Risk stratification systems (RSSs) have had an increasing role in standardizing thyroid ultrasound reports. The VA Northern California Healthcare System (VA-NCHCS) Radiology department adopted the American College of Radiology Thyroid Imaging Reporting and Data System (TI-RADS) in 2018. We aimed to assess what effect the adoption of TI-RADS at VA-NCHCS had on thyroid surgical practices. A 10-year retrospective review of the VA corporate data warehouse was completed (approximately 5 years prior and 5 years after universal adoption of TI-RADS) (i.e: 1/1/2013-7/1/2018 and 7/2/2018-12/30/2023). Using CPT and diagnosis codes, data were collected on all thyroid surgeries, including demographics, type of surgery performed, final pathology, staging of malignancy, and any incidental findings. A two-sample t-test with equal and unequal variances was used for comparative statistics. 3985 patients (1921 PRE-TIRADS vs. 2064 POST-TIRADS) and 7908 thyroid ultrasounds (3411 vs. 4497) were identified. 2859 FNAs were performed (1245 vs. 1614). One hundred and ninety-three surgeries (96 vs. 97) were performed with a decreasing trend in surgeries for benign pathology (56 vs. 45) and an increasing trend in surgeries for malignancy (39 vs. 51). We identified an increase in partial thyroidectomy surgeries for cancer diagnoses (11 vs. 18). Finally, there was a significant decrease in total thyroidectomies performed for benign pathology (30 vs. 13, p = 0.02). After the institution of TIRADs at our single institution, there was a dramatic increase in the number of ultrasounds and FNAs performed, despite near stable thyroid surgical numbers. There was a significant trend towards less-invasive surgical practices.

Comparison of cone beam CT and conventional CT guided pediatric spine biopsies.

Renal-clearable organic NIR-II dye cluster for non-invasive ureteral imaging.

The 2021 World Health Organization Classification of Tumours of the Central Nervous System, 5th edition (WHO CNS5) reorganized adult-type diffuse gliomas into three integrated tumor types-astrocytoma, IDH-mutant (AST); oligodendroglioma, IDH-mutant and 1p/19q-codeleted (ODG); and glioblastoma, IDH-wildtype (GBM)-and introduced molecular criteria that allow histologically lower-grade IDH-wildtype astrocytic tumors to be diagnosed as GBM (so-called "molecular" GBM). Although molecular genetic information has become central to glioma diagnosis, preoperative imaging-based prediction of tumor type remains essential for guiding surgical strategy, the choice between maximal safe resection and diagnostic biopsy, and treatment planning before final integrated diagnosis. The recent INDIGO trial, which demonstrated efficacy of the IDH1/2 inhibitor vorasidenib in residual grade 2 IDH-mutant glioma, has further increased the importance of preoperative imaging assessment of IDH mutation status. This mini-review summarizes the current role of imaging in adult-type diffuse gliomas in the WHO CNS5 era. First, we review imaging differentiation between AST and ODG, including the T2-fluid-attenuated inversion recovery (FLAIR) mismatch sign and its partial form, classic features supporting ODG such as coarse calcification and cortical-subcortical location, and newer biomarkers including the cortical high-flow sign on arterial spin labeling, subcortical FLAIR signal drop, and 1H-MR spectroscopy findings such as 2-hydroxyglutarate and cystathionine. Second, we describe imaging features of "molecular" GBM, including its frequently infiltrative, poorly enhancing appearance and longitudinal histologic grade progression. Third, we discuss the implications of cIMPACT-NOW Updates 8-11 for neuroradiologic diagnosis. In the WHO CNS5 era, imaging plays a central role in supporting integrated diagnosis and prioritizing appropriate molecular testing.

