Pulmonary arteriovenous malformation causing lung sequestration and media infarction: a case report.

Pulmonary arteriovenous malformations (PAVMs) are rare vascular malformations of the lungs. Direct communication of pulmonary arteries to pulmonary veins is the defining characteristic allowing venous blood to bypass the pulmonary capillary system and avoiding an efficient oxygenation process. The complexity of the pathology lies not only in the variety of its manifestations, but also in the choice of the most appropriate and effective treatment.

Deep Learning-Based Signal Amplification of T1-Weighted Single-Dose Images Improves Metastasis Detection in Brain MRI.

Objectives: Double-dose contrast-enhanced brain imaging improves tumor delineation and detection of occult metastases but is limited by concerns about gadolinium-based contrast agents' effects on patients and the environment. The purpose of this study was to test the benefit of a deep learning-based contrast signal amplification in true single-dose T1-weighted (T-SD) images creating artificial double-dose (A-DD) images for metastasis detection in brain magnetic resonance imaging.

Materials And Methods: In this prospective, multicenter study, a deep learning-based method originally trained on noncontrast, low-dose, and T-SD brain images was applied to T-SD images of 30 participants (mean age ± SD, 58.

Metastasis Detection Using True and Artificial T1-Weighted Postcontrast Images in Brain MRI.

Objectives: Small lesions are the limiting factor for reducing gadolinium-based contrast agents in brain magnetic resonance imaging (MRI). The purpose of this study was to compare the sensitivity and precision in metastasis detection on true contrast-enhanced T1-weighted (T1w) images and artificial images synthesized by a deep learning method using low-dose images.

Materials And Methods: In this prospective, multicenter study (5 centers, 12 scanners), 917 participants underwent brain MRI between October 2021 and March 2023 including T1w low-dose (0.

Lessons Learned: Risk Factors and Clinical Impact of Severe Pneumothorax After Endoscopic Lung Volume Reduction With Endobronchial Valves.

Background: Pneumothorax is a major complication after endoscopic lung volume reduction with valves, with a prevalence of up to 34%. Although some patients benefit from valve implantation despite pneumothorax, others are significantly impaired after lung collapse.

Research Question: What are the differences in the severity grades of pneumothorax and how do these affect clinical practice?

Study Design And Methods: This single-center retrospective study analyzed patients undergoing endoscopic valve implantation with and without pneumothorax after intervention.

Incidental Pulmonary Nodules: Differential Diagnosis and Clinical Management.

Background: According to data from the USA, the incidence of incidentally discovered pulmonary nodules is 5.8 per 100 000 person- years for women and 5.2 per 100 000 person-years for men.

Delta-radiomics features of ADC maps as early predictors of treatment response in lung cancer.

Objective: Investigate the feasibility of detecting early treatment-induced tumor tissue changes in patients with advanced lung adenocarcinoma using diffusion-weighted MRI-derived radiomics features.

Methods: This prospective observational study included 144 patients receiving either tyrosine kinase inhibitors (TKI, n = 64) or platinum-based chemotherapy (PBC, n = 80) for the treatment of pulmonary adenocarcinoma. Patients underwent diffusion-weighted MRI the day prior to therapy (baseline, all patients), as well as either + 1 (PBC) or + 7 and + 14 (TKI) days after treatment initiation.

Diagnostic Potential of Supplemental Static and Dynamic Ga-FAPI-46 PET for Primary F-FDG-Negative Pulmonary Lesions.

PET using Ga-labeled fibroblast activation protein (FAP) inhibitors (FAPIs) holds high potential for diagnostic imaging of various malignancies, including lung cancer (LC). However, F-FDG PET is still the clinical gold standard for LC imaging. Several subtypes of LC, especially lepidic LC, are frequently F-FDG PET-negative, which markedly hampers the assessment of single pulmonary lesions suggestive of LC.

Deep-learning based detection of vessel occlusions on CT-angiography in patients with suspected acute ischemic stroke.

