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Item Computed tomography angiography-derived extracellular volume fraction predicts early recovery of left ventricular systolic function after transcatheter aortic valve replacement(Oxford University Press, 2021) Han, Donghee; Tamarappoo, Balaji; Klein, Eyal; Tyler, Jeffrey; Chakravarty, Tarun; Otaki, Yuka; Miller, Robert; Eisenberg, Evann; Park, Rebekah; Singh, Siddharth; Shiota, Takahiro; Siegel, Robert; Stegic, Jasminka; Salseth, Tracy; Cheng, Wen; Dey, Damini; Thomson, Louise; Berman, Daniel; Makkar, Raj; Friedman, John; Radiation Oncology, School of MedicineAims: Recovery of left ventricular ejection fraction (LVEF) after aortic valve replacement has prognostic importance in patients with aortic stenosis (AS). The mechanism by which myocardial fibrosis impacts LVEF recovery in AS is not well characterized. We sought to evaluate the predictive value of extracellular volume fraction (ECV) quantified by cardiac CT angiography (CTA) for LVEF recovery in patients with AS after transcatheter aortic valve replacement (TAVR). Methods and results: In 109 pre-TAVR patients with LVEF <50% at baseline echocardiography, CTA-derived ECV was calculated as the ratio of change in CT attenuation of the myocardium and the left ventricular (LV) blood pool before and after contrast administration. Early LVEF recovery was defined as an absolute increase of ≥10% in LVEF measured by post-TAVR follow-up echocardiography within 6 months of the procedure. Early LVEF recovery was observed in 39 (36%) patients. The absolute increase in LVEF was 17.6 ± 8.8% in the LVEF recovery group and 0.9 ± 5.9% in the no LVEF recovery group (P < 0.001). ECV was significantly lower in patients with LVEF recovery compared with those without LVEF recovery (29.4 ± 6.1% vs. 33.2 ± 7.7%, respectively, P = 0.009). In multivariable analysis, mean pressure gradient across the aortic valve [odds ratio (OR): 1.07, 95% confidence interval (CI): 1.03-1.11, P: 0.001], LV end-diastolic volume (OR: 0.99, 95% CI: 0.98-0.99, P: 0.035), and ECV (OR: 0.92, 95% CI: 0.86-0.99, P: 0.018) were independent predictors of early LVEF recovery. Conclusion: Increased myocardial ECV on CTA is associated with impaired LVEF recovery post-TAVR in severe AS patients with impaired LV systolic function.Item Prediction of Revascularization by Coronary CT Angiography using a Machine Learning Ischemia Risk Score(Springer, 2021) Kwan, Alan C.; McElhinney, Priscilla A.; Tamarappoo, Balaji K.; Cadet, Sebastien; Hurtado, Cecilia; Miller, Robert J. H.; Han, Donghee; Otaki, Yuka; Eisenberg, Evann; Ebinger, Joseph E.; Slomka, Piotr J.; Cheng, Victor Y.; Berman, Daniel S.; Dey, Damini; Radiation Oncology, School of MedicineObjectives: The machine learning ischemia risk score (ML-IRS) is a machine learning-based algorithm designed to identify hemodynamically significant coronary disease using quantitative coronary computed tomography angiography (CCTA). The purpose of this study was to examine whether the ML-IRS can predict revascularization in patients referred for invasive coronary angiography (ICA) after CCTA. Methods: This study was a post hoc analysis of a prospective dual-center registry of sequential patients undergoing CCTA followed by ICA within 3 months, referred from inpatient, outpatient, and emergency department settings (n = 352, age 63 ± 10 years, 68% male). The primary outcome was revascularization by either percutaneous coronary revascularization or coronary artery bypass grafting. Blinded readers performed semi-automated quantitative coronary plaque analysis. The ML-IRS was automatically computed. Relationships between clinical risk factors, coronary plaque features, and ML-IRS with revascularization were examined. Results: The study cohort consisted of 352 subjects with 1056 analyzable vessels. The ML-IRS ranged between 0 and 81% with a median of 18.7% (6.4-34.8). Revascularization was performed in 26% of vessels. Vessels receiving revascularization had higher ML-IRS (33.6% (21.1-55.0) versus 13.0% (4.5-29.1), p < 0.0001), as well as higher contrast density difference, and total, non-calcified, calcified, and low-density plaque burden. ML-IRS, when added to a traditional risk model based on clinical data and stenosis to predict revascularization, resulted in increased area under the curve from 0.69 (95% CI: 0.65-0.72) to 0.78 (95% CI: 0.75-0.81) (p < 0.0001), with an overall continuous net reclassification improvement of 0.636 (95% CI: 0.503-0.769; p < 0.0001). Conclusions: ML-IRS from quantitative coronary CT angiography improved the prediction of future revascularization and can potentially identify patients likely to receive revascularization if referred to cardiac catheterization. Key points: • Machine learning ischemia risk from quantitative coronary CT angiography was significantly higher in patients who received revascularization versus those who did not receive revascularization. • The machine learning ischemia risk score was significantly higher in patients with invasive fractional flow ≤ 0.8 versus those with > 0.8. • The machine learning ischemia risk score improved the prediction of future revascularization significantly when added to a standard prediction model including stenosis.Item Single-cell RNA