Association of AI-determined Kellgren-Lawrence grade with medial meniscus extrusion and cartilage thickness by AI-based 3D MRI analysis in early knee osteoarthritis.

The associations among Kellgren-Lawrence (KL) grade, medial meniscus extrusion (MME), and cartilage thickness in knee osteoarthritis (OA) remain insufficiently understood. Our aim was to determine these associations in early to moderate medial tibiofemoral knee OA. We included 469 subjects with no lateral OA from the Kanagawa Knee Study.

Combination of leucine-rich alpha-2 glycoprotein and fecal markers detect Crohn's disease activity confirmed by balloon-assisted enteroscopy.

Background/aims: Endoscopic activity confirmed by enteroscopy is associated with poor clinical outcome in Crohn's disease (CD). We investigated which of the existing biomarkers best reflects endoscopic activity in CD patients including the small bowel, and whether their combined use can improve accuracy.

Methods: One hundred and four consecutive patients with ileal and ileocolonic type CD who underwent balloon-assisted enteroscopy (BAE) from October 2021 to August 2022 were enrolled, with clinical and laboratory data prospectively collected and analyzed.

Novel utility of Vesical Imaging-Reporting and Data System in multimodal treatment for muscle-invasive bladder cancer.

Objectives: To examine the clinical significance of the Vesical Imaging-Reporting and Data System (VI-RADS) in predicting outcome of multimodal treatment (MMT) in muscle-invasive bladder cancer (MIBC) patients.

Methods: We reviewed 78 pathologically proven MIBC patients who underwent MMT including transurethral resection and chemoradiotherapy, followed by partial or radical cystectomy. Treatment response was assessed through histologic evaluation of cystectomy specimens.

Serum Leucine-Rich α2 Glycoprotein: A Novel Biomarker for Transmural Inflammation in Crohn's Disease.

Introduction: Leucine-rich alpha-2 glycoprotein (LRG) is a newly studied biomarker for inflammatory diseases. This study aimed to investigate whether LRG can be used for evaluating transmural activity in patients with Crohn's disease (CD).

Methods: We performed magnetic resonance enterography (MRE) in 227 consecutive patients with CD from June 2020 to August 2021.

Motility Mapping Quantification Using the Classical Optical Flow Algorithm for Small Bowel Crohn's Disease: Comparison with Balloon-assisted Enteroscopy Findings.

Purpose: To quantify bowel motility shown on cine MRI using the classical optical flow algorithm and compare it with balloon-assisted enteroscopy (BAE) findings in patients with Crohn's disease (CD).

Methods: This retrospective study included 29 consecutive patients with CD who had undergone MR enterocolonography (MREC) and BAE between March and May 2017. We developed computer software to present motion vector magnitudes between consecutive cine MR images as bowel motility maps via a classical optical flow algorithm using the Horn-Schunck method.

Can Deep Learning-Based Volumetric Analysis Predict Oxygen Demand Increase in Patients with COVID-19 Pneumonia?

: This study aimed to investigate whether predictive indicators for the deterioration of respiratory status can be derived from the deep learning data analysis of initial chest computed tomography (CT) scans of patients with coronavirus disease 2019 (COVID-19). : Out of 117 CT scans of 75 patients with COVID-19 admitted to our hospital between April and June 2020, we retrospectively analyzed 79 CT scans that had a definite time of onset and were performed prior to any medication intervention. Patients were grouped according to the presence or absence of increased oxygen demand after CT scan.

Crohn disease: magnetic resonance enterocolonography features of endoscopic ulcer stages reclassified with the healing process and the relationships to prognoses.

Purpose: This study aimed to compare magnetic resonance enterocolonography (MREC) features among the endoscopic ulcer stages reclassified to include healing ulcers and to assess the prognoses in Crohn disease (CD).