Swift diagnosis and treatment play a decisive role in the clinical outcome of patients with acute ischemic stroke (AIS), and computer-aided diagnosis (CAD) systems can accelerate the underlying diagnostic processes. Here, we developed an artificial neural network (ANN) which allows automated detection of abnormal vessel findings without any a-priori restrictions and in <2 minutes. Pseudo-prospective external validation was performed in consecutive patients with suspected AIS from 4 different hospitals during a 6-month timeframe and demonstrated high sensitivity (≥87%) and negative predictive value (≥93%).

Prediction of Bone Marrow Biopsy Results From MRI in Multiple Myeloma Patients Using Deep Learning and Radiomics.

Objectives: In multiple myeloma and its precursor stages, plasma cell infiltration (PCI) and cytogenetic aberrations are important for staging, risk stratification, and response assessment. However, invasive bone marrow (BM) biopsies cannot be performed frequently and multifocally to assess the spatially heterogenous tumor tissue. Therefore, the goal of this study was to establish an automated framework to predict local BM biopsy results from magnetic resonance imaging (MRI).

Characterization of three new variants PiQ0, PiQ0 and PiQ0 in patients with severe alpha-1 antitrypsin deficiency.

Background: The clinical and molecular characteristics of three patients with previously unreported mutations associated with severe alpha-1 antitrypsin deficiency (AATD) are described. The pathophysiology of the chronic obstructive pulmonary disease (COPD) present in these patients was characterized through clinical, biochemical, and genetic examinations.

Case Presentations: Case 1: A 73-year-old male with bilateral centri-to panlobular emphysema and multiple increasing ventrobasal bullae and incomplete fissures, COPD (Global Initiative for Chronic Obstructive Lung Disease (GOLD) grade III B), progressive dyspnea on exertion (DOE), AAT level of 0.

Quantitative CT analysis of lung parenchyma to improve malignancy risk estimation in incidental pulmonary nodules.

Objectives: To assess the value of quantitative computed tomography (QCT) of the whole lung and nodule-bearing lobe regarding pulmonary nodule malignancy risk estimation.

Methods: A total of 251 subjects (median [IQR] age, 65 (57-73) years; 37% females) with pulmonary nodules on non-enhanced thin-section CT were retrospectively included. Twenty percent of the nodules were malignant, the remainder benign either histologically or at least 1-year follow-up.

AI-Supported Comprehensive Detection and Quantification of Biomarkers of Subclinical Widespread Diseases at Chest CT for Preventive Medicine.

Automated image analysis plays an increasing role in radiology in detecting and quantifying image features outside of the perception of human eyes. Common AI-based approaches address a single medical problem, although patients often present with multiple interacting, frequently subclinical medical conditions. A holistic imaging diagnostics tool based on artificial intelligence (AI) has the potential of providing an overview of multi-system comorbidities within a single workflow.

Deep Learning for Automatic Bone Marrow Apparent Diffusion Coefficient Measurements From Whole-Body Magnetic Resonance Imaging in Patients With Multiple Myeloma: A Retrospective Multicenter Study.

Objectives: Diffusion-weighted magnetic resonance imaging (MRI) is increasingly important in patients with multiple myeloma (MM). The objective of this study was to train and test an algorithm for automatic pelvic bone marrow analysis from whole-body apparent diffusion coefficient (ADC) maps in patients with MM, which automatically segments pelvic bones and subsequently extracts objective, representative ADC measurements from each bone.

Materials And Methods: In this retrospective multicentric study, 180 MRIs from 54 patients were annotated (semi)manually and used to train an nnU-Net for automatic, individual segmentation of the right hip bone, the left hip bone, and the sacral bone.

Augmentation therapy with human alpha-1-proteinase inhibitor reduces exacerbations in patient with bronchiectasis and alpha-1-antitrypsin deficiency.

Alpha-1-antitrypsin deficiency (AATD) is a rare cause of noncystic fibrosis (CF) bronchiectasis. The benefits of augmentation therapy in patients with chronic obstructive pulmonary disease (COPD) and pulmonary emphysema are well established. The role of augmentation therapy in AATD bronchiectasis in patients without pulmonary emphysema is not clear.

