Cryobiopsy with radial-endobronchial ultrasound (Cryo-Radial) has comparable diagnostic yield with higher safety in comparison to computed tomography-guided transthoracic biopsy for peripheral pulmonary lesions: An exploratory randomised study.

BACKGROUND: Computed tomography-guided transthoracic biopsy (CT-TTB) is the 'gold standard' biopsy for lung nodules. Radial-endobronchial ultrasound (R-EBUS) bronchoscopy is another recommended biopsy but carries a lower diagnostic yield. Addition of cryobiopsy with R-EBUS (Cryo-Radial) has shown promising results. There are no studies comparing CT-TTB with Cryo-Radial biopsy. AIM: The co-primary aims were the diagnostic yeild and safety. The secondary aim: ability to test epidermal growth factor receptor (EGFR). METHODS: A randomised controlled, multicentre exploratory study was conducted at three tertiary hospitals. Patients with nodules >1 cm on CT of the chest were randomised to CT-TTB or Cryo-Radial. With Cryo-Radial, patients had 1-3 cryo-biopsies in addition to at least one R-EBUS biopsy through the 2.6 mm guide sheath. RESULTS: Forty-eight patients were randomised: 22 to CT-TTB and 26 to Cryo-Radial. Sixteen in the CT-TTB and 20 in the Cryo-Radial received the allocated biopsy. The diagnostic yield was CT-TTB 93.8% (15/16) versus Cryo-Radial 85% (17/20) P = 0.61 and the odds ratio was 0.37. For 5/13 (38%), a diagnosis was solely made on cryobiopsy. Eleven (78%) of 14 in CT-TTB versus 7/10 (70%) Cryo-Radial were suitable for EGFR testing P = 0.66, with odds ratio 0.63. Pneumothorax occurrence was 44% (7/16) in CT-TTB versus 4.2% (1/24) in Cryo-Radial. Two (12.5%) of 16 CT-TTB required chest drain insertion. CONCLUSION: Cryo-Radial is comparable in diagnostic yield and ability to perform EGFR testing with a significantly lower risk of pneumothorax, compared with CT-TTB. Cryo-Radial has the additional advantage of mediastinal staging during the same procedure with Linear-EBUS and is a promising first-line tool in the diagnostic method of lung cancer.

Automated pneumothorax triaging in chest X-rays in the New Zealand population using deep-learning algorithms.

INTRODUCTION: The primary aim was to develop convolutional neural network (CNN)-based artificial intelligence (AI) models for pneumothorax classification and segmentation for automated chest X-ray (CXR) triaging. A secondary aim was to perform interpretability analysis on the best-performing candidate model to determine whether the model's predictions were susceptible to bias or confounding. METHOD: A CANDID-PTX dataset, that included 19,237 anonymized and manually labelled CXRs, was used for training and testing candidate models for pneumothorax classification and segmentation. Evaluation metrics for classification performance included Area under the receiver operating characteristic curve (AUC-ROC), sensitivity and specificity, whilst segmentation performance was measured using mean Dice and true-positive (TP)-Dice coefficients. Interpretability analysis was performed using Grad-CAM heatmaps. Finally, the best-performing model was implemented for a triage simulation. RESULTS: The best-performing model demonstrated a sensitivity of 0.93, specificity of 0.95 and AUC-ROC of 0.94 in identifying the presence of pneumothorax. A TP-Dice coefficient of 0.69 is given for segmentation performance. In triage simulation, mean reporting delay for pneumothorax-containing CXRs is reduced from 9.8 ± 2 days to 1.0 ± 0.5 days (P-value < 0.001 at 5% significance level), with sensitivity 0.95 and specificity of 0.95 given for the classification performance. Finally, interpretability analysis demonstrated models employed logic understandable to radiologists, with negligible bias or confounding in predictions. CONCLUSION: AI models can automate pneumothorax detection with clinically acceptable accuracy, and potentially reduce reporting delays for urgent findings when implemented as triaging tools.

Reducing the MRI outpatient waiting list through a capacity and demand time series improvement programme.

INTRODUCTION: A capacity and demand improvement initiative commenced in January 2019 with the goal of reducing the growing outpatient waiting list for magnetic resonance imaging (MRI) at Counties Manukau District Health Board (CMDHB). Initial work showed that the capacity (MRI machines and staff) actually outstripped demand, which challenged pre-existing assumptions. This became the basis for interventions to improve efficiency in the department. Interventions undertaken can be split into three distinct categories: (1) matching capacity to demand, (2) waiting list segmentation and (3) redesigning operational systems. METHODS: A capacity and demand time series during 2019 and 2020 was used as the basis for improving waiting list and operational systems. A combination of the Model for Improvement and Lean principles were used to embed operational improvements. Multiple small tests of change were implemented to various aspects of the MRI waiting list process. Staff engagement was central to the success of the quality improvement (QI) initiatives. The radiological information system (RIS) provided the bulk of the data, and this was supplemented with manual data collection. RESULTS: The number of people waiting for an MRI scan decreased from 1,954 at the start of the project to 413 at its conclusion-an overall reduction of 75%. Moreover, the average waiting time reduced from 96.4 days to 23.1. Achieving the Ministry of Health's (MoH) Priority 2 (P2) target increased from 23% to 87.5%. CONCLUSION: A partnership between Ko Awatea and the radiology department at CMDHB, examining capacity and demand for MRI and using multiple QI techniques, successfully and sustainably reduced the MRI waiting list over a two-year period. The innovative solutions to match capacity to demand may be instructive for other radiology departments, and other waiting list scenarios.

