Standard Reconstruction Research Articles

Feasibility of Accelerated Prostate Diffusion-Weighted Imaging on 0.55 T MRI Enabled With Random Matrix Theory Denoising.

Prostate cancer diffusion weighted imaging (DWI) MRI is typically performed at high-field strength (3.0 T) in order to overcome low signal-to-noise ratio (SNR). In this study, we demonstrate the feasibility of prostate DWI at low field enabled by random matrix theory (RMT)-based denoising, relying on the MP-PCA algorithm applied during image reconstruction from multiple coils. Twenty-one volunteers and 2 prostate cancer patients were imaged with a 6-channel pelvic surface array coil and an 18-channel spine array on a prototype 0.55 T system created by ramping down a commercial magnetic resonance imaging system (1.5 T MAGNETOM Aera Siemens Healthcare) with 45 mT/m gradients and 200 T/m/s slew rate. Diffusion-weighted images were acquired with 4 non-collinear directions, for which b = 50 s/mm 2 was used with 8 averages and b = 1000 s/mm 2 with 40 averages; 2 extra b = 50 s/mm 2 were used as part of the dynamic field correction. Standard and RMT-based reconstructions were applied on DWI over different ranges of averages. Accuracy/precision was evaluated using the apparent diffusion coefficient (ADC), and image quality was evaluated over 5 separate reconstructions by 3 radiologists with a 5-point Likert scale. For the 2 patients, we compare image quality and lesion visibility of the RMT reconstruction versus the standard one on 0.55 T and on clinical 3.0 T. The RMT-based reconstruction in this study reduces the noise floor by a factor of 5.8, thereby alleviating the bias on prostate ADC. Moreover, the precision of the ADC in prostate tissue after RMT increases over a range of 30%-130%, with the increase in both signal-to-noise ratio and precision being more prominent for a low number of averages. Raters found that the images were consistently of moderate to good overall quality (3-4 on the Likert scale). Moreover, they determined that b = 1000 s/mm 2 images from a 1:55-minute scan with the RMT-based reconstruction were on par with the corresponding images from a 14:20-minute scan with standard reconstruction. Prostate cancer was visible on ADC and calculated b = 1500 images even with the abbreviated 1:55-minute scan reconstructed with RMT. Prostate imaging using DWI is feasible at low field and can be performed more rapidly with noninferior image quality compared with standard reconstruction.

Coronary artery calcium quantification: comparison between filtered-back projection, hybrid iterative reconstruction, and deep learning reconstruction techniques.

The reference protocol for the quantification of coronary artery calcium (CAC) should be updated to meet the standards of modern imaging techniques. To assess the influence of filtered-back projection (FBP), hybrid iterative reconstruction (IR), and three levels of deep learning reconstruction (DLR) on CAC quantification on both in vitro and in vivo studies. In vitro study was performed with a multipurpose anthropomorphic chest phantom and small pieces of bones. The real volume of each piece was measured using the water displacement method. In the in vivo study, 100 patients (84 men; mean age = 71.2 ± 8.7 years) underwent CAC scoring with a tube voltage of 120 kVp and image thickness of 3 mm. The image reconstruction was done with FBP, hybrid IR, and three levels of DLR including mild (DLRmild), standard (DLRstd), and strong (DLRstr). In the in vitro study, the calcium volume was equivalent (P = 0.949) among FBP, hybrid IR, DLRmild, DLRstd, and DLRstr. In the in vivo study, the image noise was significantly lower in images that used DLRstr-based reconstruction, when compared images other reconstructions (P < 0.001). There were no significant differences in the calcium volume (P = 0.987) and Agatston score (P = 0.991) among FBP, hybrid IR, DLRmild, DLRstd, and DLRstr. The highest overall agreement of Agatston scores was found in the DLR groups (98%) and hybrid IR (95%) when compared to standard FBP reconstruction. The DLRstr presented the lowest bias of agreement in the Agatston scores and is recommended for the accurate quantification of CAC.

Liver Transplantation After Hepatic Artery Infusion Pump Therapy: Single-Center Experience and Technical Considerations.