Methods: Altogether, 89 consecutive patients with CD who had undergone MREC and ileocolonoscopy or balloon-assisted enteroscopy were retrospectively studied. Patients were reclassified into 38 patients with no deep ulcer, seven with healing deep ulcer, and 44 with active deep ulcer stage.

The Utility of Deep Learning in Breast Ultrasonic Imaging: A Review.

Breast cancer is the most frequently diagnosed cancer in women; it poses a serious threat to women's health. Thus, early detection and proper treatment can improve patient prognosis. Breast ultrasound is one of the most commonly used modalities for diagnosing and detecting breast cancer in clinical practice.

Dynamic Enhancement Pattern on CT for Predicting Pancreatic Neuroendocrine Neoplasms with Low PAX6 Expression: A Retrospective Observational Study.

Paired box 6 (PAX6) is a transcription factor that plays a critical role in tumor suppression, implying that the downregulation of PAX6 promotes tumor growth and invasiveness. This study aimed to examine dynamic computed tomography (CT) features for predicting pancreatic neuroendocrine neoplasms (Pan-NENs) with low PAX6 expression. We retrospectively evaluated 51 patients with Pan-NENs without synchronous liver metastasis to assess the pathological expression of PAX6.

High b-value computed diffusion-weighted imaging for differentiating bowel inflammation in Crohn's disease.

Purpose This study evaluated whether high b-value computed diffusion-weighted imaging (cDWI) can improve detection and differentiation of bowel inflammation in patients with Crohn's disease (CD). Methods Fifty-four consecutive CD patients who had undergone magnetic resonance enterography (MRE) and ileocolonoscopy (ICS) or balloon-assisted enteroscopy (BAE) were retrospectively studied; cDWI with a b-value = 1500s/mm (cDWI1500) was generated using DWI acquired with b-values of 0 and 800 s/mm (aDWI800). Overall, 366 bowel segments were evaluated.

Evaluation of the Usefulness of CO-RADS for Chest CT in Patients Suspected of Having COVID-19.

The purpose of this study was to use the Coronavirus Disease 2019 (COVID-19) Reporting and Data System (CO-RADS) to evaluate the chest computed tomography (CT) images of patients suspected of having COVID-19, and to investigate its diagnostic performance and interobserver agreement. The Dutch Radiological Society developed CO-RADS as a diagnostic indicator for assessing suspicion of lung involvement of COVID-19 on a scale of 1 (very low) to 5 (very high). We investigated retrospectively 154 adult patients with clinically suspected COVID-19, between April and June 2020, who underwent chest CT and reverse transcription-polymerase chain reaction (RT-PCR).

Efficient Anomaly Detection with Generative Adversarial Network for Breast Ultrasound Imaging.

We aimed to use generative adversarial network (GAN)-based anomaly detection to diagnose images of normal tissue, benign masses, or malignant masses on breast ultrasound. We retrospectively collected 531 normal breast ultrasound images from 69 patients. Data augmentation was performed and 6372 (531 × 12) images were available for training.

Feasibility of new fat suppression for breast MRI using pix2pix.

Purpose: To generate and evaluate fat-saturated T1-weighted (FST1W) image synthesis of breast magnetic resonance imaging (MRI) using pix2pix.

Materials And Methods: We collected pairs of noncontrast-enhanced T1-weighted an FST1W images of breast MRI for training data (2112 pairs from 15 patients), validation data (428 pairs from three patients), and test data (90 pairs from 30 patients). From the original images, 90 synthetic images were generated with 50, 100, and 200 epochs using pix2pix.

Virtual Interpolation Images of Tumor Development and Growth on Breast Ultrasound Image Synthesis With Deep Convolutional Generative Adversarial Networks.

Objectives: We sought to generate realistic synthetic breast ultrasound images and express virtual interpolation images of tumors using a deep convolutional generative adversarial network (DCGAN).

Methods: After retrospective selection of breast ultrasound images of 528 benign masses, 529 malignant masses, and 583 normal breasts, 20 synthesized images of each were generated by the DCGAN. Fifteen virtual interpolation images of tumors were generated by changing the value of the input vector.

