Vertebral Compression Fracture After Spine Stereotactic Body Radiotherapy: The Role of Vertebral Endplate Disruption.

BACKGROUND AND OBJECTIVES: Vertebral compression fracture (VCF) is a common, but serious toxicity of spinal stereotactic body radiotherapy (SBRT). Several variables that place patients at high risk of VCF have previously been identified, including advanced Spinal Instability Neoplastic Score (SINS), a widely adopted clinical decision criterion to assess spinal instability. We examine the role of tumoral endplate (EP) disruption in the risk of VCF and attempt to incorporate it into a simple risk stratification system. METHODS: This study was a retrospective cohort study from a single institution. Demographic and treatment information was collected for patients who received spinal SBRT between 2013 and 2019. EP disruption was noted on pre-SBRT computed tomography scan. The primary end point of 1-year cumulative incidence of VCF was assessed on follow-up MRI and computed tomography scans at 3-month intervals after treatment. RESULTS: A total of 111 patients were included. The median follow-up was 18 months. Approximately 48 patients (43%) had at least one EP disruption. Twenty patients (18%) experienced a VCF at a median of 5.2 months from SBRT. Patients with at least one EP disruption were more likely to experience VCF than those with no EP disruption (29% vs 6%, P < .001). A nomogram was created using the variables of EP disruption, a SINS of ≥7, and adverse histology. Patients were stratified into groups at low and high risk of VCF, which were associated with 2% and 38% risk of VCF ( P < .001). CONCLUSION: EP disruption is a novel risk factor for VCF in patients who will undergo spinal SBRT. A simple nomogram incorporating EP disruption, adverse histology, and SINS score is effective for quickly assessing risk of VCF. These data require validation in prospective studies and could be helpful in counseling patients regarding VCF risk and referring for prophylactic interventions in high-risk populations.

Feasibility, safety, and efficacy of circumferential spine stereotactic body radiotherapy.

Background: With advances in systemic therapy translating to improved survival in metastatic malignancies, spine metastases have become an increasingly common source of morbidity. Achieving durable local control (LC) for patients with circumferential epidural disease can be particularly challenging. Circumferential stereotactic body radiotherapy (SBRT) may offer improved LC for circumferential vertebral and/or epidural metastatic spinal disease, but prospective (and retrospective) data are extremely limited. We sought to evaluate the feasibility, toxicity, and cancer control outcomes with this novel approach to circumferential spinal disease. Methods: We retrospectively identified all circumferential SBRT courses delivered between 2013 and 2019 at a tertiary care institution for post-operative or intact spine metastases. Radiotherapy was delivered to 14-27.5 Gy in one to five fractions. Feasibility was assessed by determining the proportion of plans for which ≥95% planning target volume (PTV) was coverable by ≥95% prescription dose. The primary endpoint was 1-year LC. Factors associated with increased likelihood of local failure (LF) were explored. Acute and chronic toxicity were assessed. Detailed dosimetric data were collected. Results: Fifty-eight patients receiving 64 circumferential SBRT courses were identified (median age 61, KPS ≥70, 57% men). With a median follow-up of 15 months, the 12-month local control was 85% (eight events). Five and three recurrences were in the epidural space and bone, respectively. On multivariate analysis, increased PTV and uncontrolled systemic disease were significantly associated with an increased likelihood of LF; ≥95% PTV was covered by ≥95% prescription dose in 94% of the cases. The rate of new or progressive vertebral compression fracture was 8%. There were no myelitis events or any grade 3+ acute or late toxicities. Conclusions: For patients with circumferential disease, circumferential spine SBRT is feasible and may offer excellent LC without significant toxicity. A prospective evaluation of this approach is warranted.

Toward an artificial intelligence-assisted framework for reconstructing the digital twin of vertebra and predicting its fracture response.

