NightHawk: A Low-Cost, Nighttime Light Wildfire Observation Platform and Its Radiometric Calibration.

We present a low-cost prototype of a visible and near-infrared (VIS-NIR) remote sensing platform, optimized to detect and characterize natural flaming fire fronts from airborne nighttime light (NTL) observations, and its radiometric calibration. It uses commercially available CMOS sensor cameras and filters with roughly 100 nm bandwidths to effectively discriminate burning biomass from other sources of NTL, a critical ability for wildfire monitoring near populated areas. Our filter choice takes advantage of the strong potassium line emission near 770 nm present in natural flaming.

Active Label Refinement for Robust Training of Imbalanced Medical Image Classification Tasks in the Presence of High Label Noise.

The robustness of supervised deep learning-based medical image classification is significantly undermined by label noise in the training data. Although several methods have been proposed to enhance classification performance in the presence of noisy labels, they face some challenges: 1) a struggle with class-imbalanced datasets, leading to the frequent overlooking of minority classes as noisy samples; 2) a singular focus on maximizing performance using noisy datasets, without incorporating experts-in-the-loop for actively cleaning the noisy labels. To mitigate these challenges, we propose a two-phase approach that combines Learning with Noisy Labels (LNL) and active learning.

Prognostic significance of clinicopathological and ultrasonographic features in anaplastic thyroid carcinoma beyond TERT promoter mutation.

TERT promoter mutation is associated with poor prognosis in differentiated thyroid carcinoma, with US features varying by mutation status. However, this correlation in anaplastic thyroid carcinoma (ATC) is understudied. We investigated the association between clinicopathological characteristics and US features of ATC with TERT mutation status and prognosis.

Fast Two-photon Microscopy by Neuroimaging with Oblong Random Acquisition (NORA).

Advances in neural imaging have enabled neuroscientists to study how the joint activity of large neural populations conspire to produce perception, behavior and cognition. Despite many advances in optical methods, there exists a fundamental tradeoff between imaging speed, field of view, and resolution that limits the scope of neural imaging, especially for the raster-scanning multi-photon imaging needed for imaging deeper into the brain. One approach to overcoming this trade-off is computational imaging: the co-development of optics and algorithms where the optics are designed to encode the target images into fewer measurements that are faster to acquire, and the algorithms compensates by inverting the optical coding to recover a larger or higher resolution image.

Factors that predict progression of von Hippel-Lindau disease-related malignancy: a longitudinal cohort study.

Background: Von Hippel-Lindau (vHL) disease encompasses various genetic subtypes with poorly defined progression patterns. This retrospective study of a longitudinal cohort aimed to characterize follow-up duration, treatment rates, and progression patterns according to genomic subtype, and to identify risk factors for progression.

Methods: Between June 2003 and June 2020, the study enrolled 94 patients (mean age, 37.

Digital mammography with AI-based computer-aided diagnosis to predict neoadjuvant chemotherapy response in HER2-positive and triple-negative breast cancer patients: comparison with MRI.

Objective: To investigate whether digital mammography (DM) with artificial intelligence-based computer-aided diagnosis (AI-CAD) predicts pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) in human epidermal growth factor receptor 2 (HER2)-positive and triple-negative (TN) breast cancers and compare performance with dynamic contrast-enhanced (DCE)-MRI.

Materials And Methods: In this single-center study, patients who underwent NAC and surgery for HER2-positive or TN cancers between September 2020 and August 2021 were retrospectively selected to develop prediction models for pCR after NAC. From a prospective ASLAN (Avoid axillary Sentinel Lymph node biopsy After Neoadjuvant chemotherapy) trial, HER2-positive and TN cancer patients who underwent NAC and surgery between December 2021 and July 2022 were prospectively selected for model validation.

Unraveling the immune-activated tumor microenvironment correlated with clinical response to atezolizumab plus bevacizumab in advanced HCC.

Background & Aims: Despite atezolizumab plus bevacizumab being a standard treatment for advanced hepatocellular carcinoma (HCC), a significant proportion of patients do not achieve durable benefit. This study aimed to identify predictive biomarkers for this therapy by investigating the role of immune activation within the tumor microenvironment (TME).

Methods: We characterized the intratumoral TME of patients with advanced HCC treated with atezolizumab plus bevacizumab using single cell transcriptomics on pretreatment tumor biopsies from 12 patients.

US Liver Imaging Reporting and Data System Version 2017: A Systematic Review and Meta-Analysis.

Background The US Liver Imaging Reporting and Data System (LI-RADS) includes an assessment category (US-1, negative; US-2, subthreshold; and US-3, positive) and a visualization score reflecting image quality (VIS-A, no or minimal limitations; VIS-B, moderate limitations; and VIS-C, severe limitations). The US-3 and VIS-C impact patient treatment. Purpose To establish the distributions of categories and visualization scores, estimate the proportions of hepatocellular carcinoma (HCC) and overall malignancy in the US-3 category, and identify variables associated with the VIS-C score by conducting a meta-analysis.

