British Journal of Radiology

OBJECTIVE: To determine whether a more conservative Denver criterion set could reduce unnecessary CT angiography (CTA) studies when screening for blunt cerebrovascular injury (BCVI) following blunt trauma. METHODS: Following ethics approval, a retrospective chart review of 447 consecutive patients undergoing emergency CTA at two large teaching hospitals was conducted to determine presence of risk factors for each Denver criterion set. Imaging studies of adults conducted between January 2016 and June 2020 containing sufficient clinical information for accurate classification were included in the study...

OBJECTIVES: Ruptured carotid plaque causes stroke, but differentiating rupture-prone necrotic core from fibrous tissue with CT is limited by overlap of X-ray attenuation. We investigated the ability of CT-derived plaque maps created from ratios of plaque/contrast attenuation to identify histologically proven vulnerable plaques. METHODS: Seventy patients underwent carotid CT angiography and carotid endarterectomy. A derivation cohort of 20 patients had CT images matched with histology and carotid plaque components attenuation defined...

OBJECTIVE: To evaluate the clinical feasibility of T1 mapping and multimodel diffusion-weighted imaging (DWI) for assessing the histological type, grade, and lymphovascular space invasion (LVSI) of cervical cancer. METHODS: Eighty patients with cervical cancer and 43 patients with a normal cervix underwent T1 mapping and DWI with 11 b-values (0-2000 s/mm2 ). Monoexponential, biexponential, and kurtosis models were fitted to calculate the apparent diffusion coefficient (ADC), pure molecular diffusion (D), pseudo-diffusion (D*), perfusion fraction (f), mean diffusivity (MD), and mean kurtosis (MK)...

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ChatGPT is a newly developed technology created by the OpenAI company. It is an artificial-intelligence-based large language model (LLM) and able to generate human-like text. The potential roles of ChatGPT in clinical decision support and academic writing have led to intense criticism of this technology in the scientific community. Therefore, radiologists also need to be familiar with LLMs such as ChatGPT.

OBJECTIVE: To investigate the feasibility of an ultra-low radiation dose and contrast volume protocol using third-generation dual-source (DS) CT for transcatheter aortic valve implantation (TAVI) planning with coronary artery disease (CAD) assessment, coronary artery calcium score (CACS) and aortic valve calcium score (AVCS) quantification and to evaluate their relationship with TAVI outcome. METHODS: In this retrospective study were selected 203 patients (131 males, 79...

OBJECTIVES: To investigate whether preoperative ultrasound elastography (USE) can be used to predict aggressive features of solitary papillary thyroid carcinomas (PTCs). METHODS: Clinical and USE indices were retrospectively analyzed in 487 patients with surgically confirmed solitary PTCs. The patients were grouped per aggressive features on pathologic testing. Univariate and binary logistic regression analyses were performed to explore independent risk factors of aggressive features...

OBJECTIVE: Previous studies have shown that vacuum-assisted excision (VAE) is a safe and effective alternative for surgical excision (SE) of benign breast lesions. However, the use of VAE in high-risk lesions is controversial and guidelines are ambiguous. This study describes the impact of the implementation of VAE in terms of management and outcomes compared to a cohort before implementation. METHODS: A single centre retrospective study with two cohorts: 'before' and 'after' implementation of VAE was performed...

OBJECTIVES: Current state-of-the-art natural language processing (NLP) techniques use transformer deep learning architectures, which depend on large training datasets. We hypothesized that traditional NLP techniques may outperform transformers for smaller radiology report datasets. METHODS: We compared the performance of BioBERT, a deep learning-based transformer model pre-trained on biomedical text, and three traditional machine learning models (gradient boosted tree, random forest, and logistic regression) on seven classification tasks given free-text radiology reports...

OBJECTIVES: Lung cancer is the leading cause of cancer-associated mortality worldwide Central nervous system(CNS) metastasis is a prevalent and serious complication. The most common treatment for brain metastasis (BM) is still radiation therapy (RT). An increasing number of drugs have been shown to have intracranial activity or to sensitize tumours to radiotherapy. METHODS: Consecutive advanced multiline therapy failure in patients with NSCLC with BM at the authors' hospital were retrospectively reviewed...

OBJECTIVE: Morphological features of an enlarged endolymphatic duct (ED) and sac (ES) are imaging biomarkers for genotype and hearing loss phenotype. We determine which biomarkers can be measured in a reproducible manner, facilitating further clinical prediction studies in enlarged vestibular aqueduct hearing loss. METHODS: A rater reproducibility study. Three consultant radiologists independently measured previously reported MRI ED & ES biomarkers (ED midpoint width, maximal ED diameter closest to the vestibule, ES length, ES width and presence of ES signal heterogeneity) and presence of incomplete partition Type 2 from 80 ears ( T 2 weighted axial MRI)...