Hepatic artery infusion pump (HAIP) therapy has become increasingly commonplace in the treatment of intrahepatic tumors. When combined with standard chemotherapy, HAIP therapy demonstrates a higher response rate than chemotherapy alone. Biliary sclerosis is observed in up to 22 % of patients, for whom no treatment has been standardized. This report describes orthotopic liver transplantation (OLT) both as a treatment for HAIP-induced cholangiopathy and as a possible definitive oncologic treatment after HAIP-bridging therapy. A retrospective study reviewed patients who had undergone HAIP placement followed by OLT at the authors' institution. Patient demographics, neoadjuvant treatment, and postoperative outcomes were reviewed. Seven OLTs were performed for patients with prior HAIP placement. The majority were women (n = 6), and the median age was 61 years (range, 44.5-65.5 years). Transplantation was performed for five patients due to biliary complications secondary to HAIP and two patients because of residual tumor after HAIP therapy. All the OLTs had difficult dissections due to adhesions. Because of HAIP-induced damage, atypical arterial anastomoses were required in six patients (2 patients used a recipient common hepatic artery below the gastroduodenal artery takeoff; 2 patients used recipient splenic arterial inflow; 1 patient used the junction of the celiac and splenic arteries; and 1 patient used the celiac cuff). The one patient with standard arterial reconstruction experienced an arterial thrombosis. The graft was salvaged with thrombolysis. Biliary reconstruction was duct-to-duct in five cases and Roux-en-Y in two cases. The OLT procedure is a feasible treatment option for end-stage liver disease after HAIP therapy. Technical considerations include a more challenging dissection and an atypical arterial anastomosis.

Recombination smooths the time signal disrupted by latency inwithin-host HIV phylogenies.

Within-host Human immunodeficiency virus (HIV) evolution involves several features that may disrupt standard phylogenetic reconstruction. One important feature is reactivation of latently integrated provirus, which has the potential to disrupt the temporal signal, leading to variation in the branch lengths and apparent evolutionary rates in a tree. Yet, real within-host HIV phylogenies tend to show clear, ladder-like trees structured by the time of sampling. Another important feature is recombination, which violates the fundamental assumption that evolutionary history can be represented by a single bifurcating tree. Thus, recombination complicates the within-host HIV dynamic by mixing genomes and creating evolutionary loop structures that cannot be represented in a bifurcating tree. In this paper, we develop a coalescent-based simulator of within-host HIV evolution that includes latency, recombination, and effective population size dynamics that allows us to study the relationship between the true, complex genealogy of within-host HIV evolution, encoded as an ancestral recombination graph (ARG), and the observed phylogenetic tree. To compare our ARG results to the familiar phylogeny format, we calculate the expected bifurcating tree after decomposing the ARG into all unique site trees, their combined distance matrix, and the overall corresponding bifurcating tree. While latency and recombination separately disrupt the phylogenetic signal, remarkably, we find that recombination recovers the temporal signal of within-host HIV evolution caused by latency by mixing fragments of old, latent genomes into the contemporary population. In effect, recombination averages over extant heterogeneity, whether it stems from mixed time signals or population bottlenecks. Furthermore, we establish that the signals of latency and recombination can be observed in phylogenetic trees despite being an incorrect representation of the true evolutionary history. Using an approximate Bayesian computation method, we develop a set of statistical probes to tune our simulation model to nine longitudinally sampled within-host HIV phylogenies. Because ARGs are exceedingly difficult to infer from real HIV data, our simulation system allows investigating effects of latency, recombination, and population size bottlenecks by matching decomposed ARGs to real data as observed in standard phylogenies.

A reconstruction of the international standards of religious education of juveniles in correctional institutions

ABSTRACT In this article, we reconstruct the international standards relating to the religious education of a juvenile placed in an isolation centre in connection with the commission of a prohibited act. From a human rights perspective, this is a particularly complicated situation because there is a competition between parties that (at least potentially) have the right to decide on such education. These parties include: juveniles, their parent(s) or legal guardians and the authorities of an isolation centre. The rights of each of them are governed by various legal acts of a different rank – both in an international and national order. An analysis of international documents made it possible to assess the legal situation within the scope defined in the title and formulate certain postulates.