CT features of pathologically proven smoking-related interstitial fibrosis: compared with emphysema and usual interstitial pneumonia.

Objectives: To differentiate smoking-related interstitial fibrosis (SRIF) from emphysema and usual interstitial pneumonia (UIP) using CT.

Materials And Methods: From January 2016 to October 2023, a total of 123 patients who underwent lung surgery with pathologically proven SRIF (n = 23), emphysema (n = 50), and UIP (n = 50) were included. Three radiologists retrospectively reviewed preoperative chest CTs for imaging features of centrilobular/paraseptal emphysema, multiple thin-walled cysts (MTWC), honeycombing, traction bronchiectasis, subpleural ground-glass opacity (GGO)/reticulation, and presence of smoking-related disease (SRD) and compared the CT features by subgroup.

Multisensory stimuli facilitate low-level perceptual learning on a difficult global motion task in virtual reality.

The present study investigates the feasibility of inducing visual perceptual learning on a peripheral, global direction discrimination and integration task in virtual reality, and tests whether audio-visual multisensory training induces faster or greater visual learning than unisensory visual training. Seventeen participants completed a 10-day training experiment wherein they repeatedly performed a 4-alternative, combined visual global-motion and direction discrimination task at 10° azimuth/elevation in a virtual environment. A visual-only group of 8 participants was trained using a unimodal visual stimulus.

Commentary: Volumetry for Lung Nodule Assessment.

See Article page 51.

The Inner Ear and Aging Brain: A Cross-Sectional Study of Vestibular Function and Morphometric Variations in the Entorhinal and Trans-Entorhinal Cortex.

Purpose: While the vestibular system is crucial for balance, posture, and stable vision, emerging evidence connects vestibular loss in older adults to spatial cognitive deficits. However, the specific neural pathways remain unclear. This study examines morphometric changes in the entorhinal cortex (ERC) and trans-entorhinal cortex (TEC), key regions in the vestibular spatial cognitive network, with vestibular function.

Efficacy of contrast versus non-contrast CT surveillance among patients surviving two years without recurrence after surgery for stage I lung cancer.

Contrast-enhanced chest CT (CECT) is more sensitive than non-contrast-enhanced chest CT (NCECT), but NCECT may have comparable efficacy in detecting new primary lung cancer among stage I NSCLC survivors after two years of surveillance. This study aimed to evaluate the efficacy of NCECT versus CECT for surveillance among stage I NSCLC patients surviving two years after curative resection without disease recurrence. We conducted a retrospective cohort study of patients with stage I NSCLC who underwent curative-intent lung resection between January 2009 and December 2017 using the Registry for Thoracic Cancer Surgery at the Samsung Medical Center, Seoul, Korea.

Prediction of microsatellite-stable/epithelial-to-mesenchymal transition molecular subtype gastric cancer using CT radiomics and clinicopathologic factors.

Objectives: This study aimed to develop a predictive model for the microsatellite-stable (MSS)/epithelial-to-mesenchymal transition (EMT) subtype of gastric cancer (GC) using computed tomography (CT) radiomics and clinicopathological factors.

Materials And Methods: This retrospective study included 418 patients with GC who underwent primary resection and transcriptome analysis with microarray between October 1995 and May 2008. Using preoperative CT images, radiomic features from the volume of interest in the portal venous phase images were extracted.

Deciphering the intratumoral histologic heterogeneity of lung adenocarcinoma using radiomics.

Objective: To discern highly aggressive intratumoral areas among lung adenocarcinoma (LUAD) and its impact on occult nodal metastases and the recurrence rate with radiomic analysis.

Methods: This prospective dual-institution study analyzed clinical information and high-resolution preoperative CT of 528 patients from institution A and 249 patients from institution B. We extracted radiomic features and performed pathologic evaluations for resected tumors, based on the 2020 International Association for the Study of Lung Cancer (IASLC) classification.

Artificial Intelligence Model for Detection of Colorectal Cancer on Routine Abdominopelvic CT Examinations: A Training and External-Testing Study.

Radiologists are prone to missing some colorectal cancers (CRCs) on routine abdominopelvic CT examinations that are in fact detectable on the images. The purpose of this study was to develop an artificial intelligence (AI) model to detect CRC on routine abdominopelvic CT examinations performed without bowel preparation. This retrospective study included 3945 patients (2275 men, 1670 women; mean age, 62 years): a training set of 2662 patients from Severance Hospital with CRC who underwent routine contrast-enhanced abdominopelvic CT before treatment between January 2010 and December 2014 and internal (841 patients from Severance Hospital) and external (442 patients from Gangnam Severance Hospital) test sets of patients who underwent routine contrast-enhanced abdominopelvic CT for any indication and colonoscopy within a 2-month interval between January 2018 and June 2018.