This article presents an effort toward building an artificial intelligence (AI) assisted framework, coined ReconGAN, for creating a realistic digital twin of the human vertebra and predicting the risk of vertebral fracture (VF). ReconGAN consists of a deep convolutional generative adversarial network (DCGAN), image-processing steps, and finite element (FE) based shape optimization to reconstruct the vertebra model. This DCGAN model is trained using a set of quantitative micro-computed tomography (micro-QCT) images of the trabecular bone obtained from cadaveric samples. The quality of synthetic trabecular models generated using DCGAN are verified by comparing a set of its statistical microstructural descriptors with those of the imaging data. The synthesized trabecular microstructure is then infused into the vertebra cortical shell extracted from the patient's diagnostic CT scans using an FE-based shape optimization approach to achieve a smooth transition between trabecular to cortical regions. The final geometrical model of the vertebra is converted into a high-fidelity FE model to simulate the VF response using a continuum damage model under compression and flexion loading conditions. A feasibility study is presented to demonstrate the applicability of digital twins generated using this AI-assisted framework to predict the risk of VF in a cancer patient with spinal metastasis.

A digital twin for simulating the vertebroplasty procedure and its impact on mechanical stability of vertebra in cancer patients.

We present the application of ReconGAN, introduced in a previous study, for simulating the vertebroplasty (VP) operation and its impact on the fracture response of a vertebral body. ReconGAN consists of a Deep Convolutional Generative Adversarial Network (DCGAN) and a finite element based shape optimization algorithm to virtually reconstruct the trabecular bone microstructure. The VP procedure involves injecting shear-thinning liquid bone cement through a needle in the trabecular region to reinforce a diseased or fractured vertebra. To simulate this treatment modality, computational fluid dynamics (CFD) is employed to predict the morphology of the injected cement within the bone microstructure. A power-law equation is utilized to characterize the non-Newtonian shear-thinning behavior of the polymethyl methacrylate (PMMA) bone cement during injection simulations. The CFD model is coupled with the level-set method to simulate the motion of the interface separating bone cement and bone marrow. After predicting the cement morphology, a data co-registration algorithm is employed to transform the CFD model to a high-fidelity continuum damage mechanics (CDM) finite element model of the augmented vertebra for predicting the fracture response. A feasibility study is presented to demonstrate the ability of this CFD-CDM framework to investigate the effect of VP on the mechanical integrity of the vertebral body in a cancer patient with a lytic metastatic tumor.

Finite element analysis of the impact of bone nanostructure on its piezoelectric response.

The piezoelectric response of bone at the submicron scale is analyzed under mechanical loadings using the finite element (FE) method. A new algorithm is presented to virtually reconstruct realistic bone nanostructures, consisting of collagen fibrils embedded in a hydroxyapatite mineral network. This algorithm takes into account potential misalignments between fibrils, as well the porous structure of the mineral phase. A parallel non-iterative mesh generation algorithm is utilized to create high-fidelity FE models for several representative volume elements (RVEs) of the bone with various fibrils volume fractions and misalignments. The piezoelectric response of each RVE is simulated under three types of loading: the longitudinal compression, lateral compression, and shear. The resulting homogenized stress and electric field in RVEs with aligned fibrils showed a linear variation with the fibrils volume fraction under all loading conditions. For RVEs with misaligned fibrils, although more oscillations were observed in homogenized results, their difference with the results of RVEs with aligned fibrils subject to lateral compression and shear loadings were negligible. However, under longitudinal compression, the electric field associated with RVEs with misaligned fibrils was notably higher than that of RVEs with aligned fibrils for the same volume fraction.

Automated Quantification of the Impact of Defects on the Mechanical Behavior of Deoxyribonucleic acid Origami Nanoplates.

Deoxyribonucleic acid (DNA) origami is a method for the bottom-up self-assembly of complex nanostructures for applications, such as biosensing, drug delivery, nanopore technologies, and nanomechanical devices. Effective design of such nanostructures requires a good understanding of their mechanical behavior. While a number of studies have focused on the mechanical properties of DNA origami structures, considering defects arising from molecular self-assembly is largely unexplored. In this paper, we present an automated computational framework to analyze the impact of such defects on the structural integrity of a model DNA origami nanoplate. The proposed computational approach relies on a noniterative conforming to interface-structured adaptive mesh refinement (CISAMR) algorithm, which enables the automated transformation of a binary image of the nanoplate into a high fidelity finite element model. We implement this technique to quantify the impact of defects on the mechanical behavior of the nanoplate by performing multiple simulations taking into account varying numbers and spatial arrangements of missing DNA strands. The analyses are carried out for two types of loading: uniform tensile displacement applied on all the DNA strands and asymmetric tensile displacement applied to strands at diagonal corners of the nanoplate.