High frequency, broadband ultrasonic transducers are pivotal for precise superficial vascular imaging and pathological diagnosis due to their superior spatial resolution. Achieving high frequency detection fundamentally necessitates reducing the piezoelectric layer thickness to the micrometer scale. For ultrathin ferroelectric polymers, this physical scaling significantly amplifies the "surface dead layer" effect, where inherent low crystallinity and disordered dipole orientation severely suppress polarization switching, resulting in a drastic deterioration of device sensitivity. To resolve the trade-off between thickness and performance, we propose a synergistic enhancement strategy combining plasma surface modification with Curie temperature gradient polarization (CT-GP). Plasma treatment is employed to introduce polar functional groups to reactivate the inert surface layer, while the CT-GP process leverages the cooperative effects of thermal activation and electric fields near the Curie temperature to induce robust molecular chain rearrangement and domain stabilization. The β phase crystallinity of the 5 μm-thick film is elevated to 33.01%, with a piezoelectric coefficient (d33) of 20.6 pC N-1. Focused transducers fabricated from these optimized films exhibit outstanding acoustic performance, characterized by a center frequency of 39.5 MHz and a -6 dB bandwidth of 54 MHz. The high signal-to-noise ratio (19 dB) in vivo imaging of murine microvasculature was successfully demonstrated, achieving lateral resolutions of 39.4 μm. This work elucidates the physical mechanism by which surface layers limit the performance of ultrathin films and provides a new theoretical and technical pathway for the development of high-resolution vascular imaging and flexible acoustic devices.

Treatment for excessive gingival display, commonly known as gummy smile, remains challenging. This cross-sectional study investigates the clinical use of soft tissue CBCT (ST-CBCT) to measure the hard and soft tissues in the dento-gingival unit to diagnose and plan treatment for excessive gingival display. The dento-gingival complex of maxillary anterior teeth was investigated, including gingival thickness, alveolar bone thickness, and supracrestal tissue attachment. A detailed clinical treatment sequence of the therapeutic journey of a patient with altered passive eruption is presented to illustrate the clinical application of CBCT, from diagnosis to the final outcome, using Digital Smile Design. Thirty patients with altered passive eruption were evaluated. The mean distance from the gingival margin to the bone crest was 4.2 ± 1.1 mm. The mean gingival thickness was 1.1 ± 0.3 mm, and crestal labial bone thickness was 1.0 ± 0.4 mm. The majority presented thick gingiva (≥ 1 mm, 63.4%), and nearly half of all teeth (48%) showed thick crestal bone (≥ 1 mm). Male participants demonstrated a higher prevalence of thin crestal bone than female participants (66.7% vs 49.2%; P = 0.007). Contralateral teeth exhibited statistically significant differences in the distance from the cementoenamel junction to the bone crest, soft tissue thickness, and bone thickness. The dento-gingival unit presented inter- and intra-individual variability. Tomographic diagnosis, classification, and treatment planning of altered passive eruption should be conducted on a tooth-by-tooth basis for higher surgical precision and predictability, ultimately improving patient care. Soft tissue CBCT offers a comprehensive 3D overview of the soft and hard tissues in the dento-gingival unit.

Children centered care status after implementation: What happens when the spotlight and hype are turned off?

Intrathyroid thymic carcinoma (ITTC) is an exceptionally rare primary thyroid malignancy with thymic epithelial differentiation, generally characterized by relatively indolent biological behavior. However, significant knowledge gaps persist in ITTC diagnosis, and a consensus on an optimal treatment strategy for ITTC is lacking. This review synthesizes the current knowledge on ITTC, focusing on its clinicopathological features, molecular landscape, prognostic factors, and therapeutic approaches, to raise clinical awareness of this rare entity and guide individualized management. ITTC predominantly affects adults, with a slight female predilection. Pretreatment diagnosis in imaging and cytology of ITTC is challenging. Histopathologically, ITTC is indistinguishable from thymic squamous cell carcinoma (TSCC), and no specific molecular alterations have been identified to date. Lymph node metastasis and the presence of symptoms at diagnosis serve as adverse prognostic indicators in ITTC patients. While surgery remains the priority treatment for ITTC, patients' responses to adjuvant radiotherapy and/or chemotherapy are variable, underscoring the need for further investigation into the role of systemic antineoplastic therapies. Notably, checkpoint inhibitors targeting PD-L1 or PD-1 represent a promising avenue for ITTC patients with advanced disease.

