Citations

Abstract Objectives. To improve quality of coronary CT angiography (CCTA) images using a generalizable motion-correction algorithm. Approach . A neural network with attention gate and spatial transformer (ATOM) was developed to correct coronary motion. Phantom and patient CCTA images (39 males, 32 females, age range 19–92, scan date 02/2020 to 10/2021) retrospectively collected from dual-source CT were used to create training, development, and testing sets corresponding to 140- and 75 ms temporal resolution, with 75 ms images as labels. To test generalizability, ATOM was deployed for locally adaptive motion-correction in both 140- and 75 ms patient images. Objective metrics were used to assess motion-corrupted and corrected phantom and patient images, including structural-similarity-index (SSIM), dice-similarity-coefficient (DSC), peak-signal-noise-ratio (PSNR), and normalized root-mean-square-error (NRMSE). In objective quality assessment, ATOM was compared with several baseline networks, including U-net, U-net plus attention gate, U-net plus spatial transformer, VDSR, and ResNet. Two cardiac radiologists independently interpreted motion-corrupted and -corrected images at 75 and 140 ms in a blinded fashion and ranked diagnostic image quality (worst to best: 1–4, no ties). Main results . ATOM improved quality metrics ( p < 0.05) before/after correction: in phantom, SSIM 0.87/0.95, DSC 0.85/0.93, PSNR 19.4/22.5, NRMSE 0.38/0.27; in patient images, SSIM 0.82/0.88, DSC 0.88/0.90, PSNR 30.0/32.0, NRMSE 0.16/0.12. ATOM provided more consistent improvement of objective image quality, compared to the presented baseline networks. The motion-corrected images received better ranks than un-corrected at the same temporal resolution ( p < 0.05): 140 ms images 1.65/2.25, and 75 ms images 3.1/3.2. The motion-corrected 75 ms images received the best rank in 65% of testing cases. A fair-to-good inter-reader agreement was observed (Kappa score 0.58). Significance . ATOM reduces motion artifacts, improving visualization of coronary arteries. This algorithm can be used to virtually improve temporal resolution in both single- and dual-source CT.

Summary: EEG source imaging is an established technique for identifying the origin of interictal and ictal epileptiform discharges in patients with epilepsy, and it is an important tool in neurophysiology research. Accurate and reliable EEG source imaging requires appropriate choices of how the head, skull, and scalp are modeled, and understanding of the different approaches to modeling is important to guide these choices. Similarly, numerous different approaches to modeling the electrical sources within the brain exist, and appropriate understanding of the strengths and limitations of each are essential to obtaining accurate, reliable, and interpretable solutions. This review aims to describe the essential theoretical basis for these head and source models while also discussing the practical implications of each in clinical or research applications.

Abstract Loss of facial recognition or prosopagnosia has been well-recognized for over a century. It has been categorized as developmental or acquired depending on whether the onset is in early childhood or beyond, and acquired cases can have degenerative or non-degenerative aetiologies. Prosopagnosia has been linked to involvement of the fusiform gyri, mainly in the right hemisphere. The literature on prosopagnosia comprises case reports and small case series. We aim to assess demographic, clinical and imaging characteristics and neurological and neuropathological disorders associated with a diagnosis of prosopagnosia in a large cohort. Patients were categorized as developmental versus acquired; those with acquired prosopagnosia were further subdivided into degenerative versus non-degenerative, based on neurological aetiology. We assessed regional involvement on [18F] fluorodeoxyglucose-PET and MRI of the right and left frontal, temporal, parietal and occipital lobes. The Intake and Referral Center at the Mayo Clinic identified 487 patients with possible prosopagnosia, of which 336 met study criteria for probable or definite prosopagnosia. Ten patients, 80.0% male, had developmental prosopagnosia including one with Niemann–Pick type C and another with a forkhead box G1 gene mutation. Of the 326 with acquired prosopagnosia, 235 (72.1%) were categorized as degenerative, 91 (27.9%) as non-degenerative. The most common degenerative diagnoses were posterior cortical atrophy, primary prosopagnosia syndrome, Alzheimer’s disease dementia and semantic dementia, with each diagnosis accounting for &gt;10% of this group. The most common non-degenerative diagnoses were infarcts (ischaemic and haemorrhagic), epilepsy-related and primary brain tumours, each accounting for &gt;10%. We identified a group of patients with non-degenerative transient prosopagnosia in which facial recognition loss improved or resolved over time. These patients had migraine-related prosopagnosia, posterior reversible encephalopathy syndrome, delirium, hypoxic encephalopathy and ischaemic infarcts. On [18F] fluorodeoxyglucose-PET, the temporal lobes proved to be the most frequently affected regions in 117 patients with degenerative prosopagnosia, while in 82 patients with non-degenerative prosopagnosia, MRI revealed the right temporal and right occipital lobes as most affected by a focal lesion. The most common pathological findings in those with degenerative prosopagnosia were frontotemporal lobar degeneration with hippocampal sclerosis and mixed Alzheimer’s and Lewy body disease pathology. In this large case series of patients diagnosed with prosopagnosia, we observed that facial recognition loss occurs across a wide range of acquired degenerative and non-degenerative neurological disorders, most commonly in males with developmental prosopagnosia. The right temporal and occipital lobes, and connecting fusiform gyrus, are key areas. Multiple different pathologies cause degenerative prosopagnosia.

