Clinical implementation of cinematic rendering

Cinematic rendering is a recently developed photorealistic display technique for standard volumetric data sets. It has broad-reaching applications in cardiovascular, musculoskeletal, abdominopelvic, and thoracic imaging. It has been used for surgical planning and has emerging use in educational settings. We review the logistics of performing this post-processing step and its integration into existing workflow.

Metastatic sclerosing epithelioid fibrosarcoma

Sclerosing epithelioid fibrosarcoma is a rare fibrosarcoma variant in which more than half of patients experience local recurrence or metastatic spread. In the current literature, there is limited and nonspecific imaging data, contributing to frequent misdiagnosis and delays in treatment intervention. Given the poor prognosis associated with this malignancy and the high probability of metastases, accurate and prompt diagnoses are critical. In this article, we report the case of a 27-year-old female diagnosed with metastatic sclerosing epithelioid fibrosarcoma following the discovery of a growing palpable mass on her right gluteus maximus muscle. We focus on the use of radiological imaging modalities in optimizing diagnosis and correlate our imaging and pathological findings.

Solitary plasmacytoma of the pancreas: A rare case report

A plasmacytoma is a cancerous growth of abnormal plasma cells that arise within osseous or soft tissue structures. In soft tissue structures, plasmacytomas can present as solitary or multiple masses in the absence of systemic involvement. Solitary plasmacytomas can be subcategorized as extramedullary plasmacytoma (derived from plasma cells located in soft tissues) or osseous plasmacytoma (derived from plasma cells located in the bone marrow). Infrequently, these tumors can arise as extramedullary lesions from the pancreas and present similarly to other tumors, such as pancreatic neuroendocrine tumors (PNETs). In this article, we report the case of a 62-year-old male with a diagnosis of solitary plasmacytoma of the pancreas. We focus on optimizing diagnosis and management through the application of radiological imaging modalities, specifically computed tomography (CT) scans and positron emission tomography-computed tomography (PET-CT) scans.

Primary renal liposarcoma simulating angiomyolipoma

Liposarcomas are infrequent malignant tumors of mesenchymal origin most commonly seen in the extremities. Although infrequent, these can develop as primary lesions in the soft tissue of the kidney, making them difficult to diagnose through imaging modalities alone. Primary renal liposarcomas are associated with poor prognoses, increasing the importance of timely and accurate diagnosis. In extremely rare instances, the tumor can arise directly from the fat in the epicenter of the kidney, disguised as an angiomyolipoma. In this article, we report the case of a 54-year-old female who was diagnosed with a well-differentiated liposarcoma of the kidney and underwent radical nephrectomy. Our objective is to evaluate unique radiological imaging findings and correlate with histopathological analysis to optimize diagnosis.

Expanded experience with cardiovascular black blood cinematic rendering

Black blood cinematic rendering (BBCR) is a newly described preset for cinematic rendering, which creates photorealistic displays from volumetric data sets with the contrast-enhanced blood pool displayed as dark and transparent. That set of features potentially provides for enhanced visualization of endomyocardial and intraluminal pathology, as well as cardiac devices. The similarity of the images to black-blood magnetic resonance imaging (MRI) may allow for expansion of the evaluation of certain types of pathology into patient populations unable to undergo MRI. In the emergency setting, the rapid acquisition time and reasonable post-processing time make this technique clinically feasible. In this expanded experience, we demonstrate an expanded clinical experience with the BBCR technique, highlighting the applications for intraluminal cardiovascular evaluation, especially focused on current and potential emergency radiology applications.

Cinematic rendering of non-traumatic thoracic aorta emergencies: a new look at an old problem

Non-traumatic thoracic aorta emergencies are acute conditions associated with substantial morbidity and mortality. In the emergency setting, timely detection of aortic injury through radiological imaging is crucial for prompt treatment planning and favorable patient outcomes. 3D cinematic rendering (CR), a novel rendering algorithm for computed tomography (CT) image processing, allows for life-like visualization of spatial details and contours of highly complex anatomic structures such as the thoracic aorta and its vessels, generating a photorealistic view that not just adds to diagnostic confidence, but is especially useful for non-radiologists, including surgeons and emergency medicine physicians. In this pictorial review, we demonstrate the utility of CR in the setting of non-traumatic thoracic aorta emergencies through 10 cases that were processed at a standalone 3D CR station at the time of presentation, including its role in diagnosis and management.

