Omer Awan

18F-FDG PET/CT Imaging of Extranodal Rosai-Dorfman Disease with Hepatopancreatic Involvement - A Pictorial and Literature Review

We share our experience with serial PET/CT imaging on a patient with extranodal Rosai-Dorfman disease (RDD) with hepatopancreatic involvement. RDD is a benign proliferative disorder of histiocytes mainly involving the lymph nodes. It typically presents with fever and painless cervical lymphadenopathy in young adults and less than half of RDS cases demonstrate extranodal involvement. RDD involvement of the liver and pancreas is extremely rare, and this case highlights the role of PET/CT in its management.

Diagnostic Yield of FDG-PET/CT, MRI, and CSF Cytology in Non-Biopsiable Neurolymphomatosis as a Heralding Sign of Recurrent Non-Hodgkin's Lymphoma

Neurolymphomatosis (NL) is a rare condition associated with lymphomas in which various structures of the nervous system are infiltrated by malignant lymphocytes. Rarely, it may be the presenting feature of recurrence of lymphoma otherwise deemed to be in remission. It is crucial, as is the case with all types of nodal or visceral involvement of lymphoma, to identify the disease early and initiate treatment with chemotherapy and/or radiation therapy. Positron emission tomography-computed tomography (PET-CT) has been shown to be a sensitive modality for staging, restaging, biopsy guidance, therapy response assessment, and surveillance for recurrence of lymphoma. Magnetic resonance imaging (MRI) is another useful imaging modality, which, along with PET/CT, compliment cerebrospinal spinal fluid (CSF) cytology and electromyography (EMG) in the diagnosis of NL. Performing nerve biopsies to confirm neurolymphomatosis can be challenging and with associated morbidity. The case presented herein illustrates the practical usefulness of these tests in detecting NL as a heralding feature of lymphoma recurrence, especially in the absence of histopathologic correlation.

Deep Learning in Radiology

As radiology is inherently a data-driven specialty, it is especially conducive to utilizing data processing techniques. One such technique, deep learning (DL), has become a remarkably powerful tool for image processing in recent years. In this work, the Association of University Radiologists Radiology Research Alliance Task Force on Deep Learning provides an overview of DL for the radiologist. This article aims to present an overview of DL in a manner that is understandable to radiologists; to examine past, present, and future applications; as well as to evaluate how radiologists may benefit from this remarkable new tool. We describe several areas within radiology in which DL techniques are having the most significant impact: lesion or disease detection, classification, quantification, and segmentation. The legal and ethical hurdles to implementation are also discussed. By taking advantage of this powerful tool, radiologists can become increasingly more accurate in their interpretations with fewer errors and spend more time to focus on patient care.

Translational Radiomics: Defining the Strategy Pipeline and Considerations for Application—Part 1: From Methodology to Clinical Implementation

Enterprise imaging has channeled various technological innovations to the field of clinical radiology, ranging from advanced imaging equipment and postacquisition iterative reconstruction tools to image analysis and computer-aided detection tools. More recently, the advancements in the field of quantitative image analysis coupled with machine learning-based data analytics, classification, and integration have ushered us into the era of radiomics, which has tremendous potential in clinical decision support as well as drug discovery. There are important issues to consider to incorporate radiomics as a clinically applicable system and a commercially viable solution. In this two-part series, we offer insights into the development of the translational pipeline for radiomics from methodology to clinical implementation (Part 1) and from that to enterprise development (Part 2).

Translational Radiomics: Defining the Strategy Pipeline and Considerations for Application—Part 2: From Clinical Implementation to Enterprise

Enterprise imaging has channeled various technological innovations to the field of clinical radiology, ranging from advanced imaging equipment and postacquisition iterative reconstruction tools to image analysis and computer-aided detection tools. More recently, the advancement in the field of quantitative image analysis coupled with machine learning-based data analytics, classification, and integration has ushered in the era of radiomics, a paradigm shift that holds tremendous potential in clinical decision support as well as drug discovery. However, there are important issues to consider to incorporate radiomics into a clinically applicable system and a commercially viable solution. In this two-part series, we offer insights into the development of the translational pipeline for radiomics from methodology to clinical implementation (Part 1) and from that point to enterprise development (Part 2). In Part 2 of this two-part series, we study the components of the strategy pipeline, from clinical implementation to building enterprise solutions.

Value-Based Assessment of Radiology Reporting Using Radiologist-Referring Physician Two-Way Feedback System—a Design Thinking-Based Approach

In the era of value-based healthcare, many aspects of medical care are being measured and assessed to improve quality and reduce costs. Radiology adds enormously to health care costs and is under pressure to adopt a more efficient system that incorporates essential metrics to assess its value and impact on outcomes. Most current systems tie radiologists’ incentives and evaluations to RVU-based productivity metrics and peer-review-based quality metrics. In a new potential model, a radiologist’s performance will have to increasingly depend on a number of parameters that define “value,” beginning with peer review metrics that include referrer satisfaction and feedback from radiologists to the referring physician that evaluates the potency and validity of clinical information provided for a given study. These new dimensions of value measurement will directly impact the cascade of further medical management. We share our continued experience with this project that had two components: RESP (Referrer Evaluation System Pilot) and FRACI (Feedback from Radiologist Addressing Confounding Issues), which were introduced to the clinical radiology workflow in order to capture referrer-based and radiologist-based feedback on radiology reporting. We also share our insight into the principles of design thinking as applied in its planning and execution.

