Advanced 3D Visualization and 3D Printing in Radiology.

Since the discovery of X-rays in 1895, medical imaging systems have played a crucial role in medicine by permitting the visualization of internal structures and understanding the function of organ systems. Traditional imaging modalities including Computed Tomography (CT), Magnetic Resonance Imaging (MRI) and Ultrasound (US) present fixed two-dimensional (2D) images which are difficult to conceptualize complex anatomy. Advanced volumetric medical imaging allows for three-dimensional (3D) image post-processing and image segmentation to be performed, enabling the creation of 3D volume renderings and enhanced visualization of pertinent anatomic structures in 3D. Furthermore, 3D imaging is used to generate 3D printed models and extended reality (augmented reality and virtual reality) models. A 3D image translates medical imaging information into a visual story rendering complex data and abstract ideas into an easily understood and tangible concept. Clinicians use 3D models to comprehend complex anatomical structures and to plan and guide surgical interventions more precisely. This chapter will review the volumetric radiological techniques that are commonly utilized for advanced 3D visualization. It will also provide examples of 3D printing and extended reality technology applications in radiology and describe the positive impact of advanced radiological image visualization on patient care.

Three-Dimensional Printed Anatomic Models Derived From Magnetic Resonance Imaging Data: Current State and Image Acquisition Recommendations for Appropriate Clinical Scenarios.

Three-dimensional (3D) printing technologies have been increasingly utilized in medicine over the past several years and can greatly facilitate surgical planning thereby improving patient outcomes. Although still much less utilized compared to computed tomography (CT), magnetic resonance imaging (MRI) is gaining traction in medical 3D printing. The purpose of this study was two-fold: 1) to determine the prevalence in the existing literature of using MRI to create 3D printed anatomic models for surgical planning and 2) to provide image acquisition recommendations for appropriate clinical scenarios where MRI is the most suitable imaging modality. The workflow for creating 3D printed anatomic models from medical imaging data is complex and involves image segmentation of the regions of interest and conversion of that data into 3D surface meshes, which are compatible with printing technologies. CT is most commonly used to create 3D printed anatomic models due to the high image quality and relative ease of performing image segmentation from CT data. As compared to CT datasets, 3D printing using MRI data offers advantages since it provides exquisite soft tissue contrast needed for accurate organ segmentation and it does not expose patients to unnecessary ionizing radiation. MRI, however, often requires complicated imaging techniques and time-consuming postprocessing procedures to generate high-resolution 3D anatomic models needed for 3D printing. Despite these challenges, 3D modeling and printing from MRI data holds great clinical promises thanks to emerging innovations in both advanced MRI imaging and postprocessing techniques. EVIDENCE LEVEL: 2 TECHNICAL EFFICATCY: 5.

CT, US and MRI of xanthine urinary stones: in-vitro and in-vivo analyses.

BACKGROUND: Xanthine urinary stones are a rare entity that may occur in patients with Lesch-Nyhan syndrome receiving allopurinol. There is little literature describing imaging characteristics of these stones, and the most appropriate approach to imaging these stones is therefore unclear. We performed in-vitro and in-vivo analyses of xanthine stones using computed tomography (CT) at different energy levels, ultrasound (US), and magnetic resonance imaging (MRI). METHODS: Five pure xanthine stones from a child with Lesch-Nyhan were imaged in-vitro and in-vivo. CT of the stones was performed at 80 kVp, 100 kVp, 120 kVp and 140 kVp and CT numbers of the stones were recorded in Hounsfield units (HU). US of the stones was performed and echogenicity, acoustic shadowing and twinkle artifact were assessed. MRI of the stones was performed and included T2-weighted, ultrashort echo-time-weighted and T2/T1-weighted 3D bFFE sequences and signal was assessed. RESULTS: In-vitro analysis on CT demonstrated that xanthine stones were radiodense and the average attenuation coefficient did not differ with varying kVp, measuring 331.0 ± 51.7 HU at 80 kVp, 321.4 ± 63.4 HU at 100 kVp, 329.7 ± 54.2 HU at 120 kVp and 328.4 ± 61.1 HU at 140 kVp. In-vivo analysis on CT resulted in an average attenuation of 354 ± 35 HU. On US, xanthine stones where echogenic with acoustic shadowing and twinkle artifact. On MRI, stones lacked signal on all tested sequences. CONCLUSION: Xanthine stone analyses, both in-vitro and in-vivo, demonstrate imaging characteristics typical of most urinary stones: dense on CT, echogenic on US, and lacking signal on MRI. Therefore, the approach to imaging xanthine stones should be comparable to that of other urinary stones.

Hepatic Imaging in Neonates and Young Infants: State of the Art.

Neonatal liver disease is an important source of morbidity in the pediatric population. The manifestation of liver disease in young infants may be different than in older patients, and there are a number of diagnoses that are unique to this age group. Familiarity with these entities is important as imaging plays a key role in the diagnostic workup, and prompt diagnosis is necessary to prevent complications. This article reviews the spectrum of liver pathologies that can manifest in the first 6 months of life and is intended to educate the general radiologist who may be faced with interpretation of neonatal liver imaging. Categories of disease that will be reviewed include cholestatic diseases, tumors, vascular anomalies, and acquired diseases. The authors will also review optimization of ultrasonography (US) and magnetic resonance imaging of the liver and present a systematic method for interpretation of neonatal liver US findings in the context of clinical and laboratory findings. © RSNA, 2017.