Cinematic Rendering of Pancreatic Neuroendocrine Tumours: Opportunities for Clinical Implementation: Part 2: Preoperative Planning and Evaluation of Metastatic Disease

Pancreatic neuroendocrine tumours (PNETs) are a rare subset of pancreatic tumours that have historically comprised up to 3% of all clinically detected pancreatic tumours. In recent decades, however, advancements in imaging have led to an increased incidental detection rate of PNETs and imaging has played an increasingly central role in the initial diagnostics and surgical planning of these tumours. Cinematic rendering (CR) is a 3D post-processing technique that generates highly photorealistic images through more realistically modelling the path of photons through the imaged volume. This allows for more comprehensive visualization, description, and interpretation of anatomical structures. In this 2-part review article, we present the first description of the various CR appearances of PNETs in the reported literature while providing commentary on the unique clinical opportunities afforded by the adjunctive utilization of CR in the workup of these rare tumours. This second instalment focuses on the applications of CR in optimizing preoperative planning of PNETs.

Cinematic Rendering of Pancreatic Neuroendocrine Tumours: Opportunities for Clinical Implementation: Part 1: Tumour Detection and Characterization

Pancreatic neuroendocrine tumours (PNETs) are a rare subset of pancreatic tumours that have historically comprised up to 3% of all clinically detected pancreatic tumours. In recent decades, however, advancements in imaging have led to an increased incidental detection rate of PNETs and imaging has played an increasingly central role in the initial diagnostics and surgical planning of these tumours. Cinematic rendering (CR) is a 3D post-processing technique that generates highly photorealistic images through more realistically modelling the path of photons through the imaged volume. This allows for more comprehensive visualization, description, and interpretation of anatomical structures. In this 2-part review article, we present the first description of the various CR appearances of PNETs in the reported literature while providing commentary on the unique clinical opportunities afforded by the adjunctive utilization of CR in the workup of these rare tumours. The first of these 2 instalments highlights the utility of CR in optimizing PNET detection and characterization.

Factors associated with radiological misstaging of pancreatic ductal adenocarcinoma: A retrospective observational study

PURPOSE

Accurate staging of disease is vital in determining appropriate care for patients with pancreatic ductal adenocarcinoma (PDAC). It has been shown that the quality of scans and the experience of a radiologist can impact computed tomography (CT) based assessment of disease. The aim of the current study was to evaluate the impact of the rereading of outside hospital (OH) CT by an expert radiologist and a repeat pancreatic protocol CT (PPCT) on staging of disease.

METHODS

Patients evaluated at the our institute's pancreatic multidisciplinary clinic (2006 to 2014) with OH scan and repeat PPCT performed within 30 days were included. In-house radiologists staged disease using OH scans and repeat PPCT, and factors associated with misstaging were determined.

RESULTS

The study included 100 patients, with a median time between OH scan and PPCT of 19 days (IQR: 13-23 days.) Stage migration was mostly accounted for by upstaging of disease (58.8 % to 83.3 %) in all comparison groups. When OH scans were rereviewed, 21.5 % of the misstaging was due to missed metastases, however, when rereads were compared to the PPCT, occult metastases accounted for the majority of misstaged patients (62.5 %). Potential factors associated with misstaging were primarily related to imaging technique.

CONCLUSION

A repeat PPCT results in increased detection of metastatic disease that rereviews of OH scans may otherwise miss. Accessible insurance coverage for repeat PPCT imaging even within 30 days of an OH scan could help optimize delivery of care and alleviate burdens associated with misstaging.