Synthesized Image Reconstruction for Post-Reconstruction Resolution Recovery.

Resolution recovery (RR) techniques in positron emission tomography (PET) imaging aim to mitigate spatial resolution losses and related inaccuracies in quantification by using a model of the system's point spread function (PSF) during reconstruction or post-processing. However, including PSF modeling in fully 3-D image reconstruction is far from trivial as access to the scanner-specific forward and back-projectors is required, along with access to the 3-D sinogram data. Hence, post-reconstruction RR methods, such as the Richardson-Lucy (RL) algorithm, can be more practical. However, the RL method leads to relatively rapid noise amplification in early image iterations, giving inferior image quality compared to iterates obtained by placing the PSF model in the reconstruction algorithm. We propose a post-reconstruction RR method by synthesizing PET data by a forward projection of an initial real data reconstruction (such reconstructions are usually available via a scanner's standard reconstruction software). The synthetic PET data are then used to reconstruct an image, but crucially now including a modeled PSF within the system model used during reconstruction. Results from simulations and real data demonstrate the proposed method improves image quality compared to the RL algorithm, whilst avoiding the need for scanner-specific projectors and raw sinogram data (as required by standard PSF modeling within reconstruction).

Potentials of computer simulation of lung tumors in comparison with &lt;sup&gt;99m&lt;/sup&gt;Тс-MIBI SPECT/CT data

The aim of the study was to develop and validate a software package (SP) for computer simulation of the procedure for examining patients with lung cancer by SPECT/CT and assessing the accuracy of reconstruction of tumor lesions.Material and Methods. Lung scintigraphy for a patient with peripheral squamous cell carcinoma of the upper lobe of the right lung was performed using a two-detector gamma camera GE Discovery NM/CT 670 DR (USA) with high-resolution collimators for an energy of 140 KeV and a radiopharmaceutical (RP) 99mTc-Technetril (MIBI, Diamed, Moscow). The data obtained were subjected to computer processing using a specialized Xeleris 4.0 system from GE (USA). The SP included a program for generating a voxel phantom (“virtual patient”), a program for modeling the “raw” data acquisition (“virtual tomograph”) and an image reconstruction based on the OSEM algorithm (Ordered Subset Expectation Maximization). In order to validate the created SP, computer simulation of the above clinical case was performed. The semi-quantitative comparative image analysis was based on a tumor/background score.Results. There was a good correlation between clinical “raw” data recorded from a real patient and projection data calculated by the Monte Carlo method from a “virtual patient”. The results of the comparative analysis showed that the tumor/background assessment was underestimated in the reconstructed images.Conclusion. The problem of the accuracy of the tumor lesions reconstruction by using standard OSEM reconstruction algorithms has not been studied. This issue is important in the management of patients with tumor lesions of the lungs and requires study and systematization. The SP will be used in further studies to analyze errors and artifacts in images of tumor lesions, as well as to develop approaches to overcome them.

Self-supervised denoising of projection data for low-dose cone-beam CT.

Convolutional neural networks(CNNs) have shown promising results in image denoising tasks. While most existing CNN-based methods depend on supervised learning by directly mapping noisy inputs to clean targets, high-quality references are often unavailable for interventional radiology such as cone-beam computed tomography(CBCT). In this paper, we propose a novel self-supervised learning method that reduces noise in projections acquired by ordinary CBCTscans. With a network that partially blinds input, we are able to train the denoising model by mapping the partially blinded projections to the original projections. Additionally, we incorporate noise-to-noise learning into the self-supervised learning by mapping the adjacent projections to the original projections. With standard image reconstruction methods such as FDK-type algorithms, we can reconstruct high-quality CBCT images from the projections denoised by our projection-domain denoising method. In the head phantom study, we measure peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) values of the proposed method along with the other denoising methods and uncorrected low-dose CBCT data for a quantitative comparison both in projection and image domains. The PSNR and SSIM values of our self-supervised denoising approach are 27.08 and 0.839, whereas those of uncorrected CBCT images are 15.68 and 0.103, respectively. In the retrospective study, we assess the quality of interventional patient CBCT images to evaluate the projection-domain and image-domain denoising methods. Both qualitative and quantitative results indicate that our approach can effectively produce high-quality CBCT images with low-dose projections in the absence of duplicate clean or noisyreferences. Our self-supervised learning strategy is capable of restoring anatomical information while efficiently removing noise in CBCT projection data.