Abstract Background: Clinical, molecular, and genetic epidemiology studies displayed remarkable differences between ever- and never-smoking lung cancer. Methods: We conducted a stratified multi-population (European, East Asian, and African descent) association study on 44,823 ever-smokers and 20,074 never-smokers to identify novel variants that were missed in the non-stratified analysis. Functional analysis including expression quantitative trait loci (eQTL) colocalization and DNA damage assays, and annotation studies were conducted to evaluate the functional roles of the variants. We further evaluated the impact of smoking quantity on lung cancer risk for the variants associated with ever-smoking lung cancer. Results: Five novel independent loci, GABRA4, intergenic region 12q24.33, LRRC4C, LINC01088, and LCNL1 were identified with the association at two or three populations (P &lt; 5 × 10−8). Further functional analysis provided multiple lines of evidence suggesting the variants affect lung cancer risk through excessive DNA damage (GABRA4) or cis-regulation of gene expression (LCNL1). The risk of variants from 12 independent regions, including the well-known CHRNA5, associated with ever-smoking lung cancer was evaluated for never-smokers, light-smokers (packyear ≤ 20), and moderate-to-heavy-smokers (packyear &gt; 20). Different risk patterns were observed for the variants among the different groups by smoking behavior. Conclusions: We identified novel variants associated with lung cancer in only ever- or never-smoking groups that were missed by prior main-effect association studies. Impact: Our study highlights the genetic heterogeneity between ever- and never-smoking lung cancer and provides etiologic insights into the complicated genetic architecture of this deadly cancer.

Anti-CD20 monoclonal antibodies (mAbs) have revolutionized the treatment of lymphomas by improving the survival of patients, particularly in conjunction with chemotherapy. Until recently, the gold standard was based on the utilization of Rituximab (RTX) combined with chemotherapy. With our better understanding of monoclonal antibody (mAb) engineering, anti-CD20 mAb therapy has evolved to enhance clinical outcomes by improving pharmacokinetics, safety, activity and immunogenicity. Efforts to improve the on-targeting CD20 expressed on lymphomas through novel bioengineering techniques have led to the development of newer anti-CD20 mAbs that have accentuated complement-dependent cytotoxicity (CDC), antibody-dependent cell medicated cytotoxicity (ADCC), and/or a direct killing effect. There are several anti-CD20 monoclonal antibodies that have been evaluated for the treatment of lymphomas, some of which are now approved in addition to RTX.

Background and Objectives: Total knee arthroplasty (TKA) has become the treatment of choice for advanced osteoarthritis. The aim of this paper was to show the possibilities of optimizing the Perth CT protocol, which is highly effective for preoperative planning and postoperative assessment of alignment. Materials and Methods: The cross-sectional study comprised 16 patients for preoperative planning or postoperative evaluation of TKA. All patients were examined with the standard and optimized Perth CT protocol using advance techniques, including automatic exposure control (AEC), iterative image reconstruction (IR), as well as a single-energy projection-based metal artifact reduction algorithm for eliminating prosthesis artifacts. The effective radiation dose (E) was determined based on the dose report. Imaging quality is determined according to subjective and objective (values of signal to noise ratio (SdNR) and figure of merit (FOM)) criteria. Results: The effective radiation dose with the optimized protocol was significantly lower compared to the standard protocol (p < 0.001), while in patients with the knee prosthesis, E increased significantly less with the optimized protocol compared to the standard protocol. No significant difference was observed in the subjective evaluation of image quality between protocols (p > 0.05). Analyzing the objective criteria for image quality optimized protocols resulted in lower SdNR values and higher FOM values. No significant difference of image quality was determined using the SdNR and FOM as per the specified protocols and parts of extremities, and for the presence of prothesis. Conclusions: Retrospecting the ALARA (‘As Low As Reasonably Achievable’) principles, it is possible to optimize the Perth CT protocol by reducing the kV and mAs values and by changing the collimation and increasing the pitch factor. Advanced IR techniques were used in both protocols, and AEC was used in the optimized protocol. The effective dose of radiation can be reduced five times, and the image quality will be satisfactory.

Objectives: The performed hand-held echocardiography (HHE) was evaluated and interpreted by trained advanced practice providers (APPs) on hospitalized CHF patients for image quality and interpretation by comparing with expert echocardiographer and SE findings. Background: Congestive heart failure (CHF) is associated with increased hospital admissions and mortality. While a standard echocardiogram (SE) is the gold standard for cardiac assessment, it is not readily available. Hospitalized CHF patients require rapid assessment for expedited treatment. Methods: Over 6 months, five trained APPs performed HHE on hospitalized CHF patients and interpreted: (a) left ventricular (LV) size, (b) LV ejection fraction (LVEF), and (c) right atrial pressure (RAP). The study echocardiographer reviewed and blindly interpreted the HHE images and compared them with APPs and SE findings. Kappa statistics determined the degree of agreement between APPs and the study echocardiographer’s interpretation of the HHE images and SE. Results: A total of 80 CHF patients (age 73 ± 14 years, 58% males; LVEF (by SE) 45 ± 19%; 36.3% body mass indexes ≥ 30 kg/m2) were enrolled. HHE interpretation by APPs had a good agreement for LVEF (kappa 0.79) with the study echocardiographer and SE (kappa 0.74) and a good agreement for RAP (kappa 0.67) with the study echocardiographer. The correlation between the absolute LVEF interpretation by the study echocardiographer on HHE and SE was r = 0.88 (p < 0.0001). Conclusions: Trained APPs obtained diagnostic-quality HHE images and interpreted the LV function and RAP in CHF patients in good agreement with the study echocardiographer. LVEF by HHE correlated with LVEF by SE. Our study suggests trained APPs can use HHE to evaluate LVEF and RAP in CHF patients, leading to expedited and optimized treatment.