Gastrointestinal basidiobolomycosis masquerading as cancer

Gastrointestinal basidiobolomycosis is an unusual fungal infection caused by Basidiobolus ranarum, a saprophytic fungus primarily found in soil and decaying vegetables. Basidiobolomycosis typically presents as a chronic subcutaneous swelling and rarely infects the gastrointestinal tract. Thus, the infrequency of gastrointestinal infections, along with nonspecific clinical symptoms, often results in misdiagnosed cases and delays in treatment. In this article, we report the case of a 68-year-old male with gastrointestinal basidiobolomycosis masquerading as metastatic cancer. We focus on the use of radiological imaging modalities and histopathological analysis to optimize the diagnosis and treatment of this rare gastrointestinal infection.

Primary diffuse large B-cell lymphoma of the cecum

When found in the cecum or rectosigmoid junction, primary colorectal B-cell lymphoma is a rare malignant non-Hodgkin's lymphoma often associated with an unfavorable prognosis. Due to the nonspecific clinical symptoms, these uncommon tumors are often left undefined or misdiagnosed, resulting in delays in treatment and adverse patient outcomes. Contrast-enhanced computed tomography is the most commonly used medical imaging process for primary colorectal lymphoma, but due to the rarity of this disorder, accurate imaging diagnosis remains a clinical challenge. In this article, we report the case of a 70-year-old male who was diagnosed with primary B-cell lymphoma of the cecum. We focus on improving diagnosis through the utilization of radiological imaging modalities, particularly computed tomography (CT) and fluorine-18-fluorodeoxyglucose positron emission tomography/computed tomography (18-F-FDG PET/CT). While imaging modalities are important in recognizing colonic lymphomas, there are no pathognomonic imaging features for lymphoma; therefore, biopsy remains necessary for diagnostic confirmation.

CT and MRI of abdominal cancers: current trends and perspectives in the era of radiomics and artificial intelligence

Abdominal cancers continue to pose daily challenges to clinicians, radiologists and researchers. These challenges are faced at each stage of abdominal cancer management, including early detection, accurate characterization, precise assessment of tumor spread, preoperative planning when surgery is anticipated, prediction of tumor aggressiveness, response to therapy, and detection of recurrence. Technical advances in medical imaging, often in combination with imaging biomarkers, show great promise in addressing such challenges. Information extracted from imaging datasets owing to the application of radiomics can be used to further improve the diagnostic capabilities of imaging. However, the analysis of the huge amount of data provided by these advances is a difficult task in daily practice. Artificial intelligence has the potential to help radiologists in all these challenges. Notably, the applications of AI in the field of abdominal cancers are expanding and now include diverse approaches for cancer detection, diagnosis and classification, genomics and detection of genetic alterations, analysis of tumor microenvironment, identification of predictive biomarkers and follow-up. However, AI currently has some limitations that need further refinement for implementation in the clinical setting. This review article sums up recent advances in imaging of abdominal cancers in the field of image/data acquisition, tumor detection, tumor characterization, prognosis, and treatment response evaluation.

CT angiography for characterization of advanced placenta accreta spectrum: indications, risks, and benefits

Placenta accreta spectrum disorder (PASD) encompasses various types of abnormal placentation in which chorionic villi directly adhere to or invade the myometrium. The incidence of PASD has dramatically risen in the US over the past 3 decades owing to the increased rates of patients undergoing cesarean sections. While PASD remains a significant cause of maternal morbidity and mortality, accurate prenatal identification and characterization of PASD is associated with improved outcomes. Although ultrasound is the first-line imaging modality in the evaluation of PASD, with MRI serving as an adjunct, computed tomography angiography (CTA) may also offer unique diagnostic advantages in cases of advanced PASD by providing superior visualization of placental and abdominopelvic vasculature and enabling the creation of comprehensive vascular maps to roadmap complex surgical interventions. This paper represents the first evaluation of CTA as a diagnostic tool and operative planning aid in this context. Appropriate indications and diagnostic advantages of CTA in this setting are reviewed, and key multimodal imaging features of normal and abnormal placentation are highlighted.