Laparoscopic proximal gastrectomy with right-sided overlap and single-flap valvuloplasty (ROSF): a case-series study

BackgroundThere is no standard reconstruction method following proximal gastrectomy, of which gastroesophageal reflux and anastomotic complications are of great concern. Though several techniques have been devised to overcome these postoperative complications, such as double tract reconstruction, double-flap technique and side overlap fundoplication by Yamashita, none of them is considered a perfect solution. Herein, we designed a novel method of esophagogastrostomy after laparoscopic proximal gastrectomy (LPG), named right-sided overlap and single-flap valvuloplasty (ROSF).MethodsBetween March 2021 and December 2021, 20 consecutive patients underwent LPG-ROSF at Department of Gastrointestinal Surgery, Second Affiliated Hospital of Soochow University. Surgical outcomes and postoperative complications were recorded. All patients were followed-up until December 2022. Endoscopy and assessment of gastrointestinal symptoms were performed 1 year after surgery. Nutrition-related parameters including total body weight, hemoglobin, lymphocyte count, serum total protein, serum albumin and serum prealbumin were evaluated 1 year after surgery and compared with those before surgery.ResultsThe mean surgery time and anastomosis time was 285.3 ± 71.3 and 61.3 ± 11.2 min respectively. None of the patients had gastrointestinal early postoperative complications. Symptomatic reflux was observed in one patient (5%) while reflux esophagitis (Los Angeles Grade A) was observed in another patient (5%). Four patients (20%) had mild dysphagia (Visick score = II) but none of them had anastomotic stenosis. There were no significant changes in nutritional status postoperatively.ConclusionsROSF can be safely performed after LPG and has satisfactory outcomes in preventing reflux and stenosis, and maintaining nutritional status. This technique requires further validation.

Mitigation of motion-induced artifacts in cone beam computed tomography using deep convolutional neural networks.

Cone beam computed tomography (CBCT) is often employed on radiation therapy treatment devices (linear accelerators) used in image-guided radiation therapy (IGRT). For each treatment session, it is necessary to obtain the image of the day in order to accurately position the patient and to enable adaptive treatment capabilities including auto-segmentation and dose calculation. Reconstructed CBCT images often suffer from artifacts, in particular those induced by patient motion. Deep-learning based approaches promise ways to mitigate such artifacts. We propose a novel deep-learning based approach with the goal to reduce motion induced artifacts in CBCT images and improve image quality. It is based on supervised learning and includes neural network architectures employed as pre- and/or post-processing steps during CBCT reconstruction. Our approach is based on deep convolutional neural networks which complement the standard CBCT reconstruction, which is performed either with the analytical Feldkamp-Davis-Kress (FDK) method, or with an iterative algebraic reconstruction technique (SART-TV). The neural networks, which are based on refined U-net architectures, are trained end-to-end in a supervised learning setup. Labeled training data are obtained by means of a motion simulation, which uses the two extreme phases of 4D CT scans, their deformation vector fields, as well as time-dependent amplitude signals as input. The trained networks are validated against ground truth using quantitative metrics, as well as by using real patient CBCT scans for a qualitative evaluation by clinicalexperts. The presented novel approach is able to generalize to unseen data and yields significant reductions in motion induced artifacts as well as improvements in image quality compared with existing state-of-the-art CBCT reconstruction algorithms (up to +6.3 dB and +0.19 improvements in peak signal-to-noise ratio, PSNR, and structural similarity index measure, SSIM, respectively), as evidenced by validation with an unseen test dataset, and confirmed by a clinical evaluation on real patient scans (up to 74% preference for motion artifact reduction over standard reconstruction). For the first time, it is demonstrated, also by means of clinical evaluation, that inserting deep neural networks as pre- and post-processing plugins in the existing 3D CBCT reconstruction and trained end-to-end yield significant improvements in image quality and reduction of motionartifacts.