Artificial intelligence (AI) technology is developing rapidly in the medical field, particularly showing significant clinical value in the diagnosis and management of diseases in preterm infants. Preterm infants have immature organ development and a high incidence of complications; early prediction, accurate diagnosis, and individualized treatment pose major clinical challenges. With its powerful data processing and pattern recognition capabilities, AI provides new solutions for the diagnosis and management of diseases in preterm infants. It is now widely applied to the prediction of complications, imaging diagnosis, optimization of treatment plans, and prognostic evaluation for preterm infants, significantly improving diagnostic and therapeutic efficiency and accuracy. However, limitations remain in the clinical application, including data quality, model interpretability, and ethical issues. This article reviews the research progress of AI in the diagnosis and management of diseases in preterm infants, discusses its application advantages, challenges, and future directions, aiming to provide a reference for clinical practice and related research.

Intravenous thrombolysis (IVT) for suspected acute ischemic stroke is initiated before definitive imaging confirmation, resulting in treatment of patients later classified as MRI confirmed infarction (MRI +), MRI negative ischemia (MRI -), or stroke mimics. Characterization of MRI - andmimic presentations may support assessment under uncertainty. We conducted a retrospective cohort study using a prospectively maintained stroke registry at a comprehensive stroke center between (2019-2025). Consecutive patients treated with IVT within 4.5h of symptom onset who underwent brain MRI within 72h were included and categorized by diffusion-weighted imaging and final adjudicated diagnosis as MRI + , MRI - ischemia, or stroke mimics. Among 716 patients treated with IVT, 523 (73.0%) had MRI-confirmed infarction, 119 (16.6%) had MRI-negative ischemia, and 74 (10.3%) were stroke mimics. Compared with MRI + patients, MRI - and mimic groups were younger, more often female, and had a lower vascular risk burden, including atrial fibrillation (P = 0.0002) and hypertension (P = 0.0009). Both groups more frequently presented with minor deficits (NIHSS ≤ 5, P < 0.0001), while moderate-to-severe stroke was less common (P < 0.0001). Stroke mimics had fewer vascular risk factors than MRI - ischemia and were most commonly attributed to migraine, vestibular disorders, seizures, or functional neurologic conditions. Hemorrhagic transformation and in-hospital mortality occurred only in MRI + patients, while MRI - and mimic groups more often discharged home (P < 0.0001). MRI negative ischemia and stroke mimics are distinct subgroups among thrombolysed patients, presenting with lower stroke severity and vascular risk. Recognition of these patterns may aid evaluation of mild or atypical presentations while supporting IVT use.

PIWI-interacting RNAs (piRNAs) are well-recognized as promising diagnostic biomarkers for cancer, yet their quantitative detection remains a great challenge owing to their short sequences, low cellular abundance, high degradation susceptibility, and significant sequence homology among family members. Herein, we developed an ultrasensitive and highly specific biosensor for the detection of piRNA-54265-a colorectal cancer (CRC)-associated piRNA-by integrating strand displacement amplification (SDA) with the CRISPR/Cas12a system. After systematic optimization, the biosensor exhibited remarkably enhanced amplification efficiency and target specificity, achieving an ultra-low limit of detection (LOD) of 57.54 aM for piRNA-54265. Notably, this CRISPR-SDA platform enabled accurate discrimination of CRC cells from other cancer cells via high-fidelity intracellular imaging of piRNA-54265 and also realized reliable detection of the target in complex biological matrices with favorable recovery. Benefiting from its simple sequence design, user-friendly operation, and isothermal reaction conditions, the developed biosensor not only overcomes the inherent technical bottlenecks in piRNA detection but also shows great potential for applications in cellular imaging and early clinical diagnosis of CRC.

Advances in research on radiopharmaceuticals targeting NTSR1.

Recent advances in deep learning have significantly improved the accuracy and efficiency of disease classification in digital pathology. Early diagnosis and precise classification of histopathological images are crucial for enabling timely treatment and improving therapeutic outcomes. Oral squamous cell carcinoma (OSCC) is one of the most common malignancies in the oral cavity, with manual histopathological examination serving as the gold standard for diagnosis-though it is time-consuming and subject to observer variability. This study investigates the performance of four deep learning convolutional neural network (CNN) models-ResNet50 (residual blocks), DenseNet201 (dense connectivity), EfficientNetB0 (compound scaling), and ConvNeXt_Tiny (transformer-based convolutions)-for binary classification (benign vs. carcinoma) of 10,000 histopathological images. Among the models, EfficientNetB0 achieved the highest accuracy of 97.6% and an ROC-AUC score of 0.9963, demonstrating superior generalization and discriminative power. ConvNeXt_Tiny followed with an accuracy of 95.92%, DenseNet201 with 86.08%, and ResNet50 with the lowest accuracy of 71.52%. The comparative analysis underscores the advantages of modern CNN architectures over traditional residual networks, supporting the integration of deep learning models into diagnostic frameworks for improved detection of oral squamous cell carcinoma.