Cinematic rendering of solid pseudopapillary tumors: Augmenting diagnostics of an increasingly encountered tumor

Pancreatic solid pseudopapillary tumors (SPTs) are a rare subset of pancreatic neoplasms, accounting for under 2 % of exocrine pancreatic tumors. The incidence of SPTs has shown a significant increase in the past two decades, attributed to heightened cross-sectional imaging utilization. These tumors often present with nonspecific clinical symptoms, making imaging a crucial tool in their detection and diagnosis. Cinematic rendering (CR) is an advanced 3D post-processing technique that generates highly photorealistic realistic images by accurately modeling the interaction of light within the imaged volume. This allows improved visualization of anatomic structures which holds potential to improve diagnostics. In this manuscript we present the first description of CR appearances of SPTs in the reported literature. Through showcasing a range of cases, we highlight the potential of CR in illustrating the diverse imaging characteristics of these unique neoplasms.

The future of radiology and radiologists: AI is pivotal but not the only change afoot

Uncertainty regarding the future of radiologists is largely driven by the emergence of artificial intelligence (AI). If AI succeeds, will radiologists continue to monopolize imaging services? As AI accuracy progresses with alacrity, radiology reads will be excellent. Some articles show that AI can make non-radiologists experts. However, eminent figures within AI development have expressed concerns over its possible adverse uses. Bad actors, not bad AI, may account for a future in which AI is not as successful as we might hope and, as some fear, even pernicious. More relevant to current predictions over the course of AI in medicine, and radiology in particular, is how the evolution of AI is often seen in a vacuum. We cannot predict the future with certainty. But as we contemplate the potential impact of AI in radiology, we should remember that radiology does not exist in a vacuum; while AI is changing, so is everything else. The medical system, not to mention the world's population, has been severely impacted by the global COVID-19 pandemic and numerous experts expect future worldwide pandemics. We cannot predict the condition of the healthcare system in two decades but may assume that radiology will likely remain critical in any future medical practice. For now, we should responsibly use all tools at our disposal (including AI) to make ourselves as indispensable as possible. Our best chances of remaining relevant and instrumental to patient care will likely hinge on our ability to lead the changes rather than be passively impacted by them.

Deep neural network-based segmentation of normal and abnormal pancreas on abdominal CT: evaluation of global and local accuracies

PURPOSE

Delay in diagnosis can contribute to poor outcomes in pancreatic ductal adenocarcinoma (PDAC), and new tools for early detection are required. Recent application of artificial intelligence to cancer imaging has demonstrated great potential in detecting subtle early lesions. The aim of the study was to evaluate global and local accuracies of deep neural network (DNN) segmentation of normal and abnormal pancreas with pancreatic mass.

METHODS

Our previously developed and reported residual deep supervision network for segmentation of PDAC was applied to segment pancreas using CT images of potential renal donors (normal pancreas) and patients with suspected PDAC (abnormal pancreas). Accuracy of DNN pancreas segmentation was assessed using DICE simulation coefficient (DSC), average symmetric surface distance (ASSD), and Hausdorff distance 95% percentile (HD95) as compared to manual segmentation. Furthermore, two radiologists semi-quantitatively assessed local accuracies and estimated volume of correctly segmented pancreas.

RESULTS

Forty-two normal and 49 abnormal CTs were assessed. Average DSC was 87.4 ± 3.1% and 85.5 ± 3.2%, ASSD 0.97 ± 0.30 and 1.34 ± 0.65, HD95 4.28 ± 2.36 and 6.31 ± 6.31 for normal and abnormal pancreas, respectively. Semi-quantitatively, ≥95% of pancreas volume was correctly segmented in 95.2% and 53.1% of normal and abnormal pancreas by both radiologists, and 97.6% and 75.5% by at least one radiologist. Most common segmentation errors were made on pancreatic and duodenal borders in both groups, and related to pancreatic tumor including duct dilatation, atrophy, tumor infiltration and collateral vessels.

CONCLUSION

Pancreas DNN segmentation is accurate in a majority of cases, however, minor manual editing may be necessary; particularly in abnormal pancreas.