Quantitative longitudinal mapping of radiation-treated prostate cancer using MR fingerprinting with radial acquisition and subspace reconstruction

MR fingerprinting (MRF) enables fast multiparametric quantitative imaging with a single acquisition and has been shown to improve diagnosis of prostate cancer. However, most prostate MRF studies were performed with spiral acquisitions that are sensitive to B0 inhomogeneities and consequent blurring. In this work, a radial MRF acquisition with a novel subspace reconstruction technique was developed to enable fast T1/T2 mapping in the prostate in under 4 min. The subspace reconstruction exploits the extensive temporal correlations in the MRF dictionary to pre-compute a low dimensional space for the solution and thus reduce the number of radial spokes to accelerate the acquisition. Iterative reconstruction with the subspace model and additional regularization of the signal representation in the subspace is performed to minimize the number of spokes and maintain matching quality and SNR. Reconstruction accuracy was assessed using the ISMRM NIST phantom. In-vivo validation was performed on two healthy subjects and two prostate cancer patients undergoing radiation therapy. The longitudinal repeatability was quantified using the concordance correlation coefficient (CCC) in one of the healthy subjects by repeated scans over 1 year. One prostate cancer patient was scanned at three time points, before initiating therapy and following brachytherapy and external beam radiation. Changes in the T1/T2 maps obtained with the proposed method were quantified. The prostate, peripheral and transitional zones, and visible dominant lesion were delineated for each study, and the statistics and distribution of the quantitative mapping values were analyzed. Significant image quality improvements compared with standard reconstruction methods were obtained with the proposed subspace reconstruction method. A notable decrease in the spread of the T1/T2 values without biasing the estimated mean values was observed with the subspace reconstruction and agreed with reported literature values. The subspace reconstruction enabled visualization of small differences in T1/T2 values in the tumor region within the peripheral zone. Longitudinal imaging of a volunteer subject yielded CCC of 0.89 for MRF T1, and 0.81 for MRF T2 in the prostate gland. Longitudinal imaging of the prostate patient confirmed the feasibility of capturing radiation treatment related changes. This work is a proof-of-concept for a high resolution and fast quantitative mapping using golden-angle radial MRF combined with a subspace reconstruction technique for longitudinal treatment response assessment in subjects undergoing radiation treatment.

Multicenter quantitative 18F-fluorodeoxyglucose positron emission tomography performance harmonization: use of hottest voxels towards more robust quantification.

Harmonization methods reduce variability between different make and models of positron emission tomography (PET) scanners. The study aims to explore harmonization strategies that lead to comparable and robust quantitative metrics in a multicenter setting. NEMA IEC Phantom data acquisition was performed for low and high spheres-to-background ratios (SBR4:1 and 10:1) on six PET/CT (computed tomography) scanners. Different reconstruction sets, including the number of sub-iterations, number of subsets, and full width at half maximum (FWHM) for each scanner, were evaluated towards optimized and harmonized reconstruction settings. Recovery coefficients (RCs) of four quantitative metrics, including standardized uptake value (SUV)max, SUVISO-50 (SUVmean in 50% isocontour), SUVpeak, and mean uptake of 10 highest concentration voxels were evaluated as RCmax, RCISO-50, RCpeak, and RC10V, representing percent difference relative to the static ground truth case as functions of sphere sizes. A set of image reconstruction parameters was proposed for harmonized reconstruction to minimize variability between scanners. The root mean square error (RMSE), curvature, and reproducibility were examined. The proposed reconstruction protocols for harmonization and standard clinical reconstruction settings were compared to each other across all scanners. A significant difference (P value <0.0001) was observed in the aforementioned quantitative metrics between SBR10 and SBR4. Reconstruction parameter sets with the smallest RMSE and RC values within 10% bias were identified as the best candidate for harmonization. The coefficient of variation of the mean value of RCs (CVMRC) shows a remarkable reduction of about 28%, 26%, 32%, and 19% in harmonized reconstruction settings for MRCmax, MRCISO-50, MRCpeak, and MRC10V, respectively. CVMRC for MRC10V in the harmonized reconstruction setting was 5.9% in SBR4, while the smallest value in SBR10 belongs to MRCpeak, with a value of 5.8%. The reproducibility of RC is improved by deriving the value from ten hottest voxels and is equally reproducible with RCpeak. Compared to RCmax and RCISO-50, the variability is reduced by 18% and 22% if ten voxels are pooled. Harmonizing PET/CT systems with and without point spread function/time of flight (PSF/TOF) using various vendor-developed image reconstruction algorithms improves the quantification reproducibility. RC10V, likewise RCpeak, is superior to the rest of the quantitative indices in terms of accuracy and reproducibility and helpful in quantifying lesion volume below 1 mL.