Curation of the CANDID-PTX Dataset with Free-Text Reports.

Supplemental material is available for this article. Keywords: Conventional Radiography, Thorax, Trauma, Ribs, Catheters, Segmentation, Diagnosis, Classification, Supervised Learning, Machine Learning © RSNA, 2021.

The postoperative radiological features of laparoscopic sleeve gastrectomy.

Obesity is rapidly becoming one of the major challenges for health care systems. Surgery has proved to be one of the most effective methods of helping patients to achieve sustainable weight loss. Laparoscopic sleeve gastrectomy is a relatively new bariatric surgical technique. A staple line is placed in a line parallel to the lesser curve of the stomach, excluding up to 85% of the volume of the stomach. The excluded stomach is then resected leaving a 'tube' of residual stomach. Radiologists may be asked to perform and interpret imaging studies in the postoperative period and should be familiar with the normal appearances and common complications. Postoperative radiological investigations will typically be for suspected leak or obstruction. A water soluble contrast upper gastrointestinal (UGI) series should be performed in both suspected leak and obstruction if the patient is conscious and able to swallow. A normal postoperative UGI series will show free flow of contrast into the gastric remnant, which will be tubular with no spillage of contrast beyond the staple line, which is located on the caudal aspect of the gastric remnant. Stenosis or obstruction of the stomach may occur if the stomach remnant is too tight or torsion of the stomach. Stenosis is usually treated endoscopically with dilation and torsion is treated surgically. Leaks are often treated with covered stents which may be placed with endoscopic or radiological guidance. Collections may be drained under fluoroscopic, ultrasound or computed tomography guidance.

Common patterns in 558 diagnostic radiology errors.

INTRODUCTION: As a Quality Improvement initiative our department has held regular discrepancy meetings since 2003. We performed a retrospective analysis of the cases presented and identified the most common pattern of error. METHODS: A total of 558 cases were referred for discussion over 92 months, and errors were classified as perceptual or interpretative. The most common patterns of error for each imaging modality were analysed, and the misses were scored by consensus as subtle or non-subtle. RESULTS: Of 558 diagnostic errors, 447 (80%) were perceptual and 111 (20%) were interpretative errors. Plain radiography and computed tomography (CT) scans were the most frequent imaging modalities accounting for 246 (44%) and 241 (43%) of the total number of errors, respectively. In the plain radiography group 120 (49%) of the errors occurred in chest X-ray reports with perceptual miss of a lung nodule occurring in 40% of this subgroup. In the axial and appendicular skeleton missed fractures occurred most frequently, and metastatic bone disease was overlooked in 12 of 50 plain X-rays of the pelvis or spine. The majority of errors within the CT group were in reports of body scans with the commonest perceptual errors identified including 16 missed significant bone lesions, 14 cases of thromboembolic disease and 14 gastrointestinal tumours. Of the 558 errors, 312 (56%) were considered subtle and 246 (44%) non-subtle. CONCLUSION: Diagnostic errors are not uncommon and are most frequently perceptual in nature. Identification of the most common patterns of error has the potential to improve the quality of reporting by improving the search behaviour of radiologists.

Economic and ethical impact of extrarenal findings on potential living kidney donor assessment with computed tomography angiography.

To determine the prevalence and spectrum of extrarenal findings in a screening population of potential living kidney donors undergoing renal Computed tomography angiography (CTA) and evaluate their impact on subsequent patient management and imaging costs. Two radiologists retrospectively reviewed 175 consecutive renal CTA's performed for assessment of potential living kidney donors. Extrarenal radiological findings were recorded and classified according to high, medium, or low importance based on clinical relevance and the need for further investigations and/or treatment. The cost of additional imaging examinations was calculated using 2002 Canadian (British Columbia) reimbursements. There were 73 extrarenal findings in 71/175 (40.6%) of the potential kidney donors in the study population. Findings were categorized as of high clinical importance in 18 (10.3%) cases, including lung lesions, bowel tumors, and liver tumors and as medium importance in 31 (17.7%). Twenty-two (12.6%) individuals had findings categorized as low importance, probably of no clinical significance and requiring no follow-up. Further potential evaluation of the 49 patients (28%) with highly and moderately significant extrarenal findings may require an additional $6137 (mean $35.1 per each case of all the screened patients). Transplantation of a kidney from a living donor is an excellent alternative to cadaveric allografts. Potential living kidney donors are a highly selected population of healthy individuals, screened for significant past or current medical conditions before undergoing CTA. Despite this screening, potentially significant extrarenal findings (classified as high or medium importance) were revealed in 28% of patients. These patients may require further investigations and/or treatment. The referring physician and patient should be aware of such potentially high probability, which may require further nontransplant related evaluation and treatment. This has medical, legal, economic, and ethical implications.