British Journal of Radiology最新文献

Objectives: We performed a retrospective study comparing two rectal preparation regimens, Polyethylene Glycol 3350 (PEG) and Fleet Enema (FE), in patients undergoing prostate Stereotactic Body Radiation Therapy (SBRT).

Methods: The study included 24 patients receiving prostate SBRT (40 Gy in 5 fractions), for a total of 120 treatment fractions. Patients received either FE (N = 73) or PEG (N = 47) for rectal preparation. Outcomes included: (1) treatment time, measured from the initial setup cone-beam CT (CBCT) to the post-treatment CBCT (including rectal-related interventions, excluding machine delays); (2) intra-fraction motion, defined as the displacement vector between verification and post-treatment CBCTs registered to fiducial markers; and (3) clinical acceptability, determined by blinded review of all setup CBCTs by three radiation therapists, who scored each scan as either "Acceptable" (proceed directly to treatment) or "Need Intervention". Regression analysis was used to compare regimens.

Results: Population-averaged median treatment times were 14 minutes (95% CI 5.8-22.2) for PEG and 11 minutes (95% CI 9.6-12.3) for FE, with greater time variability in PEG (p < 0.001). Intra-fraction motion did not differ significantly between regimens. All 3 RTs judged the setup CBCTs as clinically acceptable for treatment 47.7% of the time (95% CI 31.6-63.8%) for the PEG regimen and 74.4% of the time (95% CI 61% - 87.8%) for the FE regimen.

Conclusions: Overall, the FE regimen showed greater consistency in all outcome measures. This suggests an operational advantage for using FE since it results in more consistent patient treatment times without negatively impacting treatment quality and precision.

Advances in knowledge: Daily FE improves the consistency of prostate SBRT treatment and enhances the clinical workflow by minimizing unplanned disruptions.

Objectives: Management guidelines for incidental aortic dilation detected on low-dose chest computed tomography (LDCT) lung cancer screening (LCS) are lacking. Therefore, this study aims to validate artificial intelligence (AI) software for automated aortic measurements and assess aortic dilation distribution in screening participants.

Methods: Baseline LDCT scans from two tertiary centers (April 2017 to December 2023) were reviewed. In 100 randomly selected cases, radiologist- and AI-measured maximum aortic diameters (MADs) were compared at the ascending thoracic aorta (ATA), aortic arch (AACH), descending thoracic aorta (DTA), and abdominal aorta (AA). AI then analyzed all scans, and coronary artery calcification (CAC) was assessed using the Agatston method to evaluate correlations with MADs.

Results: Overall, 1,204 patients (99.2% men; mean age ± SD: 62.7 ± 5.4 years) were included. Intraclass correlation coefficients between radiologists and AI were 0.950, 0.758, 0.933, and 0.931 for ATA, AACH, DTA, and AA, respectively. Mean maximum diameters were: ATA, 38.7 ± 3.7 mm (33.4% ≥ 40 mm, 18.5% ≥ 42 mm, and 5.6% ≥ 45 mm); AACH, 37.3 ± 3.3 mm; DTA, 29.4 ± 2.9 mm; and AA, 26.3 ± 2.3 mm. MADs significantly correlated with CAC severity (p ≤  0.001).

Conclusion: AI software reliably measures MADs. Aortic dilation distribution may serve as a reference in LDCT LCS, and its association with CAC highlights the clinical importance of incorporating MADs into patient management.

Advances in knowledge: Validated AI software enables reliable MAD assessment; reported aortic dilation prevalence offers valuable reference data for LDCT LCS.

Objectives: This work aimed to introduce Advanced intelligence Clear-IQ Engine (Canon, Japan) (AiCE) reconstruction to the clinical workflow by assessing the image quality and impact on Radiotherapy treatment planning. This introduction would then allow for optimisation of CT scanning doses.

Methods: A CT scan of an electron density phantom was performed using clinical protocols using AIDR3D and AiCE reconstructions at different mAs values. Clinical scans were reconstructed using AiCE and the dose distributions of the clinical plans recalculated. An optimisation project was initiated for Breast Radiotherapy patients after the phantom testing proved the image quality is stable with reducing dose.

