British Journal of Radiology最新文献

Endocrine hypertension is an uncommon but treatable cause of secondary hypertension. It results from excessive hormone production by the endocrine glands or due to ectopic hormone production. The causes of abnormal hormonal production can be congenital or acquired. Specific syndromes can also predispose to the development of endocrine hypertension. Extensive catecholamine production can occur due to pheochromocytomas and paragangliomas. Excessive aldosterone secretion by the adrenal cortex commonly occurs due to idiopathic (bilateral) adrenal hyperplasia or aldosterone-producing adrenal adenomas. Excessive cortisol production can occur secondary to abnormalities in the adrenal gland, the pituitary gland, or ectopic hormone production, or it can be caused by exogenous steroid intake. Other endocrine conditions that can lead to hypertension include acromegaly, primary hyperparathyroidism, hyperthyroidism, and hypothyroidism. Imaging plays a vital role in diagnosing the cause of endocrine hypertension, leading to appropriate management. The clinical presentation and laboratory investigations serve as a guide to the appropriate imaging investigation that needs to be performed to confirm a diagnosis.

Objectives: To develop and test a convolutional neural network model for automated segmentation of complicated cystic renal masses (cCRMs) on MRI.

Methods: This multicenter retrospective study analyzed 210 cCRMs between October 2019 and May 2021, divided into training/internal validation (n = 150, Institution 1) and test sets (n = 60, Institutions 2-4). Comparative 3D V-Net and U-Net models were developed across seven MRI sequences (T2-weighted, diffusion-weighted, apparent diffusion coefficient maps, unenhanced T1-weighted, and enhanced corticomedullary, nephrographic, and excretory phases images). A total of 14 models were developed, and seven pairwise comparisons were performed between the 3D V-Net and U-Net models. Segmentation performance was evaluated using Dice similarity coefficient (DSC) and Hausdorff distance (HD), with subgroup analysis of small cCRMs (≤40mm).

Results: In the test set, the excretory-phase V-Net (EPV-Net model) showed the highest DSC, and perform better than the corresponding U-Net (EPU-Net model) across all cCRMs (DSC: 0.74 ± 0.05 vs 0.70 ± 0.06, P < 0.001; HD: 27.41 ± 7.44 mm vs 39.18 ± 11.07 mm, P < 0.001) and the 35 small cCRMs subgroup (DSC: 0.74 ± 0.05 vs 0.70 ± 0.06, P < 0.001; HD: 27.48 mm ± 6.32 vs 38.72 ± 10.69 mm, P < 0.001).

Conclusions: The 3D EPV-Net model demonstrated good segmentation accuracy, even for small lesions, supporting its clinical utility for cCRMs evaluation.

Advances in knowledge: This automated approach may streamline workflow compared to manual segmentation in cCRMs assessment.

Objectives: We assessed if there was disparity between qualified statisticians and other researchers regarding the level of statistical assistance deemed necessary to support radiological research.

Methods: We categorised 50 consecutive, eligible original research articles published in an indexed imaging journal (European Radiology) 2024, according to authors' statements regarding statistical support, declared in the "statistics and biometry" section. Two reviewers extracted data related to study design, statistical methods, and analysis. Two medical statisticians categorised each study as presenting "complex" statistical methods or not and then compared this with authors' own assessment of statistical complexity, stated in the published article. We performed descriptive analyses.

Results: Most studies were observational (49, 98%) and retrospective (38, 76%). 35 (70%) studies were diagnostic, 7 (14%) prognostic, and 6 (12%) mixed. Malignancy was the most frequent topic (29 studies, 58%), and MRI the most frequent modality (35 studies, 70%). We deemed most studies (33, 66%) presented complex statistical methods. Of these, 13 studies (26% overall) declared that "no complex statistical methods were necessary for this paper". However, 10 of these employed hypothesis testing, frequently using multiple methods; 9 employed agreement and/or reliability analyses; all presented accuracy measures; 11 (85%) presented a regression model.

Conclusion: We found that approximately one quarter of original research articles published in our sample stated that "no complex statistical methods were necessary", but then presented complex analyses.

Advances in knowledge: Some radiological researchers may underestimate the complexities of statistical analysis and requirement for specialist statistical support, which risks inappropriate analyses and misleading results.

Objectives: This study investigated gray and white matter alterations and their association with motor and cognitive symptoms in early-stage Parkinson's disease (PD).

Methods: Thirty-one early-stage PD patients and thirty matched healthy controls underwent multimodal MRI (VBM, DTI) and comprehensive clinical/neuropsychological assessments. We assessed gray matter atrophy, white matter microstructure, and caudate-cortical connectivity.

