Impact of pre-operative abdominal MRI on survival for patients with resected pancreatic carcinoma: a population-based study.

Background: This study determined the impact of pre-operative abdominal MRI on all-cause mortality for patients with resected PDAC. Methods: All adult (≥18 years) PDAC patients who underwent pancreatectomy between January 2011 and December 2022 in Ontario, Canada, were identified for this population-based cohort study (ICD-O-3 codes: C250, C251, C252, C253, C257, C258). Patient demographics, comorbidities, PDAC stage, medical and surgical management, and survival data were sourced from multiple linked provincial administrative databases at ICES. All-cause mortality was compared between patients with and without a pre-operative abdominal MRI after controlling for multiple covariates. Findings: A cohort of 4579 patients consisted of 2432 men (53.1%) and 2147 women (46.9%) with a mean age of 65.2 years (standard deviation: 11.2 years); 2998 (65.5%) died while 1581 (34.5%) survived. Median follow-up duration post-resection was 22.4 months (interquartile range: 10.8-48.8 months), and median survival post-pancreatectomy was 25.9 months (95% confidence interval [95% CI]: 24.8, 27.5). Patients who underwent a pre-operative abdominal MRI had a median survival of 33.1 months (95% CI: 30.7, 37.2) compared to 21.1 months (95% CI: 19.8, 22.6) for all others. A total of 2354/4579 (51.4%) patients underwent a pre-operative abdominal MRI, which was associated with a 17.2% (95% CI: 11.0, 23.1) decrease in the rate of all-cause mortality, with an adjusted hazard ratio (aHR) of 0.828 (95% CI: 0.769, 0.890). Interpretation: Pre-operative abdominal MRI was associated with improved overall survival for PDAC patients who underwent pancreatectomy, possibly due to better detection of liver metastases than CT. Funding: Northern Ontario Academic Medicine Association (NOAMA) Clinical Innovation Fund.

Canadian radiology: 2024 update.

Radiology in Canada is advancing through innovations in clinical practices and research methodologies. Recent developments focus on refining evidence-based practice guidelines, exploring innovative imaging techniques and enhancing diagnostic processes through artificial intelligence. Within the global radiology community, Canadian institutions play an important role by engaging in international collaborations, such as with the American College of Radiology to refine implementation of the Ovarian-Adnexal Reporting and Data System for ultrasound and magnetic resonance imaging. Additionally, researchers have participated in multidisciplinary collaborations to evaluate the performance of artificial intelligence-driven diagnostic tools for chronic liver disease and pediatric brain tumors. Beyond clinical radiology, efforts extend to addressing gender disparities in the field, improving educational practices, and enhancing the environmental sustainability of radiology departments. These advancements highlight Canada's role in the global radiology community, showcasing a commitment to improving patient outcomes and advancing the field through research and innovation. This update underscores the importance of continued collaboration and innovation to address emerging challenges and further enhance the quality and efficacy of radiology practices worldwide.

ACR Appropriateness Criteria® Clinically Suspected Adnexal Mass, No Acute Symptoms: 2023 Update.

Asymptomatic adnexal masses are commonly encountered in daily radiology practice. Although the vast majority of these masses are benign, a small subset have a risk of malignancy, which require gynecologic oncology referral for best treatment outcomes. Ultrasound, using a combination of both transabdominal, transvaginal, and duplex Doppler technique can accurately characterize the majority of these lesions. MRI with and without contrast is a useful complementary modality that can help characterize indeterminate lesions and assess the risk of malignancy is those that are suspicious. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

Bowel Emergencies in Patients With Cancer.

Cancer is the second most common cause of death worldwide. Bowel emergencies in patients with cancer are becoming increasingly more prevalent due to advances in cancer therapy and longer overall patient survival. When these patients present acutely, they are often frail and may have pre-existing co-morbidities. This article discusses the imaging features of bowel emergencies commonly encountered in oncological patients in clinical practice. These include chemotherapy related colitis, neutropenia enterocolitis and typhlitis, toxic megacolon, bowel perforation, malignant bowel obstruction and gastrointestinal haemorrhage. The radiologist plays a key role in identifying these oncological emergencies and guiding further management.

Applications of Artificial Intelligence in Acute Abdominal Imaging.