Diagnostic Accuracy of 128-Slice Single-Source CT for the Detection of Dislocated Bucket Handle Meniscal Tears in the Setting of an Acute Knee Trauma—Correlation with MRI and Arthroscopy

(1) Background: Meniscal tears are amongst the most common knee injuries. Dislocated bucket handle meniscal tears in particular should receive early intervention. The purpose of this study was to evaluate the diagnostic performance of CT in detecting dislocated bucket handle meniscal tears compared with the gold-standard MRI and arthroscopy. (2) Methods: Retrospectively, 96 consecutive patients underwent clinically indicated CT of the knee for suspected acute traumatic knee injuries (standard study protocol, 120 kV, 90 mAs). Inclusion criteria were the absence of an acute fracture on CT and a timely MRI (<6 months). Corresponding arthroscopy was assessed. Two experienced musculoskeletal radiologists analyzed the images for dislocated bucket handle meniscal tears, associated signs thereof (double posterior cruciate ligament sign, double delta sign, disproportional posterior horn sign), and subjective diagnostic confidence on a 5-point-Likert scale (1 = 'non-diagnostic image quality', 5 = 'very confident'). (3) Results: Dislocated bucket handle meniscal tears were detected on CT by standard three-plane bone kernel reconstructions with a sensitivity of 90.7% and a specificity of 99.3% by transferring the knowledge of established MRI signs. The additional use of soft-tissue kernel reconstructions in three planes increased the sensitivity by 4.0% to 94.7%, specificity to 100%, inter-rater agreement to 1.0, and the diagnostic confidence of both readers improved to a median 4/5 ('confident') in both readers. (4) Conclusions: Trauma CT scan of the knee with three-plane soft-tissue reconstructions delivers the potential for the detection of dislocated bucket handle meniscal tears with very high diagnostic accuracy.

2022 음악과 교육과정 교과역량과 성취기준 재구성에 따른 중학교 블렌디드 감상수업 연구

Objectives The purpose of this study is to present an effective appreciation class plan by linking the reconstruction of achievement standards with core competencies through blended learning classes according to the reorganization achievement standards by the 2022 music curriculum. Methods To this end, the restructuring of achievement standards was compared to the existing achievement standards, and the class plan was devised in connection with five curriculum competencies as a total of 3 classes for the 1st and 2nd classes and for the online class 3rd class for the offline class by using integration and readjustment during the restructuring of achievement standards. Results It was suggested to develop all five core competencies while preventing content connection, optimization of learning volume, and learning deficits by using blended learning classes. Conclusions Through blended learning classes, the effect of growing according to individual abilities, inducing interest, and forming bonds was derived, and through listening classes, the effect of experiencing the aesthetics of music, sympathizing with other people's thoughts, and accepting various cultures was derived.