Sinonasal NUT-Midline Carcinoma - A Multimodality Approach to Diagnosis, Staging and Post-Surgical Restaging.

Nuclear protein testis (NUT) midline carcinoma is a rare malignancy involving predominantly the midline structures of the body. It is characterized by its genotypic feature of BRD4-NUT translocation, which is in contrast with other malignant processes that are usually categorized based on their histologic/phenotypic features. As these tumors may vary in their histologic presentation, they can be misdiagnosed as poorly differentiated carcinomas. Moreover, they are often very aggressive and associated with high mortality. Therefore, it is extremely important to diagnose them early using computed tomography (CT) and magnetic resonance imaging (MRI) and perform staging and restaging using 18-fluorodeoxyglucose positron emission tomography/computed tomography (18-FDG PET/CT), in addition to accurately identifying them at a microscopic and molecular level. We report a unique case of a sinonasal NUT midline carcinoma that was diagnosed with CT, staged with PET/CT, and restaged using PET/CT and MRI.

Imaging Patterns of Injuries After the 2015 Amtrak Philadelphia Train Derailment

OBJECTIVEnThe purpose of this article is to describe the injury patterns observed in the 2015 Philadelphia Amtrak train derailment.nnnCONCLUSIONnFractures accounted for most observed injuries, but uncommon and potentially serious injuries included posterior sternoclavicular dislocation and mesenteric contusion. Imaging plays a critical role in the triage of patients during mass-casualty events, and familiarity with the injury patterns associated with high-velocity unrestrained blunt force trauma will aid diagnosis in any future similar occurrence.

Painless hand mass

Radiograph (Fig. 1) and CT (Fig. 2) images show a wellcorticated osseous lesion originating from the dorsomedial surface of the second metacarpal neck. There is a slight irregularity of the underlying cortex, but no periosteal reaction or bone destruction. Although no visible cleavage plane separates the lesion from the second metacarpal, the medullary space of the lesion is noncontiguous with that of the underlying bone, and it lacks characteristic orientation away from the joint space as is seen with an osteochondroma. Clinically, a firm, immobile, nontender mass was palpated in the second intermetacarpal space. The overlying skin was normal in appearance. Because the patient had a limited range of motion at the second and third carpometacarpal joints, surgical excision was performed. Histopathology demonstrates fragments of bone and cartilage with areas of endochondral ossification and surrounding bland fibroblastic proliferation. The interface between forming bone and cartilage has a characteristic purple-blue staining quality (Fig. 3). First described by Nora et al. in 1983 (described in Abramovic i and Ste ine r [1] ) , b iza r re pa ros tea l osteochondromatous proliferation (BPOP), also referred to as a BNora lesion,^ is a rare, benign, locally aggressive osteochondromatous exostosis composed of bone and cartilage in a fibrous myxoid cell stroma without cellular atypia. Histologically, BPOP is characterized by the presence of a hypercellular fibrocartilaginous cap containing large, bizarre binucleate chondrocytes, with admixed areas of endochondral ossification maturing to trabecular bone. Bony trabeculae are histologically immature, with high osteoblastic activity and irregular calcification. Bizarre parosteal osteochondromatous proliferation most commonly arise from the periosteum of the metacarpals and metatarsals, with the hand affected four timesmore commonly

Adapting a Standardized, Industry-Proven Tool to Measure Patients’ Perceptions of Quality at the Point of Care in a PET/CT Center

Patient satisfaction with health-care delivery is essential today. Using a psychometrically validated questionnaire—SERVPERF—we quantitatively measured patients’ perceptions of the quality of service at the point of care in a PET/CT center, and we used this information to guide subsequent quality improvement interventions. SERVPERF is a survey instrument that measures performance for various services. It has demonstrated reliability and validity across various industries. The standard for measuring patient perception of quality in hospitals—the “Hospital Consumer Assessment of Health Care Providers and Systems” survey—does not include questions about the care received in a typical radiology department and is not performed at the point of care. Methods: 429 patients undergoing PET/CT examinations filled out an anonymous modified SERVPERF questionnaire on completion of imaging and reported their level of agreement with each of the 27 items by circling a Likert-type scale from 1 to 7. Each item was designed to elicit a response on the patient’s perception of performance on a metric of quality. Data were summarized as the mean of each item. The frequency of low scores (≤3) was also calculated. Results: The items with the lowest mean score were “The department’s physical facilities are visually appealing” (6.158) and “Documentation such as sign-in sheet, handouts, and brochures are visually appealing” (6.162). The item with the highest frequency of low scores (≤3) was, “The department provides services at the promised time” (11/429 responses). Conclusion: Our study showed that patient perception of quality in a diagnostic radiology department can be measured with a standardized survey at the point of care delivery and used to direct patient-centered quality improvement interventions.