Automated detection and quantification of brain metastases on clinical MRI data using artificial neural networks.

Background: Reliable detection and precise volumetric quantification of brain metastases (BM) on MRI are essential for guiding treatment decisions. Here we evaluate the potential of artificial neural networks (ANN) for automated detection and quantification of BM.

Methods: A consecutive series of 308 patients with BM was used for developing an ANN (with a 4:1 split for training/testing) for automated volumetric assessment of contrast-enhancing tumors (CE) and non-enhancing FLAIR signal abnormality including edema (NEE).

Clinical characterization of a novel alpha1-antitrypsin null variant: PiQ0.

The clinical characterization of a null variant of - PiQ0 - resulting in alpha1-antitrypsin (AAT) deficiency is described. This rare mutation (c.-5+5 G > A) has been previously identified but not clinically described.

A reporting and analysis framework for structured evaluation of COVID-19 clinical and imaging data.

The COVID-19 pandemic has worldwide individual and socioeconomic consequences. Chest computed tomography has been found to support diagnostics and disease monitoring. A standardized approach to generate, collect, analyze, and share clinical and imaging information in the highest quality possible is urgently needed.

An undifferentiated carcinoma at Klatskin-position with long-term complete remission after chemotherapy.

Background: Neoplasms anatomically adjacent to the bile duct usually derive from malignantly transformed cholangiocytes forming cholangiocarcinoma (CCA). CCAs are divided in extrahepatic (eCCA) and intrahepatic (iCCA) tumors. Patients with irresectable CCAs are treated with systemic chemotherapy and have an unfavorable prognosis with a median survival of about one year.

Liver cancers with stem/progenitor-cell features - a rare chemotherapy-sensitive malignancy.

Primary liver tumors are a heterogeneous group of malignancies. Besides classical hepatocellular carcinoma (HCC) and cholangiocarcinoma (CC), combined and intermediate forms of liver cancer exist and can express stem-cell markers like nuclear cell adhesion molecule (NCAM-1/CD56), c-kit (CD117) or epithelial cell adhesion molecule (EpCAM) together with high proliferative activity. Liver tumors with progenitor-cell features are associated with an unfavorable prognosis, but the phenotype has not resulted in therapeutic consequences so far.

[Pituitary gland tumors].

Background And Objectives: This article gives an overview of the most common tumors of the pituitary gland and the differential diagnostics with special emphasis on radiological diagnostic criteria.

Material And Methods: A selective search of the literature in PubMed was carried out.

Results: Pituitary adenomas constitute 10-15% of all intracranial tumors and are the most common tumors of the sellar region.

Library of molecular associations: curating the complex molecular basis of liver diseases.

Background: Systems biology approaches offer novel insights into the development of chronic liver diseases. Current genomic databases supporting systems biology analyses are mostly based on microarray data. Although these data often cover genome wide expression, the validity of single microarray experiments remains questionable.

BlotBase: a northern blot database.

With the availability of high-throughput gene expression analysis, multiple public expression databases emerged, mostly based on microarray expression data. Although these databases are of significant biomedical value, they do hold significant drawbacks, especially concerning the reliability of single gene expression profiles obtained by microarray data. Simultaneously, reliable data on an individual gene's expression are often published as single northern blots in individual publications.

Pheromone components from body scales of female Anarsia lineatella induce contacts by conspecific males.

Pheromonal communication of adult peach twig borers, Anarsia lineatella Zeller (Lepidoptera: Gelechiidae), was reinvestigated based on recent findings that virgin female-baited traps were more attractive to mate-seeking males than a two-component synthetic sex pheromone consisting of (E)-5-decen-1-yl acetate (1000 microg) and (E)-5-decen-1-ol (100 microg), suggesting that females use additional pheromone components. Hypothesizing that these additional components may be released from body parts other than abdominal sex pheromone glands, we extracted female body scales and analyzed aliquots by coupled gas chromatographic-electroantennographic detection (GC-EAD) and GC-mass spectrometry. Eight straight-chain and four methylated aliphatic hydrocarbons, as well as two acetates, all elicited responses from excised male antennae.