Classification of Breast Masses on Ultrasound Shear Wave Elastography using Convolutional Neural Networks.

We aimed to use deep learning with convolutional neural networks (CNNs) to discriminate images of benign and malignant breast masses on ultrasound shear wave elastography (SWE). We retrospectively gathered 158 images of benign masses and 146 images of malignant masses as training data for SWE. A deep learning model was constructed using several CNN architectures (Xception, InceptionV3, InceptionResNetV2, DenseNet121, DenseNet169, and NASNetMobile) with 50, 100, and 200 epochs.

Objective evaluation for treat to target in Crohn's disease.

Background: Crohn's disease (CD) is a chronic and destructive bowel disease; continued disease activity can lead to penetrating complications. With the recent advent of effective medications, the importance of using a treat-to-target approach to guide therapy is becoming important.

Methods: In this review, we reviewed the previous evidence for evaluating CD lesions.

Breast Ultrasound Image Synthesis using Deep Convolutional Generative Adversarial Networks.

Deep convolutional generative adversarial networks (DCGANs) are newly developed tools for generating synthesized images. To determine the clinical utility of synthesized images, we generated breast ultrasound images and assessed their quality and clinical value. After retrospectively collecting 528 images of 144 benign masses and 529 images of 216 malignant masses in the breasts, synthesized images were generated using a DCGAN with 50, 100, 200, 500, and 1000 epochs.

Crohn Disease: A 5-Point MR Enterocolonography Classification Using Enteroscopic Findings.

Objective: The objectives of our study were to establish the efficacy of a 5-point MR enterocolonography classification for assessing Crohn disease (CD) activity, compare this classification with a validated MRI score (i.e., the MR index of activity [MaRIA]), and compare both with endoscopic findings, which were assessed using the Crohn disease endoscopic index of severity (CDEIS).

Balloon-Occluded Carbon Dioxide Gas Angiography for Internal Iliac Arteriography and Intervention.

Introduction: The usefulness of carbon dioxide (CO) gas digital subtraction angiography (DSA) has been reported for patients with renal insufficiency and allergy to iodinated contrast agents. However, CO gas cannot replace the iodinated contrast agent in all cases owing to some disadvantages. We describe balloon-occluded CO DSA (B-CO DSA) as an improved CO DSA procedure for interventions in the internal iliac artery (IIA) region and compare the quality of images obtained using conventional CO DSA and B-CO DSA.

Prognostic implications of Cu-diacetyl-bis (N-methylthiosemicarbazone) PET/CT in patients with glioma.

Objective: The potential of positron emission tomography/computed tomography using Cu-diacetyl-bis (N-methylthiosemicarbazone) (Cu-ATSM PET/CT), which was originally developed as a hypoxic tracer, to predict therapeutic resistance and prognosis has been reported in various cancers. Our purpose was to investigate prognostic value of Cu-ATSM PET/CT in patients with glioma, compared to PET/CT using 2-deoxy-2-[F]fluoro-D-glucose (F-FDG).

Method: 56 patients with glioma of World Health Organization grade 2-4 were enrolled.

Prediction of histological grade of hepatocellular carcinoma using quantitative diffusion-weighted MRI: a retrospective multivendor study.

Objective: To evaluate the usefulness of quantitative diffusion-weighted (DW) imaging acquired by multivendor magnetic resonance units for predicting grade of hepatocellular carcinoma (HCC).

Methods: 83 patients with 100 histologically diagnosed HCCs who underwent pre-operative liver DW imaging with b = 0 and1000 s mm or b = 0 and800 s mm at any of six institutions were included. Two radiologists independently measured the apparent diffusion coefficient (ADC) of the lesion as well as non-ADC parameters, such as the relative contrast ratio and the contrast-to-noise ratio (CNR) between the lesion and the liver parenchyma on high b-value DW images.