Results: PD patients showed selective deficits in memory (FCSRT total recall, p-FDR = 0.014) and processing speed (SDMT, p-FDR = 0.025). VBM revealed bilateral caudate atrophy (left, p-FDR = 0.024; right, p-FDR = 0.026). DTI demonstrated widespread microstructural alterations in corpus callosum and major association tracts. Disease duration negatively correlated with corpus callosum streamline counts (superior parietal p = 0.02; posterior parietal p = 0.004). UPDRS negatively correlated with FA in occipital (p = 0.002) and temporal (p = 0.0017) corpus callosum segments. Reduced caudate-cortical streamline density in frontal regions correlated with UPDRS/FCSRT scores; caudate-cingulum streamlines correlated with MMSE attention/calculation.

Conclusions: Our findings suggest early functionally relevant degeneration of fronto-caudate and interhemispheric pathways in PD. These structural changes correlate with specific cognitive and motor impairments, and are candidate imaging biomarkers for early PD progression and/or cognitive vulnerability.

Advances in knowledge: This is the first tractography study to evaluate connectivity between the caudate nuclei and different frontal lobe regions, unveiling specific white matter alterations in early Parkinson's disease. Our findings suggest that caudate atrophy, though not directly correlated with clinical variables, may underlie or result from impaired caudate-cortical connectivity, potentially accounting for some of the multifaceted PD symptoms.

Objective: To correlate response evaluation after neoadjuvant chemotherapy (NAC), assessed by magnetic resonance imaging (MRI) and pathology, with disease-free survival (DFS) in breast cancer patients, according to immunophenotype.

Methods: Single-center, IRB-approved retrospective cohort study included consecutive breast cancer patients who underwent NAC and preoperative breast MRI. Pathologic response was evaluated using the residual cancer burden (RCB) system, with pathological complete response (pCR) defined as the absence of invasive carcinoma. Radiological complete response (rCR) was defined as the absence of abnormal enhancement on MRI. The Kaplan-Meier method estimated DFS and Cox regression analysis calculated hazard ratios (HR).

Results: 571 patients were included (mean age 46 years, range 26-90). The most common immunophenotype was Luminal (42.3%), followed by triple-negative (TNBC, 31.5%) and HER2-overexpressed (26.3%). Radiological and pathological responses were concordant in 71.5%. Overall, 35.2% achieved rCR and 37.5% achieved pCR. DFS curves did not differ significantly according to radiologic-pathologic response combinations in Luminal or HER2 groups (LogRank p = 0.505 and p = 0.257). In the TNBC group, patients without pCR or rCR had significantly worse DFS compared to those achieving either response (LogRank p = 0.001). Cox regression revealed that TNBC patients with both non-rCR and non-pCR had a markedly higher risk of recurrence or death (HR 7.728; 95%CI 2.696-22.149; p < 0.001).

Conclusions: Integrating MRI and pathological response assessments after NAC may enhance risk stratification and prognostication, especially in triple-negative breast cancer.

Advances in knowledge: Patients with both non-rCR and non-pCR have significantly worse DFS, underscoring the prognostic value of combining imaging and pathological findings, particularly in TNBC.

Coronary computed tomography angiography (CCTA) has evolved into a key non-invasive tool for evaluating coronary artery disease, offering high sensitivity, detailed anatomical visualization, and strong prognostic value. Current Society of Cardiovascular Computed Tomography guidelines recommend CCTA as a first-line test for symptomatic patients, while limiting its use in asymptomatic individuals to select high-risk cases. Advantages in a screening context include early detection of subclinical atherosclerosis, prognostic assessment through high-risk plaque features, and facilitation of personalized preventive strategies. However, widespread screening faces challenges: procedural complexity, contrast and radiation exposure, psychological impact, and economic cost. Emerging integration of artificial intelligence promises to enhance efficiency, automate plaque quantification, and enable individualized risk prediction, potentially improving cost-effectiveness and clinical adoption. Future validation through randomized controlled trials and real-world data is needed to confirm the impact of CCTA-based screening on cardiovascular event reduction, healthcare resource use, and patient quality of life.

Objectives: We sought to identify factors associated with prognosis and bleeding in patients with melanoma brain metastases(BM).Objectives were median overall survival (mOS [months]) and bleeding incidence.

Methods: We conducted a retrospective analysis of patients receiving SRS at our center 11/1511/23.Analysis was performed on Prism 10.1.1.Extraction from electronic medical records was undertaken by authors, with local R&D approval(NEU012).