Photon-Counting Computed Tomography (PC-CT) of the spine: impact on diagnostic confidence and radiation dose

ObjectivesComputed tomography (CT) is employed to evaluate surgical outcome after spinal interventions. Here, we investigate the potential of multispectral photon-counting computed tomography (PC-CT) on image quality, diagnostic confidence, and radiation dose compared to an energy-integrating CT (EID-CT).MethodsIn this prospective study, 32 patients underwent PC-CT of the spine. Data was reconstructed in two ways: (1) standard bone kernel with 65-keV (PC-CTstd) and (2) 130-keV monoenergetic images (PC-CT130 keV). Prior EID-CT was available for 17 patients; for the remaining 15, an age–, sex–, and body mass index–matched EID-CT cohort was identified. Image quality (5-point Likert scales on overall, sharpness, artifacts, noise, diagnostic confidence) of PC-CTstd and EID-CT was assessed by four radiologists independently. If metallic implants were present (n = 10), PC-CTstd and PC-CT130 keV images were again assessed by 5-point Likert scales by the same radiologists. Hounsfield units (HU) were measured within metallic artifact and compared between PC-CTstd and PC-CT130 keV. Finally, the radiation dose (CTDIvol) was evaluated.ResultsSharpness was rated significantly higher (p = 0.009) and noise significantly lower (p < 0.001) in PC-CTstd vs. EID-CT. In the subset of patients with metallic implants, reading scores for PC-CT130 keV revealed superior ratings vs. PC-CTstd for image quality, artifacts, noise, and diagnostic confidence (all p < 0.001) accompanied by a significant increase of HU values within the artifact (p < 0.001). Radiation dose was significantly lower for PC-CT vs. EID-CT (mean CTDIvol: 8.83 vs. 15.7 mGy; p < 0.001).ConclusionsPC-CT of the spine with high-kiloelectronvolt reconstructions provides sharper images, higher diagnostic confidence, and lower radiation dose in patients with metallic implants.Key Points• Compared to energy-integrating CT, photon-counting CT of the spine had significantly higher sharpness and lower image noise while radiation dose was reduced by 45%.• In patients with metallic implants, virtual monochromatic photon-counting images at 130 keV were superior to standard reconstruction at 65 keV in terms of image quality, artifacts, noise, and diagnostic confidence.

Evaluation of the second-generation whole-heart motion correction algorithm (SSF2) used to demonstrate the aortic annulus on cardiac CT

The main purpose of pre-transcatheter aortic valve implantation (TAVI) cardiac computed tomography (CT) for patients with severe aortic stenosis is aortic annulus measurements. However, motion artifacts present a technical challenge because they can reduce the measurement accuracy of the aortic annulus. Therefore, we applied the recently developed second-generation whole-heart motion correction algorithm (SnapShot Freeze 2.0, SSF2) to pre-TAVI cardiac CT and investigated its clinical utility by stratified analysis of the patient's heart rate during scanning. We found that SSF2 reconstruction significantly reduced aortic annulus motion artifacts and improved the image quality and measurement accuracy compared to standard reconstruction, especially in patients with high heart rate or a 40% R-R interval (systolic phase). SSF2 may contribute to improving the measurement accuracy of the aortic annulus.

What's New in Sports Medicine.

What's New in Sports Medicine.

Effects of DIEP flap-based breast reconstruction on respiratory function

BackgroundBreast reconstruction (BR) is an essential part of breast cancer treatment, and the DIEP flap is considered the gold standard reconstruction technique, which uses a free abdominal flap. Concerns have been raised regarding the effects of abdominoplasty on respiratory functions. This topic has not been addressed regarding donor-site closure of DIEP flaps. Our aim is to prospectively compare preoperative and postoperative spirometry in patients undergoing DIEP flap-based BR, investigating its impact on respiratory function. Materials and methodsWe enrolled 21 patients who received BR with DIEP flap in our institution, who underwent pulmonary function assessment by spirometry 1 month preoperatively and 1 year postoperatively. We assessed Forced Expiratory Volume in the first second (FEV1), Forced Vital Capacity (FVC), FEV1/FVC ratio, and Peak Expiratory Flow (PEF). Statistical analysis was performed using the paired samples test. ResultsAn improvement in the mean values of all 4 variables was found at 1 year from surgery. Namely, FEV1 improved by 0.1 L with a standard deviation (SD) of 0.39 L, FVC by 0.04 L with SD of 0.627, FEV1/FVC by 2.11 L with SD of 7.85 L, and PEF by 1.2 L with SD of 1.45 L. Only PEF was statistically significant [P = 0.001]. ConclusionOur results suggest that DIEP flap BR does not negatively impact respiratory function. Although further knowledge is required, we confirm the possibility of considering the indication for abdominoplasty and DIEP flap reconstruction in patients with altered and reduced pulmonary function.

