In 2017, roughly 2 trillion (2,000,000,000,000) medical images were produced, reviewed, reported, archived, and used in the detection and management of disease. Based on historical trends, this number has doubled every 5 years and is accelerating. This explosive growth in imaging data has created major opportunities for the use of Artificial Intelligence (AI). The question is less whether radiologists, and technologists, will be replaced by AI (they will not) and more about whether we could survive without AI. Although intelligent algorithms have been used for some time in segments of the imaging field, new methods of machine learning, based particularly on “deep learning”, are much more powerful. Many of the deep learning publications today point to the promise of significant advances in efficiency, precision, reproducibility, and prognostic abilities. If AI will not replace radiologists/technologists but rather augment them with tools to meet the rising demands for diagnostic imaging, then it is imperative that we have a basic understanding of the concepts and language that defines this area of knowledge. In the not so distant past the average technologist understood the basics of film processing but wouldn’t even recognize the words DICOM or EMR; we are now at that point of change with AI. Deep learning, machine learning, neural networks, ground truth, the list goes on. The goal of this presentation is to provide a basic framework of the concepts, terminology, and references to how AI has, and likely, will be employed in medical imaging, thus making us better practitioners and partners with this technology. Read More

Meeting name: SPR 2019 Annual Meeting & Postgraduate Course , 2019

Authors: Stanley Parker, Stanley Charles

Keywords: Artificial Intelligence, Medical Imaging, Technologist

Superior mesenteric artery (SMA) syndrome, or Wilkie’s syndrome, is an obscure condition in which an acute angulation between the aorta and SMA leads to compression of the third part of the duodenum. Subsequently, patients typically present with a constellation of gastrointestinal findings that closely resemble small bowel obstruction, early satiety, and anorexia. SMA syndrome is most often observed in the setting of rapid weight loss, wasting conditions, and corrective spinal surgeries, where a decrease in retroperitoneal fat diminishes the cushion between the aorta and SMA, causing vascular compression of the duodenum. Diagnosis of SMA syndrome is one of exclusion and is based on the combination of highly suspicious clinical findings and confirmatory diagnostic imaging evidence of obstruction. Upper GI Fluoroscopy can demonstrate a dilated first and second portion of the duodenum, with compression of the third portion, and delayed passage of contrast past midline. Ultrasound and computed tomography (CT)/magnetic resonance imaging (MRI) enable measurement of the aortomesenteric angle and distance, with normal values ranging from 25-60° and 10-28mm, respectively, and values indicative of SMA syndrome ranging from 6-15° and 2-8mm, respectively. We present a classic case of SMA syndrome in a 15-year-old patient. The patient presented with clinical symptoms consisting of scoliosis, chronic nausea and vomiting, weight loss, and anorexia. The patient then underwent Upper GI Fluoroscopy which demonstrated duodenal dilatation and delayed contrast transit past midline, achieved only after prolonged decubitus and prone positioning. Subsequently, abdominal ultrasound demonstrated an aortomesenteric angle of 10-18° and an aortomesenteric distance of 5 mm. Lastly, abdominal MRI demonstrated an aortomesenteric angle of 15° and an aortomesenteric distance of 3 mm, corroborating the ultrasound findings and confirming the diagnosis of SMA syndrome. The patient was initiated on nutritional support and at most recent follow-up was responding well to conservative treatments. Read More

Meeting name: SPR 2019 Annual Meeting & Postgraduate Course , 2019

Authors: Stanley Parker, Stanley Charles

Keywords: SMA Syndrome, Ultrasound, MRI