Results: 81 patients were evaluable. 119 treatment courses were delivered. There were no bleeding events (BE) in the first 7 days , 1 within 28 days(0.8%) and 19 within 90 days(16%).7.6%(N = 9) died within 90 days and 25.2%(N = 30) died within 6 m. There were no deaths within 30 days or related to treatment.mOS was 17.6 m(95% CI 9.20-35.05).Significantly inferior survival outcomes were observed for patients with elevated lactate dehydrogenase(LDH),poor performance status(Karnofsky performance status [KPS]),higher total treated intracranial volume(GTV) and total number of BM.mOS of patients with a normal LDH was 37.0 m vs 5.2 m for those with LDH >ULN(HR 4.40, P<.0001).This was also true on multivariable analysis including KPS, BM number and BM size(HR 3.75 95%CI 1.94-7.30, p = <0.0001).For patients with KPS ≥90 mOS was 35.0 m vs 7.7 m for KPS ≤80(HR 2.55, P<.0004).This was significant using the multivariable analysis described above(HR 2.12 95%CI 1.123-3.948, p = 0.0181).

Conclusions: Despite theoretically high risk of bleeding after SRS in MM BM, incidence of bleeding in our cohort was low.mOS was comparable to historical controls of 16-23 months.

Advances in knowledge: We novelly performed univariate and multivariate analysis demonstrating poor survival outcomes in patients with high LDH, poor performance status and larger brain metastases (both by BM size and number).

Objectives: To determine the feasibility and accuracy of photon-counting detector (PCD)-CT for iron and fat quantification in the myocardium.

Materials and methods: Cylindrical tubes were filled with porcine myocardium and iron-citrate with iron concentrations of 0-20mg Fe/g. Dilution series were prepared with myocardium and iron (no-fat probes) and with 5%-fat (fat probes). The tubes were positioned in a chest phantom and were scanned with a calcium-scoring protocol on a PCD-CT. A re-parameterized three-material decomposition was used to separate iron and fat from myocardium.

Results: On virtual monoenergetic images, attenuation increased linearly with iron concentrations in both fat and no-fat probes. In no-fat probes, linear regression yielded a slope of 1.2HU/(mgFe/g) with an intercept of 35.8HU (R2=0.964). In the fat probes, the slope was similar at 1.1HU/(mgFe/g), while the regression line shifted downwards by 6.1HU with an intercept of 29.6HU (R2=0.985). Iron maps separated fat from iron with calculated median fat-fractions of 4.85 in the fat and 0.90 in the no-fat probes. In iron images, attenuation increased linearly with increasing iron concentrations, with similar slopes between fat and no-fat probes and negligible differences in the intercept.

Conclusion: Experimental evidence indicates the feasibility and accuracy of PCD-CT for iron and fat quantification in the myocardium. Iron-specific three-material decomposition eliminates the confounding effect of fat on myocardial iron quantification.

Advances in knowledge: This study highlights the value of dual-energy CT with three-material decomposition for quantifying iron and fat in the myocardium. Thus, CT could serve as alternative for the current reference standard MRI.

Objectives: To establish typical values (TVs) for air kerma at the reference point (Ka, r, mGy) and fluoroscopy time (minutes) in four interventional procedures: vascular angiography (pelvic/lower limbs), vascular angioplasty (pelvic/lower limbs), coronary angiography and angioplasty. The study also aimed to assess the influence of body mass index (BMI) and identify other clinical factors associated with radiation exposure.

Methods: A retrospective analysis of 2,200 patient examinations was performed at a large hospital. Demographic, anthropometric, dosimetric data were extracted from fluoroscopy equipment reports and electronic medical records. TVs were calculated overall and stratified by procedure type and BMI category.

Results: Variation in TVs was observed across procedure types and BMI groups. Ka, r values ranged from 185.0 mGy (underweight) to 796.5 mGy (class III obesity), with an overall TV of 413 mGy. Fluoroscopy time demonstrated a correlation with radiation dose. Age and sex influenced exposure but to a lesser degree. Relying on aggregated TVs may mask clinical differences, leading to under- or overestimation of patient dose.

Conclusions: Tailoring TVs to patient BMI and procedure type enhances dose assessment accuracy, supporting optimized radiation protection strategies in clinical practice.

Advances in knowledge: This study demonstrates that anthropometric characteristics have measurable impact on radiation dose indicators in interventional radiology and provides BMI-stratified TVs based on a clinical dataset. Although multiple factors influence radiation exposure, including procedural complexity and operator experience, anthropometry remains an independent contributor. The TVs presented here support protocol optimization and contextualization of local practice.