Reconstructing cosmological initial conditions from late-time structure with convolutional neural networks

ABSTRACT We present a method to reconstruct the initial linear-regime matter density field from the late-time non-linearly evolved density field in which we channel the output of standard first-order reconstruction to a convolutional neural network (CNN). Our method shows dramatic improvement over the reconstruction of either component alone. We show why CNNs are not well-suited for reconstructing the initial density directly from the late-time density: CNNs are local models, but the relationship between initial and late-time density is not local. Our method leverages standard reconstruction as a preprocessing step, which inverts bulk gravitational flows sourced over very large scales, transforming the residual reconstruction problem from long-range to local and making it ideally suited for a CNN. We develop additional techniques to account for redshift distortions, which warp the density fields measured by galaxy surveys. Our method improves the range of scales of high-fidelity reconstruction by a factor of 2 in wavenumber above standard reconstruction, corresponding to a factor of 8 increase in the number of well-reconstructed modes. In addition, our method almost completely eliminates the anisotropy caused by redshift distortions. As galaxy surveys continue to map the Universe in increasingly greater detail, our results demonstrate the opportunity offered by CNNs to untangle the non-linear clustering at intermediate scales more accurately than ever before.

Deep Learning MRI Reconstruction for Accelerating Turbo Spin Echo Hand and Wrist Imaging: A Comparison of Image Quality, Visualization of Anatomy, and Detection of Common Pathologies with Standard Imaging

Magnetic resonance imaging (MRI) of the hand and wrist is a routine MRI examination and takes about 15-20 minutes, which can lead to problems resulting from the relatively long scan time, such as decreased image quality due to motion artifacts and lower patient throughput. The objective of this study was to evaluate a deep learning (DL) reconstruction for turbo spin echo (TSE) sequences of the hand and wrist regarding image quality, visualization of anatomy, and diagnostic performance concerning common pathologies. Twenty-one patients (mean age: 43 ± 19 [19-85] years, 10 men, 11 female) were prospectively enrolled in this study between October 2020 and June 2021. Each participant underwent two MRI protocols: first, standard fully sampled TSE sequences reconstructed with a standard GRAPPA reconstruction (TSES) and second, prospectively undersampled TSE sequences using a conventional parallel imaging undersampling pattern reconstructed with a DL reconstruction (TSEDL). Both protocols were acquired consecutively in one examination. Two experienced MSK-imaging radiologists qualitatively evaluated the images concerning image quality, noise, edge sharpness, artifacts, and diagnostic confidence, as well as the delineation of anatomical structures (triangular fibrocartilage complex, tendon of the extensor carpi ulnaris muscle, extrinsic and intrinsic ligaments, median nerve, cartilage) using a five-point Likert scale and assessed common pathologies. Wilcoxon signed-rank test and kappa statistics were performed to compare the sequences. Overall image quality, artifacts, delineation of anatomical structures, and diagnostic confidence of TSEDL were rated to be comparable to TSES (p > 0.05). Additionally, TSEDL showed decreased image noise (4.90, median 5, IQR 5-5) compared to TSES (4.52, median 5, IQR 4-5, p < 0.05) and improved edge sharpness (TSEDL: 4.10, median 4, IQR 3.5-5; TSES: 3.57, median 4, IQR 3-4; p < 0.05). Inter- and intrareader agreement was substantial to almost perfect (κ=0.632-1.000) for the detection of common pathologies. Time of acquisition could be reduced by more than 60% with the protocol using TSEDL. Compared to TSES, TSEDL provided decreased noise and increased edge sharpness, equal image quality, delineation of anatomical structures, detection of pathologies, and diagnostic confidence. Therefore, TSEDL may be clinically relevant for hand and wrist imaging, as it reduces examination time by more than 60%, thus increasing patient comfort and patient throughput.