Evaluation of Convolutional Neural Networks (CNNs) in Identifying Retinal Conditions Through Classification of Optical Coherence Tomography (OCT) Images.

Introduction Diabetic retinopathy (DR) is a leading cause of blindness globally, emphasizing the urgent need for efficient diagnostic tools. Machine learning, particularly convolutional neural networks (CNNs), has shown promise in automating the diagnosis of retinal conditions with high accuracy. This study evaluates two CNN models, VGG16 and InceptionV3, for classifying retinal optical coherence tomography (OCT) images into four categories: normal, choroidal neovascularization, diabetic macular edema (DME), and drusen.

Inter-reader agreement for diagnosing thymic cysts on chest MRI in two tertiary referral centers.

Despite the substantial role of chest MRI for the diagnosis and follow-up of thymic cysts, information about inter-reader agreement and optimal MR sequences is still limited. We aimed to investigate the inter-reader agreement for diagnosing thymic cysts using various combinations of MR sequences and to assess the effect of the addition of CT on inter-reader agreement. A total of 76 anterior mediastinal lesions (≤ 30 mm) from two tertiary referral hospitals (55 from Institution A and 21 from Institution B) who underwent chest CT and contrast-enhanced chest MR were included.

Tracing Metastatic Evolutionary Patterns in Lung Adenocarcinoma: Prognostic Dissection Based on a Multi-state Model.

Purpose: After surgery for lung adenocarcinoma, a patient may experience various states of recurrence, with multiple factors potentially influencing the transitions between these states. Our purpose was to investigate the effects of clinical and pathological factors on tumor recurrence, death, and prognosis across various metastasizing pathways.

Materials And Methods: Our study group included 335 patients with all demographic and pathologic data available who underwent surgical resection for lung adenocarcinoma for more than 10 years.

Automatic detection of fluorescently labeled synapses in volumetric in vivo imaging data.

Synapses are submicron structures that connect and enable communication between neurons. Many forms of learning are thought to be encoded by synaptic plasticity, wherein the strength of specific synapses is regulated by modulating expression of neurotransmitter receptors. For instance, regulation of AMPA-type glutamate receptors is a central mechanism controlling the formation and recollection of long-term memories.

Comparative Analysis of Automated and Handheld Breast Ultrasound Findings for Small (≤1 cm) Breast Cancers Based on BI-RADS Category.

: This study aimed to compare ultrasound (US) findings between automated and handheld breast ultrasound (ABUS and HHUS, respectively) in small breast cancers, based on the breast imaging reporting and data system (BI-RADS) category. : We included 51 women (mean age: 52 years; range: 39-66 years) with breast cancer (invasive or DCIS), all of whom underwent both ABUS and HHUS. Patients with tumors measuring ≤1 cm on either modality were enrolled.

Role of radiofrequency ablation in the treatment of symptomatic distant metastasis of thyroid cancer.

Objective: To evaluate the effectiveness and safety of radiofrequency ablation (RFA) for the treatment of symptomatic distant metastasis of differentiated thyroid carcinoma.

Materials And Methods: The medical records of 12 patients who underwent RFA for the palliative treatment of 18 symptomatic distant metastases from thyroid cancer between January 2008 and December 2020 were analyzed. All patients were assessed for their degree of discomfort and underwent periodical evaluations as outpatients, including clinical examination, imaging, and serologic markers.

Radiation exposure in concurrent abdominoplevic and chest CT Scans: an analysis of overlap and clinical impact.

This study investigated the additional radiation exposure, influencing factors, and clinical significance of overlapping-axis coverage in abdominopelvic CT scans performed consecutively after same-day chest CT scans. Data from 761 patients were analyzed, with measuring the total and overlapping-axis coverage of the portal venous phase in abdominopelvic CT scans. The average overlapping portion was 33.

Radiofrequency Ablation for Recurrent Thyroid Cancers: 2025 Korean Society of Thyroid Radiology Guideline.

Radiofrequency ablation (RFA) is a minimally invasive treatment modality used as an alternative to surgery in patients with benign thyroid nodules, recurrent thyroid cancers (RTCs), and primary thyroid microcarcinomas. The Korean Society of Thyroid Radiology (KSThR) initially developed recommendations for the optimal use of RFA for thyroid tumors in 2009 and revised them in 2012 and 2017. As new meaningful evidence has accumulated since 2017 and in response to a growing global interest in the use of RFA for treating malignant thyroid lesions, the task force committee members of the KSThR decided to update the guidelines on the use of RFA for the management of RTCs based on a comprehensive analysis of current literature and expert consensus.