Corrigendum to: 'CT of a pulmonary artery intimal sarcoma: A case report' [Radiology Case Reports 18 (2023) 3840-3843]

[This corrects the article DOI: 10.1016/j.radcr.2023.08.029.].

Three-dimensional CT cinematic rendering of adrenal masses: Role in tumor analysis and management

The adrenal gland is home to an array of complex physiological and neoplastic disease processes. While dedicated adrenal computed tomography (CT) is the gold standard imaging modality for adrenal lesions, there exists significant overlap among imaging features of adrenal pathology. This can often make radiological diagnosis and subsequent determination of the optimal surgical approach challenging. Cinematic rendering (CR) is a novel CT post-processing technique that utilizes advanced light modeling to generate highly photorealistic anatomic visualization. This generates unique prospects in the evaluation of adrenal masses. As one of the first large tertiary care centers to incorporate CR into routine diagnostic workup, our preliminary experience with using CR has been positive, and we have found CR to be a valuable adjunct during surgical planning. Herein, we highlight the unique utility of CR techniques in the workup of adrenal lesions and provide commentary on the opportunities and obstacles associated with the application of this novel display method in this setting.

Accurate non-invasive grading of nonfunctional pancreatic neuroendocrine tumors with a CT derived radiomics signature

PURPOSE

The purpose of this study was to develop a radiomics-signature using computed tomography (CT) data for the preoperative prediction of grade of nonfunctional pancreatic neuroendocrine tumors (NF-PNETs).

MATERIALS AND METHODS

A retrospective study was performed on patients undergoing resection for NF-PNETs between 2010 and 2019. A total of 2436 radiomic features were extracted from arterial and venous phases of pancreas-protocol CT examinations. Radiomic features that were associated with final pathologic grade observed in the surgical specimens were subjected to joint mutual information maximization for hierarchical feature selection and the development of the radiomic-signature. Youden-index was used to identify optimal cutoff for determining tumor grade. A random forest prediction model was trained and validated internally. The performance of this tool in predicting tumor grade was compared to that of EUS-FNA sampling that was used as the standard of reference.

RESULTS

A total of 270 patients were included and a fusion radiomic-signature based on 10 selected features was developed using the development cohort (n = 201). There were 149 men and 121 women with a mean age of 59.4 ± 12.3 (standard deviation) years (range: 23.3-85.0 years). Upon internal validation in a new set of 69 patients, a strong discrimination was observed with an area under the curve (AUC) of 0.80 (95% confidence interval [CI]: 0.71-0.90) with corresponding sensitivity and specificity of 87.5% (95% CI: 79.7-95.3) and 73.3% (95% CI: 62.9-83.8) respectively. Of the study population, 143 patients (52.9%) underwent EUS-FNA. Biopsies were non-diagnostic in 26 patients (18.2%) and could not be graded due to insufficient sample in 42 patients (29.4%). In the cohort of 75 patients (52.4%) in whom biopsies were graded the radiomic-signature demonstrated not different AUC as compared to EUS-FNA (AUC: 0.69 vs. 0.67; P = 0.723), however greater sensitivity (i.e., ability to accurately identify G2/3 lesion was observed (80.8% vs. 42.3%; P < 0.001).

CONCLUSION

Non-invasive assessment of tumor grade in patients with PNETs using the proposed radiomic-signature demonstrated high accuracy. Prospective validation and optimization could overcome the commonly experienced diagnostic uncertainty in the assessment of tumor grade in patients with PNETs and could facilitate clinical decision-making.

Cinematic rendering in the evaluation of complex vascular injury of the lower extremities: how we do it

Lower extremity trauma is one of the most common injury patterns seen in emergency medical and surgical practice. Vascular injuries occur in less than one percent of all civilian fractures. However, if not treated promptly, such injuries can lead to ischemia and death. Computed tomography angiography (CTA) is the non-invasive imaging gold standard and plays a crucial part in the decision-making process for treating lower extremity trauma. A novel, FDA-approved 3D reconstruction technique known as cinematic rendering (CR) yields photorealistic reconstructions of lower extremity vascular injuries depicting clinically important aspects of those injuries, aiding in patient workup and surgical planning, and thus improving patient outcomes. In this article, we provide clinical examples of the use of CR in evaluating lower extremity vascular injuries, including the relationship of these injuries to adjacent osseous structures and overlying soft tissues, and its role in management of lower extremity trauma.