Results: In the electron density phantom the difference between the Hounsfield Number of water for AIDR3D and AiCE images was 5-6HU depending on the mAs. This was within IPEM 91 tolerances for HU variation. When comparing the clinical goals of plans calculated the dose difference was a maximum of 0.45 Gy. The median dose difference was a 0.02 Gy difference. The clinical doses were successfully reduced to the limit of what was tested in phantom measurements with the image quality being clinically acceptable and a 12% reduction in mean DLP.

Conclusion: AiCE has been evaluated to demonstrate HU stability that is suitable for use in Radiotherapy treatment planning. The breast CT protocol was optimised with the introduction of AiCE and the doses were reduced without affecting image quality.

Advances in knowledge: AiCE is a novel reconstruction technique and has been used for clinical treatment planning and for optimising CT doses.

Objectives: To evaluate a multi-parametric dual energy CT (DECT) radiomics model combined with clinical factors and DECT findings for differentiating between laryngeal benign and malignant lesions.

Methods: For this retrospective study, the radiomic models were constructed based on a whole cohort of 282 patients underwent DECT examination. The radiomics signature was selected based on reproducible features by using the least absolute shrinkage and selection operator method, and highly related radiomic, clinical features and DECT findings were selected to establish the radiomics-clinical model by using multivariable logistic regression analysis. Nomogram performance was evaluated by its discrimination, calibration, and clinical use.

Results: Compared with the single-parametric DECT radiomic models, the multi-parametric model can improve the diagnostic efficacy for differentiating laryngeal benign from malignant lesions, with AUCs of 0.938 in training set and 0.920 in test set, respectively. Moreover, multi-parametric DECT based radiomics-clinical model incorporates the radiomics signature and DECT-reported lesion size showed the best diagnostic performance (AUC of 0.945) in the whole cohort, when compared with the radiomics model (AUC of 0.933, P < 0.05) and clinical model (AUC of 0.855, P < 0.05).

Conclusions: The multi-parametric DECT based radiomics-clinical model can serve as an important modality for noninvasively differentiating laryngeal benign lesions from malignant ones.

Advances in knowledge: This study highlight the value of DECT based radiomics model for differentiating laryngeal benign from malignant lesions. Moreover, the combination of radiomic, clinical features and DECT findings demonstrated good performance for differential diagnosing in laryngeal lesions.

Objective: To evaluate solid volume ratio (SVR) in predicting long-term postoperative outcomes in lung adenocarcinoma patients.

Methods: This study retrospectively analyzed the clinical, pathological, and CT data of patients with lung adenocarcinoma who underwent surgical resection and were pathologically confirmed in the Department of Thoracic Surgery of our hospital from June 2014 to June 2023. Multivariate COX analysis was also conducted to identify independent factors that affect treatment effect. P < 0.05 was considered statistically significant.

Results: A total of 154 patients (82 males and 72 females) were included in this study. The average age was 62.11 ± 8.74 years. There were 60 patients (38.96%) who smoked, and 63 patients (40.90%) had positive pleural invasion. The 3-year DFS rate and OS rate after surgical resection were 87.5% and 92.0%, respectively; the 5-year DFS rate and OS rate after surgical resection were 81.6% and 89.1%, respectively. Multiple COX regression analysis showed that gender (P = 0.009, OR: 4.197, 95% CI: 1.426-12.353), and the solid volume ratio (P = 0.004, OR: 1.021, 95% CI: 1.007-1.036) were identified as an independent predictor of recurrence. Multivariate COX analysis showed that SVR (P = 0.003, OR: 1.028, 95% CI: 1.009-1.046) was identified as an independent predictor of postoperative survival in patients with lung cancer.

Conclusion: In this study, compared with consolidation tumor rate (CTR), the SVR has certain value in evaluating the therapeutic efficacy of lung adenocarcinoma.

Advances in knowledge: SVR is an independent predictor of postoperative recurrence and survival in lung cancer, and provides new ideas for postoperative efficacy evaluation.

Objectives: To characterise contemporary UK practice in prostate MRI reporting and pathways, and identify priorities for standardisation.