New Frontiers in Breast Cancer Imaging: The Rise of AI.

Artificial intelligence (AI) has been implemented in multiple fields of medicine to assist in the diagnosis and treatment of patients. AI implementation in radiology, more specifically for breast imaging, has advanced considerably. Breast cancer is one of the most important causes of cancer mortality among women, and there has been increased attention towards creating more efficacious methods for breast cancer detection utilizing AI to improve radiologist accuracy and efficiency to meet the increasing demand of our patients. AI can be applied to imaging studies to improve image quality, increase interpretation accuracy, and improve time efficiency and cost efficiency. AI applied to mammography, ultrasound, and MRI allows for improved cancer detection and diagnosis while decreasing intra- and interobserver variability. The synergistic effect between a radiologist and AI has the potential to improve patient care in underserved populations with the intention of providing quality and equitable care for all. Additionally, AI has allowed for improved risk stratification. Further, AI application can have treatment implications as well by identifying upstage risk of ductal carcinoma in situ (DCIS) to invasive carcinoma and by better predicting individualized patient response to neoadjuvant chemotherapy. AI has potential for advancement in pre-operative 3-dimensional models of the breast as well as improved viability of reconstructive grafts.

COVID-19 in Kidney Transplant Recipient and Waitlist Patients: Implications of Chest Radiographic Severity Score.

PURPOSE: To evaluate the chest radiographic severity score (CXR-SS) for coronavirus disease 2019 (COVID-19) patients who are kidney transplant recipients compared with patients on the waitlist. STUDY DESIGN AND METHODS: This retrospective cohort includes 78 kidney transplant recipients (50 men, mean age 59.9±11.9 y) and 59 kidney transplant waitlist patients (33 men, mean age 58.8±10.8 y) diagnosed with COVID-19 between March 15 and May 30, 2020 with reverse transcriptase-polymerase chain reaction. Patient chest radiographs were divided into 6 zones and examined for consolidation. Primary outcome was mortality. Secondary outcomes included hospital admission, intensive care unit (ICU) admission, and intubation. Predictors of our primary and secondary outcomes were identified by bivariate analysis and multivariate regression analysis. RESULTS: No significant difference was found in CXR-SS between 2 groups (P=0.087). Transplant recipients had significantly higher rates of hospitalization (odds ratio, 6.8; 95% confidence interval: 1.7, 39.3; P<0.001), ICU admission (odds ratio, 6.5; 95% confidence interval [CI]: 1.8-35.9; P=0.002), intubation (odds ratio, 11; 95% CI: 2.4-96.9; P=0.001), and mortality (odds ratio, 17; 95% CI: 3.9-153.1; P<0.001). A higher CXR-SS was not predictive of mortality, intubation, or ICU admission. CXR-SS was associated with hospital admission overall (odds ratio, 1.613; 95% CI: 1.04-2.49; P=0.0314). CONCLUSION: The CXR-SS was not predictive of mortality, ICU admission or intubation in our population. Kidney transplant patients with COVID-19 had near universal hospital admission, more than one-third mortality and about a quarter were intubated and admitted to the ICU-all significantly worse outcomes than for patients on the transplant waitlist.

Acute Appendicitis in Pediatric Patients With Sickle Cell Disease: Lower Incidence, More Imaging, and More False-Positives.

OBJECTIVE: Patients with sickle cell disease (SCD) experience recurrent pain crises, which may mimic appendicitis. A prior study found a significantly lower rate of appendicitis in patients with SCD compared with national averages. We investigate the incidence of appendicitis and number of imaging studies for appendicitis in pediatric patients with SCD. METHODS: Using a retrospective study design from a single institution, SCD and control cohorts were created. Inclusion criteria included age 0 to 21years and at least one follow-up appointment within 24 months. Length of observation was calculated from initial presentation to either inpatient admission for appendicitis or last clinic visit. Analysis of an SCD subgroup and a control subset (n = 1,596) was used to compare the number of imaging studies. Incidence rates of appendicitis and number of appendicitis studies were determined. Z-tests, binomial enumeration exact tests, and Fischer's exact tests were used. RESULTS: The SCD cohort included 1,064 patients between January 1, 2001, to December 31, 2014, and the control cohort included 115,109 patients without SCD between January 1, 2011, and December 31, 2011. Incidence rate of appendicitis per 10,000 patient-years was significantly lower in the SCD group compared with controls (2.9 cases versus 10.7 cases per 10,000 patient-years; P = .044). Additionally, the SCD group received significantly more ultrasounds (148 versus 60 per 10,000 patient-years; P< .0001) and CTs (94 versus 27 per 10,000 patient-years; P< .0001) for appendicitis, which remained significant when controlling for race. Patients with SCD also received more false-positive scans. DISCUSSION: Patients with SCD had a significantly lower incidence of appendicitis than controls, yet had a higher number of imaging tests performed for appendicitis. Appendicitis should be viewed as a less common cause of acute abdominal pain in SCD. This consideration should help guide imaging strategy.