Cinematic Rendering of Gastrointestinal Stromal Tumors: A Review of Current Possibilities and Future Developments

Gastrointestinal stromal tumors (GISTs) are defined as CD117-positive primary, spindled or epithelioid, mesenchymal tumors of the gastrointestinal tract, omentum, or mesentery. While computed tomography (CT) is the recommended imaging modality for GISTs, overlap in imaging features between GISTs and other gastrointestinal tumors often make radiological diagnosis and subsequent selection of the optimal therapeutic approach challenging. Cinematic rendering is a novel CT post-processing technique that generates highly photorealistic anatomic images based on a unique lighting model. The global lighting model produces high degrees of surface detail and shadowing effects that generate depth in the final three-dimensional display. Early studies have shown that cinematic rendering produces high-quality images with enhanced detail by comparison with other three-dimensional visualization techniques. Cinematic rendering shows promise in improving the visualization of enhancement patterns and internal architecture of abdominal lesions, local tumor extension, and global disease burden, which may be helpful for lesion characterization and pretreatment planning. This article discusses and illustrates the application of cinematic rendering in the evaluation of GISTs and the unique benefit of using cinematic rendering in the workup of GIST with a specific emphasis on tumor characterization and preoperative planning.

CT of a pulmonary artery intimal sarcoma: A case report

Pulmonary artery intimal sarcomas are rare, malignant tumors often associated with poor prognoses. These highly lethal tumors are difficult to distinguish given their nonspecific symptoms and challenging imaging interpretations, often being misdiagnosed as acute or chronic pulmonary embolisms, tumor emboli, or mediastinal masses. Given the poor survival rate associated with this malignancy and surgical resection is the absolute choice of treatment, early and accurate diagnoses are essential. In this article, we report the case of a 78-year-old female who was diagnosed with a pulmonary artery intimal sarcoma. We focus on optimizing diagnosis and management through the application of radiological imaging modalities, specifically computed tomography angiography scans.

Concepts and techniques for revascularization of replaced hepatic arteries in pancreatic head resections

BACKGROUND

The relationship of pancreatic ductal adenocarcinoma (PDAC) to important peripancreatic vasculature dictates resectability. As per the current guidelines, tumors with extensive, unreconstructible venous or arterial involvement are staged as unresectable locally advanced pancreatic cancer (LAPC). The introduction of effective multiagent chemotherapy and development of surgical techniques, have renewed interest in local control of PDAC. High-volume centers have demonstrated safe resection of short-segment encasement of the common hepatic artery. Knowledge of the unique anatomy of the patient's vasculature is important in surgical planning of these complex resections. Hepatic artery anomalies are common and insufficient knowledge can result in iatrogenic vascular injury during surgery.

METHODS AND RESULTS

Here, we discuss different strategies to resect and reconstruct replaced hepatic arteries during pancreatectomy for PDAC to ensure restoration of adequate blood flow to the liver. Strategies include various arterial transpositions, in-situ interposition grafts and the use of extra-anatomic jump grafts.

CONCLUSION

These surgical techniques allow more patients to undergo the only available curative treatment currently available for PDAC. Moreover, these improvements in surgical techniques highlight the shortcoming of current resectability criteria, which rely mainly on local tumor involvement and technical resectability, and disregards tumor biology.

Radiologists' Expectations of Artificial Intelligence in Pancreatic Cancer Imaging: How Good Is Good Enough?

BACKGROUND

Existing (artificial intelligence [AI]) tools in radiology are modeled without necessarily considering the expectations and experience of the end user-the radiologist. The literature is scarce on the tangible parameters that AI capabilities need to meet for radiologists to consider them useful tools.

OBJECTIVE

The purpose of this study is to explore radiologists' attitudes toward AI tools in pancreatic cancer imaging and to quantitatively assess their expectations of these tools.