Artificial intelligence (AI) is a rapidly growing field with significant implications for radiology. Acute abdominal pain is a common clinical presentation that can range from benign conditions to life-threatening emergencies. The critical nature of these situations renders emergent abdominal imaging an ideal candidate for AI applications. CT, radiographs, and ultrasound are the most common modalities for imaging evaluation of these patients. For each modality, numerous studies have assessed the performance of AI models for detecting common pathologies, such as appendicitis, bowel obstruction, and cholecystitis. The capabilities of these models range from simple classification to detailed severity assessment. This narrative review explores the evolution, trends, and challenges in AI applications for evaluating acute abdominal pathologies. We review implementations of AI for non-traumatic and traumatic abdominal pathologies, with discussion of potential clinical impact, challenges, and future directions for the technology.

Deep Learning for Pneumothorax Detection on Chest Radiograph: A Diagnostic Test Accuracy Systematic Review and Meta Analysis.

BACKGROUND: Pneumothorax is a common acute presentation in healthcare settings. A chest radiograph (CXR) is often necessary to make the diagnosis, and minimizing the time between presentation and diagnosis is critical to deliver optimal treatment. Deep learning (DL) algorithms have been developed to rapidly identify pathologic findings on various imaging modalities. PURPOSE: The purpose of this systematic review and meta-analysis was to evaluate the overall performance of studies utilizing DL algorithms to detect pneumothorax on CXR. METHODS: A study protocol was created and registered a priori (PROSPERO CRD42023391375). The search strategy included studies published up until January 10, 2023. Inclusion criteria were studies that used adult patients, utilized computer-aided detection of pneumothorax on CXR, dataset was evaluated by a qualified physician, and sufficient data was present to create a 2 × 2 contingency table. Risk of bias was assessed using the QUADAS-2 tool. Bivariate random effects meta-analyses and meta-regression modeling were performed. RESULTS: Twenty-three studies were selected, including 34 011 patients and 34 075 CXRs. The pooled sensitivity and specificity were 87% (95% confidence interval, 81%, 92%) and 95% (95% confidence interval, 92%, 97%), respectively. The study design, use of an institutional/public data set and risk of bias had no significant effect on the sensitivity and specificity of pneumothorax detection. CONCLUSIONS: The relatively high sensitivity and specificity of pneumothorax detection by deep-learning showcases the vast potential for implementation in clinical settings to both augment the workflow of radiologists and assist in more rapid diagnoses and subsequent patient treatment.

Abdominal Emergencies in Cancer Patients.

Abdominal emergencies in cancer patients encompass a wide spectrum of oncologic conditions caused directly by malignancies, paraneoplastic syndromes, reactions to the chemotherapy or often represent the first clinical manifestation of an unknown malignancy. Not rarely, clinical symptoms are the tip of an iceberg. In this scenario, the radiologist is asked to exclude the cause responsible for the patient's symptoms, to suggest the best way to manage and to rule out the underlying malignancy. In this article, we discuss some of the most common abdominal oncological emergencies that may be encountered in an emergency department.

Imaging of hepato-pancreato-biliary emergencies in patients with cancer.

Hepato-pancreato-biliary (HPB) emergencies in patients with cancer encompass an extensive array of various conditions, including primary malignancies that require prompt treatment, associated severe complications, and life-threatening consequences arising from treatment. In patients with cancer, the liver can be affected by chemotherapy-induced hepatotoxicity, veno-occlusive disease, Budd-Chiari syndrome, liver hemorrhage, and other complications arising from cancer therapy with all these complications requiring timely diagnosis and prompt treament. Cholecystitis induced by systemic anticancer therapies can result in severe conquences if not promptly identified and treated. The application of immunotherapy in cancer therapy is associated with cholangitis. Hemobilia, often caused by medical interventions, may require arterial embolization in patients with severe bleeding and hemodynamic instability. Malignant biliary obstruction in patients with biliary cancers may necessitate palliative strategies such as biliary stenting. In pancreatic cancer, patients often miss surgical treatment due to advanced disease stages or distant metastases, leading to potential emergencies at different treatment phases. This comprehensive review underscores the complexities of diagnostic and treatment roles of medical imaging in managing HPB emergencies in patients with cancer. It illustrates the crucial role of imaging techniques, including magnetic resonance imaging, computed tomography and ultrasound, in diagnosing and managing these conditions for timely intervention. It provides essential insights into the critical nature of early diagnosis and intervention in cancer-related HPB emergencies, ultimately impacting patient outcomes and survival rates.