OBJECTIVES: To identify variables predicting interfractional anatomical variations measured with cone-beam CT (CBCT) throughout abdominal paediatric radiotherapy, and to assess the potential of surface-guided radiotherapy (SGRT) to monitor these changes. METHODS: Metrics of variation in gastrointestinal (GI) gas volume and separation of the body contour and abdominal wall were calculated from 21 planning CTs and 77 weekly CBCTs for 21 abdominal neuroblastoma patients (median 4 years, range: 2 - 19 years)...

OBJECTIVE: Gamma passing rate (GPR) predictions using machine learning methods have been explored for treatment verification of radiotherapy plans. However, these methods presented datasets with unbalanced number of plans having different treatment conditions (heterogeneous datasets), such as anatomical sites or dose per fractions, leading to lower model interpretability and prediction performance. METHODS: We investigated the impact of the dataset composition on GPR binary classification (pass/fail) using random forest (RF), XG-boost, and neural network (NN) models...

OBJECTIVES: We aimed to explore the diagnostic efficacy of MR texture analysis and imaging signs in the differentiation of renal oncocytoma from renal cell carcinoma (RCC). METHODS: From January 2015 to March 2019, a total of 168 localized solid renal masses (37 oncocytomas, 131 RCCs) were retrospectively included. Two radiologists reviewed complete MR images and recorded imaging presentation. Texture parameters were extracted from 3D ROIs on axial FSE-T2WI. Univariate and multivariate logistic regressions were used for feature selection and nomogram construction...

OBJECTIVES: The purpose of this study is to report the oncological outcome, observed toxicities and normal tissue complication probability (NTCP) calculation for pencil beam scanning (PBS) PT delivered to salivary gland tumour (SGT) patients. METHODS: We retrospectively reviewed 26 SGT patients treated with PBSPT (median dose, 67.5 Gy(RBE)) between 2005 and 2020 at our institute. Toxicities were recorded according to CTCAEv.4.1. Overall survival (OS), local control (LC), locoregional control (LRC) and distant control (DC) were estimated...

OBJECTIVE: Accurate diagnosis and early treatment are crucial for survival in patients with brain metastases. This study aims to expand the capability of radiomics-based classification algorithms with novel features and compare results with deep learning-based algorithms to differentiate the subtypes of lung cancer from MRI of metastatic lesions in the brain. METHODS: This study includes 75 small cell lung carcinoma, 72 squamous cell carcinoma, and 75 adenocarcinoma segments...

OBJECTIVE: To explore the feasibility of measuring the volume of Meckel's cave by MRI before operation and its value in guiding percutaneous balloon compression (PBC) of trigeminal nerve (TN). METHODS: The preoperative MRI and operative data of 31 patients, who underwent PBC of TN, were analyzed retrospectively. Axial scanning was performed using T 2 -weighted three-dimensional high-resolution MRI, and then coronal and sagittal images were reconstructed. Volumes of Meckel's cave were measured by two radiologists, and their consistence was assessed using intraclass correlation coefficient (ICC)...

OBJECTIVES: Glioblastoma (GBM) is the most common malignant primary brain tumor with local recurrence after radiotherapy (RT), the most common mode of failure. Standard RT practice applies the prescription dose uniformly across tumor volume disregarding radiological tumor heterogeneity. We present a novel strategy using diffusion-weighted (DW-) MRI to calculate the cellular density within the gross tumor volume (GTV) in order to facilitate dose escalation to a biological target volume (BTV) to improve tumor control probability (TCP)...

OBJECTIVES: Our study used a radiomics method to differentiate bone marrow signal abnormality (BMSA) between Charcot neuroarthropathy (CN) and osteomyelitis (OM). METHODS AND MATERIALS: The records of 166 patients with diabetic foot suspected CN or OM between January 2020 and March 2022 were retrospectively examined. A total of 41 patients with BMSA on MRI were included in this study. The diagnosis of OM was confirmed histologically in 24 of 41 patients. We clinically followed 17 patients as CN with laboratory tests...

CT reconstruction has undergone a substantial change over the last decade with the introduction of iterative reconstruction (IR) and now with deep learning reconstruction (DLR). In this review, DLR will be compared to IR and filtered back-projection (FBP) reconstructions. Comparisons will be made using image quality metrics such as noise power spectrum, contrast-dependent task-based transfer function, and non-prewhitening filter detectability index ( dNPW ' ). Discussion on how DLR has impacted CT image quality, low-contrast detectability, and diagnostic confidence will be provided...