Deep learning (DL) has driven major progress in medical imaging diagnosis. However, its effectiveness is often limited by the scarcity of large annotated datasets and the poor generalization of models to small, out-of-distribution (OOD) data. Self-supervised learning (SSL) and transfer learning offer promising solutions: SSL enables representation learning from unlabeled data via pretext tasks, while transfer learning helps adapt models to new domains with limited labeled data. In this study, we evaluate SSL-based strategies for detecting and segmenting clinically significant prostate cancer (csPCa) in MRI. We investigate the impact of key design decisions-including model architectures, pretext tasks, contrastive learning methods, and downstream tasks-using one medium-sized pre-training dataset (PI-CAI) and two small OOD target datasets: Prostate158 and ChiPCa. We propose a three-stage training pipeline that includes SSL, supervised pre-training, and a final fine-tuning on the target small labeled dataset.Results show that our proposed full three-stage training pipeline achieves the most consistent performance in both detection and segmentation on Prostate158, whose csPCa area distribution is closer to the pre-training dataset. In contrast, for ChiPCa, whose csPCa distribution differs from the pre-training dataset, the full strategy is the best for detection but suboptimal for segmentation, where partial training stages can provide better results. In general, either UNETR or UNet can serve well for detection, but UNet architecture reports consistently better results for segmentation. These findings provide practical guidance on when multi-stage SSL pipelines are most beneficial and how dataset similarity and architectural choice influence prostate segmentation performance.

The reported prevalence of feline idiopathic epilepsy (IE) and presumptive imaging diagnoses based on magnetic resonance imaging (MRI) varies depending on factors such as differences between primary care versus referral study populations. This retrospective, imaging-based study reviewed MRI data from cats with suspected epileptic seizures. Cases were categorised as follows: no lesions detected (IE, referring to cats aged 6 months‒7 years with recurrent epileptic seizures, and epilepsy or epileptic seizure of unknown aetiology [EuA] [i.e., cats not fulfilling IE criteria]) and structural lesion(s) detected (SL). Presumptive imaging diagnoses were classified according to the following aetiologies: presumptive intra-axial/extra-axial neoplasia, inflammatory, vascular, congenital, traumatic, metabolic/toxic and degenerative. Of 432 MRIs, 39% revealed SL, whereas 61% showed no structural lesions (of which 47% of cases were classified as IE and 53% were classified as EuA). Among cats with SL, presumptive imaging-based diagnoses included inflammatory diseases (25%), extra-axial neoplasia (19%), metabolic/toxic aetiologies (12%), congenital disorders (10%), lesions of unknown relevance (9%), intra-axial neoplasia (7%), trauma (5%), suspected hippocampal necrosis (5%), vascular events (4%), thiamine deficiency (2%) and degenerative diseases (2%). This imaging-based study lacked histopathological confirmation and comprehensive clinical information. Nearly two-thirds of MRIs involving cats with suspected epileptic seizures showed no structural brain abnormalities.

Paid Family and Medical Leave Policies in Academic Radiology and Radiation Oncology Departments: A SCARD and SCAROP Survey.