Sequencing Technology Revealed the Pivotal Role of Fibroblast Heterogeneity in Ang II-Induced Abdominal Aortic Aneurysms(Research Square, 2021-11-02) Weng, Yingzheng; Lou, Jiangjie; Bao, Yizong; Cai, Changhong; Zhu, Kefu; Du, Changqing; Chen, Xiaofeng; Tang, Lijiang; Radiation Oncology, School of MedicineThe mechanism of abdominal aortic aneurysm (AAA) has not been fully elucidated. In this study, we aimed to map the cellular heterogeneity, molecular alteration, and functional transformation of angiotensin (Ang) II-induced AAA in mice based on single-cell RNA sequencing (sc-RNA seq) technology. sc-RNA seq was performed on suprarenal abdominal aorta tissue from male Apoe-/- C57BL/6 mice of Ang II-induced AAA and shame models to determine the heterogeneity and phenotypic transformation of all cells. Immunohistochemistry was used to determine the pathophysiological characteristics of AAA. The single-cell trajectory was performed to predict the differentiation of fibroblasts. Finally ligand-receptor analysis was used to evaluate intercellular communication between fibroblasts and smooth muscle cells (SMCs). More than 27,000 cells were isolated and 25 clusters representing 8 types of cells were identified, including fibroblasts, macrophages, endothelial cells, SMCs, T lymphocytes, B lymphocytes, granulocytes, and natural killer cells. During AAA progression, the function and phenotype of different type cells altered separately, including activation of inflammatory cells, alternations of macrophage polarization, phenotypic transformation of vascular smooth muscle cells, and endothelial to mesenchymal transformation. The alterations of fibroblasts were the most conspicuous. Single-cell trajectory revealed the critical reprogramming genes of fibroblasts mainly enriched in regulation of immune system. Finally, the ligand-receptor analysis confirmed that disorder of collagen metabolism led by fibroblasts was one of the most prominent characteristics of Ang II-induced AAA. Our study revealed the cellular heterogeneity of Ang II-induced AAA. Fibroblasts may play a critical role in Ang II-induced AAA progression according to multiple biological functions, including immune regulation and extracellular matrix metabolic balance. Our study may provide us with a different perspective on the etiology and pathogenesis of AAA.Item The cost of elective nodal coverage in prostate cancer: Late quality of life outcomes and dosimetric analysis with 0, 45 or 54 Gy to the pelvis(Elsevier, 2022-06-27) Jensen, Garrett L.; Jhavar, Sameer G.; Ha, Chul S.; Hammonds, Kendall P.; Swanson, Gregory P.; Radiation Oncology, School of MedicinePurpose: Elective pelvic lymph node radiotherapy (PLNRT) in prostate cancer is often omitted from definitive (n = 267) and post prostatectomy (n = 160) radiotherapy (RT) due to concerns regarding toxicity and efficacy. Data comparing patient-reported outcome measures (PROMs) with or without PLNRT is limited. Our long-term supposition is that PLNRT, particularly to higher doses afforded by IMRT, will decrease pelvic failure rate in select patients. We aim to establish the impact of two different PLNRT doses on long term quality of life (QOL). Methods and materials: Prostate cancer patients (n = 428) recorded baseline scores using the Expanded Prostate Cancer Index Composite (EPIC), prior to definitive or post-prostatectomy RT. PLNRT, if given, was prescribed to 45 or 54 Gy at 1.8 Gy per fraction. New EPIC scores were recorded 20-36 months after radiotherapy. Absolute change in each domain subscale and summary score was recorded, along with if these changes met minimally important difference (MID) criteria. A separate multivariate analysis (MVA) was performed for each measure. Subsequent dosimetric analysis was performed. Results: Frequency of a MID decline was significantly greater with PLNRT to 54 Gy for urinary function, incontinence, and overall. No urinary decline was correlated with PLNRT to 45 Gy. PLNRT to 54 Gy was significant for decline in urinary function, bother, irritative, incontinence, and overall score in one or both MVA models while 45 Gy was not. Postoperative status was significant for decline in urinary function, incontinence, and overall. Amongst postoperative patients, there was significantly greater decline in urinary function score in the salvage setting. Neither 54 nor 45 Gy significantly affected bowel subscale or overall score decline. Conclusions: Using conventional fractionation, adding PLNRT to 54 Gy, but not 45 Gy, correlates with worse urinary QOL, with postoperative patients experiencing a steeper decline. PLNRT had no significant impact on bowel QOL with either dose.Item GammaTile for Gliomas: A Single-Center Case Series(Springer Nature, 2021-11) Budnick, Hailey C.; Richardson, Angela M.; Shiue, Kevin; Watson, Gordon; Ng, Sook K.; Le, Yi; Shah, Mitesh V.; Radiation Oncology, School of MedicineGammaTile® (GT Medical Technologies, Tempe, Arizona) is a surgically targeted radiation source, approved by FDA for brachytherapy in primary and secondary brain neoplasms. Each GammaTile is composed of a collagen sponge with four seeds of cesium 131 and is particularly useful in recurrent tumors. We report our early experience in seven patients with recurrent gliomas to assess this