Methods: Between February and April 2025, a questionnaire was distributed by the British Society of Urogenital Radiology to UK-based consultant radiologists who report prostate MRI. It contained 34 questions, covering 6 domains: demographics; MRI protocols; biopsy; reporting preferences; imaging pathways; and attitudes towards accreditation.

Results: 77 radiologists representing 52 NHS Trusts across all nations of the UK responded. Key findings include variable patient preparation for MRI including anti-spasmodic medication (69.2% administering) and instruction related to bowel preparation (13.5%). 100% of Trusts were performing MRI prior to biopsy for suspected cancer; 73.1% using multiparametric MRI. When reporting prostate MRI for suspected cancer, 28.6% document only a PI-RADS score, 27.3% only a Likert score, with 44.1% stating both. The PI-QUAL score is moderately well known (71.4% of respondents) but not in routine use (7.8%). Transperineal prostate biopsy was performed at 88.5% of Trusts, with biopsy more likely to be performed by urologists (98.1% of Trusts) or urology nurses (36.5%) than radiologists (26.9%). Patients with high- or very high-risk prostate cancer undergo variable staging pathways, with university teaching hospitals more likely to offer PSMA PET/CT than other settings (33.3% vs 12.0%, p = 0.023).

Conclusions: This survey shows the current state of UK prostate MRI practice, including universal pre-biopsy MRI. It identifies areas for standardisation, including MRI protocols, scoring systems, and national staging guidelines.

Advances in knowledge: Provides an up-to-date snapshot on prostate MRI within the UK.

Objectives: This study aimed to develop and construct a predictive model based on the quantitative parameters of full-volume dual-energy computed tomography (DECT) to forecast the International Association for the Study of Lung Cancer classification of non-mucinous invasive pulmonary adenocarcinoma (IPA).

Methods: The preoperative clinical and imaging data of 161 patients with pure solid type non-mucinous IPA from September 2021 to May 2024 were retrospectively analyzed. The semiautomated software was used to perform full-volume segmentation of the lesions and the associated DECT quantitative parameters were recorded. Through univariate and multivariate logistic regression analyses, we identified independent characteristic variables that distinguished high-grade from low-grade non-mucinous IPA. We subsequently used these characteristic variables to construct a multiparameter model.

Results: Volume, slope of the spectral curve (λ40keV-100keV) and normalized iodine concentration (NIC) were identified as independent feature variables to distinguish low-grade and high-grade non-mucinous IPA. By utilizing these three variables, we constructed a quantitative visualization nomogram to distinguish the new IASLC grade of non-mucinous IPA. The model exhibited excellent performance in both the training and testing groups, with area under the curve (AUC) values of 0.884 (95% CI: 0.826-0.943) and 0.848 (95% CI: 0.738-0.958), respectively.

Conclusion: This study successfully established and validated a nomogram based on DECT quantitative parameters, which can effectively differentiate high-grade and low-grade non-mucinous IPA and provides potential value for clinical decision-making.

Advances in knowledge: This study is the first attempt to apply a nomogram based on DECT to assess the invasiveness of non-mucous IPA.

Negative workplace behaviour (NWB) - including bullying, harassment, mobbing, and tall poppy syndrome-remains a significant, under-addressed threat to healthcare professionals. This commentary explores NWB drivers, consequences and mitigation techniques in medicine, with a particular focus on radiology, using an evidence-based approach. The drivers of NWB are multifaceted, encompassing power imbalances, leadership failures, implicit bias, and institutional culture. Evidence highlights the disproportionate impact on women, who are more frequently targeted and more susceptible to burnout and severe mental health outcomes. Beyond individual harm, NWB degrades team performance, increases turnover, impairs patient safety, and erodes institutional integrity. Mitigation requires a commitment: fostering ethical, inclusive leadership; instituting zero-tolerance policies; supporting effective bystander intervention; and ensuring safe, transparent reporting mechanisms. Authentic leadership, diversity initiatives, and well-being support programs play critical roles in prevention. This paper highlights collective accountability to create psychologically safe workplaces in healthcare-where professionals can speak up without fear and are protected, respected, and empowered to thrive.