Allergic bronchopulmonary aspergillosis (ABPA) develops in patients through type I or type III hypersensitivity reactions to the filamentous fungi Aspergillus. There is a wide spectrum of radiological presentations of ABPA, including fleeting alveolar opacities, centrilobular nodules, bronchiectasis, mucoid impaction resulting in bronchocele, cavitation, and pulmonary fibrosis. This study aims to identify the pattern of radiological presentation in our community and its implications in the clinical diagnosis of the disease. We conducted a descriptive, cross-sectional study. The study was conducted at the Department of Radiology, Combined Military Hospital, Bahawalpur, between 4th April 2021 and 3rd October 2021. A total of 85 asthmatic patients between the ages of 18 and 60 years with a clinical diagnosis of ABPA reporting for high-resolution computed tomography (HRCT) were included. Patients with bronchiectasis other than ABPA, such as tuberculosis, foreign body, recurrent aspiration, and malignancy, were excluded. All the patients underwent an HRCT scan of the chest. In this study, the frequency of different radiological presentations of ABPA in adult asthmatic patients was as follows: mucus plug in 47 (55.29%) patients, centrilobular nodules in 49 (57.65%) patients, central bronchiectasis in 35 (41.18%) patients, and patchy air space consolidation in 37 (43.53%) patients. This study concluded that centrilobular nodules are the most common radiological presentation of ABPA in adult asthmatic patients, followed by the mucus plug, patchy air space consolidation, and central bronchiectasis.

Radiation safety competence is essential for nursing professionals to ensure safe practices in radiology settings. However, nursing academic programs often fail to adequately address this critical area, leaving notable deficiencies in knowledge and preparedness that can hinder the implementation of radiation safety measures. This study aimed to assess radiation safety competence among final-year nursing students at Jazan University, Saudi Arabia, and to examine associated attitudes and perceived preparation for radiology-related practice. A cross-sectional study was carried out involving final-year nursing students in Saudi Arabia. Data were gathered through a structured survey designed to evaluate radiation safety competencies, attitudes, and perceptions regarding the adequacy of academic preparation and readiness for work in radiology departments after graduation. The data were analyzed using descriptive and inferential statistical methods. The study included 258 nursing students, the majority of whom were female (68.60%). Among the participants, 40.70% considered their academic preparation for radiology to be adequate, and only 20.93% felt prepared for work in radiology post-graduation. The overall competence level was moderate, with a mean score of 3.35 ± 1.03, and attitudes toward radiation safety were generally positive, averaging 3.88 ± 1.16. Students who perceived their academic preparation as sufficient or reported feeling ready for radiology work achieved significantly higher competence scores (p = 0.032 and p = 0.026, respectively) compared to those who felt unprepared or uncertain. The lowest rated items were observed in foundational knowledge areas, including understanding ionizing radiation types and sources and explaining the health risks associated with ionizing radiation (37.21%). Attitude toward radiation safety emerged as the most influential predictor of the perceived competence (p < 0.001). Final-year nursing students rated their radiation safety competence as moderate, with positive attitudes being strongly associated with higher self-perceived competence. Nursing curricula should incorporate a dedicated radiation safety module with supervised clinical orientation in imaging areas, simulation-based training, and competence-based assessment to strengthen foundational knowledge and readiness for radiology-related practice.

This study intends to develop a scoring model for using oral contrast-enhanced ultrasound to aid in the imaging diagnosis of gastric cancer. Patients with a pathological diagnosis of gastric lesions who underwent oral contrast-enhanced ultrasound examination in our hospital from September 2019 to December 2021 were included. The age, gender, and ultrasound image characteristics of the patients were analysed, and a scoring model was established. The area under the receiver operating characteristic curve was used to evaluate the model's discriminative performance, and the Hosmer-Lemeshow test was used to assess its goodness-of-fit. A total of 66 patients were included in this study. Pathological examination confirmed malignant lesions in 9 patients and benign lesions in 57. The variables age, male sex, gastric wall thickness, loss of wall stratification, ulceration, and the presence of blood flow signals were used to establish a scoring model. A score greater than 4.65 was considered indicative of gastric cancer. The model demonstrated discriminative ability, with an area under the receiver operating characteristic curve of 0.92 (95% confidence interval, 0.83-0.97, p < 0.0001). The Hosmer-Lemeshow test indicated good calibration (p > 0.05). This scoring system using oral contrast-enhanced ultrasound exhibited good diagnostic capability for gastric cancer and thus may be useful for screening. It will still require subsequent investigation of its reliability through prospective studies.

Schlaegel lines: History, etiology, multimodal imaging, and differential diagnosis of curvilinear streaks in chorioretinal disorders.