hungarian Brain Research Program (KTIA_NAP_13-2014-0009) for funding.This is the author accepted manuscript. The final version is available from Bentham Science via http://dx.doi.org/10.2174/15672050120915101910495

Study protocol: population screening for colorectal cancer by colonoscopy or CT colonography: a randomized controlled trial

<p>Abstract</p> <p>Background</p> <p>Colorectal cancer (CRC) is the second most prevalent type of cancer in Europe. Early detection and removal of CRC or its precursor lesions by population screening can reduce mortality. Colonoscopy and computed tomography colonography (CT colonography) are highly accurate exams and screening options that examine the entire colon. The success of screening depends on the participation rate. We designed a randomized trial to compare the uptake, yield and costs of direct colonoscopy population screening, using either a telephone consultation or a consultation at the outpatient clinic, versus CT colonography first, with colonoscopy in CT colonography positives.</p> <p>Methods and design</p> <p>7,500 persons between 50 and 75 years will be randomly selected from the electronic database of the municipal administration registration and will receive an invitation to participate in either CT colonography (2,500 persons) or colonoscopy (5,000 persons) screening. Those invited for colonoscopy screening will be randomized to a prior consultation either by telephone or a visit at the outpatient clinic. All CT colonography invitees will have a prior consultation by telephone. Invitees are instructed to consult their general practitioner and not to participate in screening if they have symptoms suggestive for CRC. After providing informed consent, participants will be scheduled for the screening procedure. The primary outcome measure of this study is the participation rate. Secondary outcomes are the diagnostic yield, the expected and perceived burden of the screening test, level of informed choice and cost-effectiveness of both screening methods.</p> <p>Discussion</p> <p>This study will provide further evidence to enable decision making in population screening for colorectal cancer.</p> <p>Trial registration</p> <p>Dutch trial register: NTR1829</p

Opportunistic Detection of Type 2 Diabetes Using Deep Learning From Frontal Chest Radiographs

Deep learning (DL) models can harness electronic health records (EHRs) to predict diseases and extract radiologic findings for diagnosis. With ambulatory chest radiographs (CXRs) frequently ordered, we investigated detecting type 2 diabetes (T2D) by combining radiographic and EHR data using a DL model. Our model, developed from 271,065 CXRs and 160,244 patients, was tested on a prospective dataset of 9,943 CXRs. Here we show the model effectively detected T2D with a ROC AUC of 0.84 and a 16% prevalence. The algorithm flagged 1,381 cases (14%) as suspicious for T2D. External validation at a distinct institution yielded a ROC AUC of 0.77, with 5% of patients subsequently diagnosed with T2D. Explainable AI techniques revealed correlations between specific adiposity measures and high predictivity, suggesting CXRs\u27 potential for enhanced T2D screening

Mucinous rectal cancer: concepts and imaging challenges

Rectal adenocarcinoma with mucinous components is an uncommon type of rectal cancer with two distinct histologic subtypes: mucinous adenocarcinoma and signet-ring cell carcinoma. Mucin can also be identified as pattern of response after neoadjuvant treatment. On imaging modalities, mucin typically demonstrates high signal intensity on T2-weighted images, low attenuation on computed tomography, and may be negative on 18-fluorodeoxyglucose positron emission tomography. After neoadjuvant CRT, cellular and acellular mucin share similar imaging features, and differentiating them is currently the main challenge faced by radiologists. Radiologists should be aware of pros, cons, and limitations of each imaging modality in the primary staging and restaging to avoid misinterpretation of the radiological findings