METHODS

A link to the survey was posted on the www.ctisus.com website, advertised in the www.ctisus.com email newsletter, and publicized on LinkedIn, Facebook, and Twitter accounts. This survey asked participants about their demographics, practice, and current attitudes toward AI. They were also asked about their expectations of what constitutes a clinically useful AI tool. The survey consisted of 17 questions, which included 9 multiple choice questions, 2 Likert scale questions, 4 binary (yes/no) questions, 1 rank order question, and 1 free text question.

RESULTS

A total of 161 respondents completed the survey, yielding a response rate of 46.3% of the total 348 clicks on the survey link. The minimum acceptable sensitivity of an AI program for the detection of pancreatic cancer chosen by most respondents was either 90% or 95% at a specificity of 95%. The minimum size of pancreatic cancer that most respondents would find an AI useful at detecting was 5 mm. Respondents preferred AI tools that demonstrated greater sensitivity over those with greater specificity. Over half of respondents anticipated incorporating AI tools into their clinical practice within the next 5 years.

CONCLUSION

Radiologists are open to the idea of integrating AI-based tools and have high expectations regarding the performance of these tools. Consideration of radiologists' input is important to contextualize expectations and optimize clinical adoption of existing and future AI tools.

Accelerating artificial intelligence: How federated learning can protect privacy, facilitate collaboration, and improve outcomes

Cross-institution collaborations are constrained by data-sharing challenges. These challenges hamper innovation, particularly in artificial intelligence, where models require diverse data to ensure strong performance. Federated learning (FL) solves data-sharing challenges. In typical collaborations, data is sent to a central repository where models are trained. With FL, models are sent to participating sites, trained locally, and model weights aggregated to create a master model with improved performance. At the 2021 Radiology Society of North America's (RSNA) conference, a panel was conducted titled "Accelerating AI: How Federated Learning Can Protect Privacy, Facilitate Collaboration and Improve Outcomes." Two groups shared insights: researchers from the EXAM study (EMC CXR AI Model) and members of the National Cancer Institute's Early Detection Research Network's (EDRN) pancreatic cancer working group. EXAM brought together 20 institutions to create a model to predict oxygen requirements of patients seen in the emergency department with COVID-19 symptoms. The EDRN collaboration is focused on improving outcomes for pancreatic cancer patients through earlier detection. This paper describes major insights from the panel, including direct quotes. The panelists described the impetus for FL, the long-term potential vision of FL, challenges faced in FL, and the immediate path forward for FL.

Evaluation of extensive inflammatory conditions of the bowel using three-dimensional CT cinematic rendering: focus on inflammatory bowel disease

Inflammatory conditions that affect long segments of bowel and/or the mesentery and mesenteric vasculature are a common cause of emergency department visits and evaluation by cross-sectional imaging. Inflammatory bowel disease, specifically Crohn disease and ulcerative colitis, can be unsuspected at presentation and may only be eventually diagnosed based on initial imaging findings. Traditional 2D axial reconstructions and multi-planar reformations can be limited in their ability to globally assess the extent of disease. 3D methods such as volume rendering (VR) are often used as adjunctive means of visualizing the pathology in such patients. Recently, a novel technique known as cinematic rendering (CR) has emerged, utilizing advanced lighting models and ray tracing to simulate photon interactions with tissues, resulting in realistic shadows and enhanced surface detail compared to VR. Generating CR images from select presets takes an experienced radiologist approximately 5 min, meaning that the technique can be incorporated into meaningful emergency department workflows. Given the apparent advantages of CR, we highlight its application in a series of cases in which patients had inflammatory conditions that affected long segments of bowel and/or involved the mesentery, particularly those patients with inflammatory bowel disease, but also including patients with mesenteric venous thrombosis and lymphedema. Those conditions included inflammatory bowel disease, mesenteric venous thrombosis, and bowel lymphedema. We present examples of those conditions in this pictorial essay and describe the potential of CR to visualize key findings. As CR exhibits possible advantages, further studies are warranted to support its broader clinical adoption and assess its efficacy in diagnosing and guiding managing of inflammatory conditions in emergency settings.

