Pooley, Robert A.

Three-dimensional (3D) anatomic modeling derived from high-resolution medical imaging, such as computed tomography (CT) and magnetic resonance imaging (MRI), has been increasingly adopted in preclinical testing and device development. This white paper describes a cardiac-specific workflow that integrates 3D printing and silicone molding for support device development and procedural simulation. Patient-derived computed tomography angiography data were segmented using FDA-cleared medical modeling software to isolate the left ventricular anatomy and were further processed in computer-aided design (CAD) to ensure accurate physiological wall thickness and structural fidelity. Material jetting 3D printing was performed on a Stratasys J750 using material distributions designed to mimic the mechanical properties of myocardium, thereby approximating myocardial compliance. In parallel, stereolithography apparatus molds were designed from the left ventricle CAD model to cast transparent, pliable left ventricular models in Sorta-Clear™ 18 silicone. The 3D-printed models preserved intricate morphological detail and were suitable for mechanical manipulation and device deployment studies, whereas silicone models offered tunable mechanical properties, transparency for visualization, and durability for repeated use. Together, these complementary modalities provided rapid manufacturing capability and application-relevant physical representation. Case-specific parameters, strengths, and limitations of both models in enhancing patient care and device testing are highlighted, with relevance to heart failure applications. Current knowledge gaps, workflow and integration challenges, and future opportunities are identified, positioning this work as a reference framework for continued innovation in anatomic modeling. Within the collaborative framework of Mayo Clinic’s Anatomic Modeling Unit and Simulation Center, this integrated modeling workflow demonstrates the value of multidisciplinary collaboration between engineers and clinicians. Clinically, these patient-specific left ventricular models may enable pre-procedural device sizing and positioning and may support simulation of mechanical circulatory support (MCS) deployment while identifying possible anatomic constraints prior to intervention. This workflow has direct applicability in advanced heart failure patients undergoing MCS support, such as the Impella axillary MCS device or the durable LVAD, with potential to reduce procedural uncertainty while reducing complications and improving peri-procedural outcomes. Additionally, these models also serve as high-accuracy educational tools, enabling trainees and multidisciplinary care teams to visualize and possibly rehearse procedural steps while gaining hands-on experience in a risk-free environment.

Purpose Cartilage cap resurfacing is a method to seal a superior semicircular canal dehiscence. The purpose of this study was to evaluate the detection of new bone formation after surgical placement of a cartilage cap over a dehiscent semicircular canal. Methods In this retrospective review, two neuroradiologists blinded to each other’s interpretation reviewed the temporal bones of 20 patients, five of which had a pre-operative computed tomography (CT) exam which was interpreted as unilateral superior semicircular canal dehiscence and with new bone formation following repair on follow-up CT. There were also 15 control subjects. Each neuroradiologist was blinded to history, including post-operative changes, and asked to determine if there was a dehiscence or no dehiscence. Results Out of the 15 controls, there was 100% inter-observer agreement. On the five post-operative patients, there was agreement in 4/5 that there was no dehiscence post-operatively and 1/5 agreement of dehiscence post-operatively, but ectopic bone adjacent to the dehiscence. Conclusion Our results indicate that new bone formation can be seen at the site of cartilage cap placement over the dehiscence and be interpreted as bony closure of the dehiscence.

The purpose of this work was to investigate the performance of currently available magnetic resonance imaging (MRI) for detecting kidney stones, compared to computed tomography (CT) results, and to determine the characteristics of successfully detected stones. Patients who had undergone both abdominal/pelvic CT and MRI exams within 30 days were studied. The images were reviewed by two expert radiologists blinded to the patients’ respective radiological diagnoses. The study consisted of four steps: (1) reviewing the MRI images and determining whether any kidney stone(s) are identified; (2) reviewing the corresponding CT images and confirming whether kidney stones are identified; (3) reviewing the MRI images a second time, armed with the information from the corresponding CT, noting whether any kidney stones are positively identified that were previously missed; (4) for all stones MRI-confirmed on previous steps, the radiologist experts being asked to answer whether in retrospect, with knowledge of size and location on corresponding CT, these stones would be affirmed as confidently identified on MRI or not. In this best-case scenario involving knowledge of stones and their locations on concurrent CT, radiologist experts detected 19% of kidney stones on MRI, with stone size being a major factor for stone identification.

Object Near-infrared spectroscopy (NIRS) offers noninvasive bedside measurement of direct regional cerebral arteriovenous (mixed) brain oxygenation. To validate the accuracy of this monitoring technique, the authors analyzed the statistical correlation of NIRS and CT perfusion with respect to regional cerebral blood flow (CBF) measurements. Methods The authors retrospectively reviewed all cases in which NIRS measurements were obtained at a single, academic neurointensive care unit from February 2008 to June 2011 in which CT perfusion was performed at the same time as NIRS data was collected. Regions of interest were obtained 2.5 cm below the NIRS bifrontal scalp probe on CT perfusion with an average volume between 2 and 4 ml, with mean CBF values used for purposes of analysis. Linear regression analysis was performed for NIRS and CBF values. Results The study included 8 patients (2 men, 6 women), 6 of whom suffered subarachnoid hemorrhage, 1 ischemic stroke, and 1 intracerebral hemorrhage and brain edema. Mean CBF measured by CT perfusion was 61 ml/100 g/min for the left side and 60 ml/100 g/min for the right side, while mean NIRS values were 75 on the right and 74 on the left. Linear regression analysis demonstrated a statistically significant probability value (p < 0.0001) comparing NIRS frontal oximetry and CT perfusion–obtained CBF values. Conclusions The authors demonstrated a linear correlation for frontal NIRS cerebral oxygenation measurements compared with regional CBF on CT perfusion imaging. Thus, frontal NIRS cerebral oxygenation measurement may serve as a useful, noninvasive, bedside intensive care unit monitoring tool to assess brain oxygenation in a direct manner.