type of brachytherapy with particular attention to ease of use, complication, and surgical planning. This study represents a retrospective chart review of surgical use and early clinical outcomes of GammaTile in recurrent gliomas. The number of tiles was planned using pre-operative imaging and dosimetry was planned based on post-operative imaging. Patients were followed during their hospital stay and were followed up after discharge. Parameters such as case length, resection extent, complication, ICU length of stay (LOS), hospital LOS, pre-operative Glasgow Coma Scale (GCS), immediate post-operative GCS, post-operative imaging findings, recurrence at follow-up, length of follow-up, and dosimetry were collected in a retrospective manner. Seven patients were identified that met the inclusion criteria. Two patients were diagnosed with recurrent glioblastoma multiforme (GBM), one lower-grade glioma that recurred as a GBM, one GBM that recurred as a gliosarcoma, and two recurrent oligodendrogliomas. We found that operation time, ICU LOS, hospital LOS, pre- and post-operative GCS, and post-operative complications were within the expected ranges for tumor resection patients. Further, dosimetry data suggests that six out of seven patients received adequate radiation coverage, with the seventh having implantation limitations due to nearby organs at risk. We report no postoperative complications that can be attributed to the GammaTiles themselves. In our cohort, we report seven cases where GammaTiles were implanted in recurrent gliomas. No implant-related post-operative complications were identified. This early data suggests that GammaTile can be a safe form of brachytherapy in recurrent gliomas.Item Shape Dependent Motion Interpolants for Planar Objects(ASME, 2023) Liu, Huan; Ge, Qiaode Jeffrey; Langer, Mark P.; Radiation Oncology, School of MedicineKinematics is most commonly about the motion of unbounded spaces. This paper deals with the kinematics of bounded shapes in a plane. This paper studies the problem of motion interpolation of a planar object with its shape taken into consideration. It applies and extends a shape dependent distance measure between two positions in the context of motion interpolation. Instead of using a fixed reference frame, a shape-dependent inertia frame of reference is used for formulating the distance between positions of a rigid object in a plane. The resulting distance function is then decomposed in two orthogonal directions and is used to formulate an interpolating function for the distance functions in these two directions. This leads to a shape dependent interpolation of translational components of a planar motion. In difference to the original concept of Kazerounian and Rastegar that comes with a shape dependent measure of the angular motion, it is assumed in this paper that the angular motion is shape independent as the angular metric is dimensionless. The resulting distance measure is not only a combination of translation and rotation parameters but also depends on the area moments of inertia of the object. It derives the explicit expressions for decomposing the shape dependent distance in two orthogonal directions, which is then used to obtain shape dependent motion interpolants in these directions. The resulting interpolants have similarities to the well-known spherical linear interpolants widely used in computer graphics in that they are defined using sinusoidal functions instead of linear interpolation in Euclidean space. The path of the interpolating motion can be adjusted by different choice of shape parameters. Examples are provided to illustrate the effect of object shapes on the resulting interpolating motions.Item Challenges and Opportunities in Developing an Oncology Clinical Trial Network in the United States Veterans Affairs Health Care System: The VA STARPORT Experience(MDPI, 2024-08-21) Solanki, Abhishek A.; Zheng, Kevin; Skipworth, Alicia N.; Robin, Lisa M.; Leparski, Ryan F.; Henry, Elizabeth; Rettig, Matthew; Salama, Joseph K.; Ritter, Timothy; Jones, Jeffrey; Quek, Marcus; Chang, Michael; Block, Alec M.; Welsh, James S.; Kumar, Aryavarta; Chao, Hann-Hsiang; Chen, Albert C.; Shapiro, Ronald; Bitting, Rhonda L.; Kwon, Robert; Stross, William; Puckett, Lindsay; Wong, Yu-Ning; Nickols, Nicholas G.; Carlson, Kimberly; VA STARPORT Investigators Group; Radiation Oncology, School of MedicineThe United States Veterans Affairs (VA) Health Care System has a strong history of conducting impactful oncology randomized clinical trials (RCTs). We developed a phase II/III RCT to test the use of metastasis-directed therapy in Veterans with oligometastatic prostate cancer (OMPC)-the first VA RCT in OMPC that leverages novel imaging and advanced radiotherapy techniques. To accomplish this, we developed a clinical trial network to conduct the study. In this manuscript, we describe several challenges we encountered in study development/conduct and our strategies to address them, with the goal of helping investigators establish robust study networks to conduct clinical trials. In the study start-up, we encountered challenges in timely site activation, and leveraged project management to maximize efficiency. Additionally, there were several changes in the clinical paradigms in