Radiation-induced osteosarcoma of the chest wall after treatment for unresectable thymoma

Secondary osteosarcoma is a rare complication of radiation therapy for a primary tumor. Here we report a unique presentation of radiation-induced osteosarcoma of the chest wall after radiation treatment for thymoma. This patient underwent multiple imaging studies, including magnetic resonance imaging and computed tomography with cinematic rendering. Diagnosis of osteosarcoma was confirmed through imaging features and histology. Several surgical procedures were performed to evaluate and attempt resection of the tumor, but ultimately the tumor location and involvement prevented adequate resection and chemotherapy was initiated. This case highlights the importance of identifying clear cumulative dose thresholds for radiation therapy and rare complications of radiotherapy.

Systematic Evaluation of Imaging Features of Early Bladder Cancer Using Computed Tomography Performed before Pathologic Diagnosis

BACKGROUND

Bladder cancer is the sixth most common malignancy in the United States (US). Despite its high prevalence and the significant potential benefits of early detection, no reliable, cost-effective screening algorithm exists for asymptomatic patients at risk. Nonetheless, reports of incidentally identified early bladder cancer on CT/MRI scans performed for other indications are emerging in the literature. This represents a new opportunity for early detection, with over 80 million CT scans performed in the US yearly, 40% of which are abdominopelvic CTs. This investigation aims to define the imaging features of early bladder cancer, with the mission of facilitating early diagnosis.

METHODS

Following IRB approval with a waiver of informed consent, a retrospective review was performed, identifying 624 patients with non-muscle-invasive bladder cancer diagnosed at Johns Hopkins Hospital between 2000 and 2019. Of these patients, 99 patients underwent pelvic CT within the 5 years preceding pathologic diagnosis. These imaging studies were reviewed retrospectively to evaluate for the presence and features of any focal bladder wall abnormality.

RESULTS

Median age at the time of pathologic diagnosis was 70 years (range: 51-88 years), and 82% (81/99) of patients were male. A total of 226 CT studies were reviewed. The number of studies per patient ranged from 1 to 33. Median time interval between all available imaging and pathologic diagnosis was 14 months. A total of 62% (141/226) of the scans reviewed were performed for indications other than suspected urinary tract cancer (UTC). A bladder wall mass was visualized in 67% (66/99) of patients and on 35% (78/226) of scans performed before diagnosis. The majority (84%, 67/80) of masses were intraluminal. Mean transverse long- and short-axis measurements were 24 mm and 17 mm, respectively, with long dimension measurements ranging between 5 and 59 mm.

CONCLUSIONS

Early bladder cancer was visualized on CT preceding pathologic diagnosis in more than 2/3 of patients, and the majority of scans were performed for indications other than suspected urinary tract cancer/UTC symptoms. These results suggest that cross-sectional imaging performed for other indications can serve as a resource for opportunistic bladder cancer screening, particularly in high-risk patients.

An Approach to Leadership in Academic Medicine: Lessons Learned From the Experience of Dr. John L. Cameron

OBJECTIVE

Dr. John L. Cameron was appointed the chair of surgery at Johns Hopkins in 1984. He subsequently built the largest group of clinician-scientists anywhere in the world who were focused on pancreatic cancer.

MATERIALS AND METHODS

Trainees were selected over the decades to join the group based on characteristics including self-confidence, a sense of humor, a collegial and congenial personality, and a strong previous track record. Resume items such as prior leadership positions, academic achievements, and participation in team sports can all prove to be important predictors for future success.

RESULTS

Many of the trainees that were molded by that group have perpetuated its ideals by pursuing academic careers. Dr Cameron's approach can be distilled to 3 key points: work hard and lead by example, make diamonds by applying the right amount of pressure, and serve your people and give the impression that you are working for your trainees and junior people.

CONCLUSIONS

With those leadership principles, it should still be possible to build successful academic programs, despite the significant challenges that have arisen.