Background: levated levels of cancer antigen-125 (CA-125) are strongly associated with the likelihood of ovarian cancer recurrence, making it a significant concern in clinical practice. [18F]FDG PET/CT has emerged as a valuable tool for detecting recurrent ovarian cancer. This study aims to evaluate the diagnostic performance of [18F]FDG PET/CT in identifying ovarian cancer relapse among patients exhibiting rising CA-125 levels, through a systematic review and meta-analysis.

Methods: A comprehensive search was carried out across PubMed, Embase, and the Cochrane Library, encompassing all records up to July 2024. Studies were eligible for inclusion if they provided data on true positives (TP), false positives (FP), true negatives (TN), and false negatives (FN) regarding the detection of ovarian cancer recurrence in patients with elevated CA-125 levels. Studies were excluded if they were duplicates, lacked full-text availability, contained incomplete information or were unable to be included in data extraction, involved animal studies, or were reviews or systematic reviews. The data were analyzed using STATA version 15.1.

Results: Across all included studies, the pooled sensitivity and specificity were 0.94 (95% confidence interval (CI): 0.89-0.97) and 0.89 (95% CI: 0.71-0.96), respectively. The positive likelihood ratio (LR+) was 7.11 (95% CI: 2.75-18.38), while the negative likelihood ratio (LR-) was 0.07 (95% CI: 0.03-0.15). The overall diagnostic odds ratio (DOR) amounted to 99.20 (95% CI: 26.66-369.14). Additionally, the area under the receiver operating characteristic curve (AUC) reached 0.97 (95% CI: 0.95-0.98).

Conclusion: With its high sensitivity and specificity, [18F]FDG PET/CT serves as an effective tool for detecting ovarian cancer recurrence in patients exhibiting elevated CA-125 levels. These results endorse its effectiveness as a dependable diagnostic method in clinical settings.

Advances in knowledge: This meta-analysis provides updated pooled evidence that [18F]FDG PET/CT demonstrates excellent diagnostic accuracy (AUC 0.97) in detecting ovarian cancer recurrence in patients with elevated CA-125. Compared with earlier meta-analyses limited to PET alone, our findings highlight the added value of integrated PET/CT systems in improving specificity and reducing false positives, thereby supporting its recommendation in international guidelines and strengthening its role in clinical decision-making for recurrent ovarian cancer.

Objectives: To evaluate the clinical utility of Node-Reporting and Data System (Node-RADS) 1.0 in assessing axillary lymph node (ALN) on breast MRI.

Methods: This retrospective study included women with clinical T1-T2 stage breast cancer who underwent surgery between April 2014 and March 2023. MRI-ALN status was first evaluated using routine clinical diagnostic criteria. Node-RADS scores were subsequently assigned based on preoperative MRI after a two-week interval. The optimal cut-off was determined using the Youden index. Diagnostic performance was compared for assessing ALN metastasis (ALNM) and pathological ALN (pALN) burden. In the secondary analysis, differences in imaging features were further evaluated in patients with Node-RADS < 3.

Results: The optimal cut-off for diagnosing ALNM was Node-RADS >1. Compared with MRI-ALN status, Node-RADS score demonstrated lower sensitivity (56% vs. 71%, p < 0.01), but comparable specificity (92% vs. 85%, p = 0.16). For assessing pALN burden, Node-RADS > 2 was the optimal cut-off with lower sensitivity (55% vs. 77%, p < 0.01) but higher specificity (82% vs. 62%, p < 0.01). In the secondary analysis, patients with ALNM showed significant differences in cortical morphology and the suspicious breast-side lymph node sign.

Conclusions: Node-RADS 1.0 showed lower sensitivity than conventional MRI diagnosis in assessing ALNM but demonstrated good specificity in evaluating ALNM and pALN burden.

Advances in knowledge: Node-RADS 1.0 showed lower sensitivity than conventional MRI diagnosis in assessing ALNM. The potential value of cortical morphology and the suspicious breast-side lymph node sign in improving the sensitivity of Node-RADS 1.0 warrant further investigation.