imaging and treatment that led to protocol amendments to ensure maximum equipoise, recruitment, and impact of the study. Specifically, we amended the trial to add de novo OMPC patients (from initially only recurrent OMPC) and expanded the study to allow up to 10 metastases (from initially five). Finally, in order to maintain local study team engagement, we developed initiatives to maximize collaboration and add value to the overall clinical program through study participation.Item On the Construction of Confidence Regions for Uncertain Planar Displacements(ASME, 2024) Yu, Zihan; Ge, Qiaode Jeffrey; Langer, Mark P.; Arbab, Mona; Radiation Oncology, School of MedicineThis paper studies the statistical concept of confidence region for a set of uncertain planar displacements with a certain level of confidence or probabilities. Three different representations of planar displacements are compared in this context and it is shown that the most commonly used representation based on the coordinates of the moving frame is the least effective. The other two methods, namely the exponential coordinates and planar quaternions, are equally effective in capturing the group structure of SE(2). However, the former relies on the exponential map to parameterize an element of SE(2), while the latter uses a quadratic map, which is often more advantageous computationally. This paper focus on the use of planar quaternions to develop a method for computing the confidence region for a given set of uncertain planar displacements. Principal component analysis (PCA) is another tool used in our study to capture the dominant direction of movements. To demonstrate the effectiveness of our approach, we compare it to an existing method called rotational and translational confidence limit (RTCL). Our examples show that the planar quaternion formulation leads to a swept volume that is more compact and more effective than the RTCL method, especially in cases when off-axis rotation is present.Item On the Computation of Mean and Variance of Spatial Displacements(ASME, 2024) Ge, Qiaode Jeffrey; Yu, Zihan; Arbab, Mona; Langer, Mark P.; Radiation Oncology, School of MedicineThis paper studies the problem of computing an average (or mean) displacement from a set of given spatial displacements using three types of parametric representations: Euler angles and translation vectors, unit quaternions and translation vectors, and dual quaternions. It is shown that the use of Euclidean norm in the space of unit quaternions reduces the problem to that of computing the mean for each quaternion component separately and independently. While the resulting algorithm is simple, a change in the sign of a unit quaternion could lead to an incorrect result. A novel kinematic measure based on dual quaternions is introduced to capture the separation between two spatial displacements. This kinematic measure is used to define the variance of a set of displacements, which is then used to formulate a constrained least squares minimization problem. It is shown that the problem decomposes into that of finding the optimal translation vector and the optimal unit quaternion. The former is simply the centroid of the set of translation vectors and the latter is obtained as the eigenvector corresponding to the least eigenvalue of a 4 × 4 positive definite symmetric matrix. In addition, it is found that the weight factor used in combining rotations and translations in the formulation does not play a role in the final outcome. Examples are provided to show the comparisons of these methods.Item On the Computation of the Average of Spatial Displacements(ASME, 2022) Ge, Q. J.; Yu, Zihan; Arbab, Mona; Langer, Mark; Radiation Oncology, School of MedicineMany applications in biomechanics and medical imaging call for the analysis of the kinematic errors in a group of patients statistically using the average displacement and the standard deviations from the average. This paper studies the problem of computing the average displacement from a set of given spatial displacements using three types of parametric representations: Euler angles and translation vectors, unit quaternions and translation vectors, and dual quaternions. It has been shown that the use of Euclidean norm in the space of unit quaternions reduces the problem to that of computing the average for each quaternion component separately and independently. While the resulting algorithm is simple, the change of the sign of a unit quaternion could lead to an incorrect result. A novel kinematic measure based on dual quaternions is introduced to capture the separation between two spatial displacement. This kinematic measure is then used to formulate a constrained least squares minimization problem. It has been shown that the problem decomposes into that of finding the optimal translation vector and the optimal unit quaternion. The former is simply the centroid of the set of given translation vectors and the latter can be obtained as the eigenvector corresponding to the least eigenvalue of a 4 × 4 positive definite symmetric matrix. It is found that the weight factor used in combining rotations and translations in the formulation does not play a role in the final outcome. Examples are provided to show the comparisons of these methods.