Purpose To explore the possible structural and material property features that may facilitate complete glottal closure in an otherwise isotropic physical vocal fold model. Method Seven vocal fold models with different structural features were used in this study. An isotropic model was used as the baseline model, and other models were modified from the baseline model by either embedding fibers aligned along the anterior-posterior direction in the body or cover layer, adding a stiffer outer layer simulating the epithelium layer, or a combination of the two features. Phonation tests were performed with both aerodynamic and acoustic measurements and high-speed imaging of vocal fold vibration. Results Compared to the isotropic one-layer model, the presence of a stiffer epithelium layer led to complete glottal closure along the anterior-posterior direction and strong excitation of high-order harmonics in the resulting acoustic spectra. Similar improvements were observed with fibers embedded in the cover layer, but to a lesser degree. Presence of fibers in the body layer did not yield noticeable improvements in glottal closure or harmonic excitation. Conclusions This study shows that the presence of collagen and elastin fibers and the epithelium layer may play a critical role in achieving complete glottal closure.

Objective The voice effects following laser cordectomy for early glottic cancer are poorly described. We investigated the voice outcomes of subligamentous cordectomy of progressive anterior-posterior extent of excision. Study Design Physical phonatory modeling Methods The influence of vocal fold surgical defects and corresponding scar was experimentally investigated using a self-oscillating physical model of the vocal folds and compared with the baseline model without defects or scar. Results Results showed that increasing anterior-posterior extent of resection increased phonation threshold pressure and flow rate and reduced excitation of high-order harmonics, resulting a more breathy and rough voice production. However, it was found out that voice production was improved with the placement of scar, which increased both excitation of high-order harmonics and the harmonic-to-noise ratio. Conclusions Though large anterior-posterior surgical resections resulted in progressive impact on vocal measures, a limited excision of the vocal fold cover surprisingly demonstrated minimal voice changes. Further investigations are required to define the acceptable extent of surgical resection which may result in optimal voice outcomes. Level of Evidence N/A

Previous studies showed that isotropic vocal fold models often vibrated with incomplete glottal closure at onset despite the vocal folds were in contact at rest. This contrasts with human phonation in which complete glottal closure is observed even during soft phonation with minimal or low laryngeal muscle contraction. Based on previous experimental studies, we hypothesize that this difference in glottal closure patterns is due to the relatively large stiffness in the anterior-posterior direction or the presence of the epithelium layer. These hypotheses were tested in self-oscillating physical vocal-fold models, with anisotropic stiffness conditions simulated by fibers loosely imbedded at different locations in otherwise isotropic vocal folds. The results showed that, compared to isotropic one-layer models, the presence of a stiff epithelium layer led to complete glottal closure along the anterior-posterior direction, increased maximum glottal opening, strong excitation of high-order harmonics in the resulting voice spectra and reduced noise production. Similar improvement in glottal closure and high-order harmonics excitation was observed with fibers in the cover layer, but to a less degree. Presence of fibers in the body-layer led to reduced maximum glottal opening but did not yield noticeable improvement in glottal closure and harmonic excitation. [Work supported by NIH.]

Introduction: Adverse remodeling of the left ventricle (LV) after myocardial infarction (MI) results in abnormal tissue biomechanics and impaired cardiac function, ultimately leading to heart failure. We hypothesized that intramyocardial delivery of engineered stromal cell-derived factor 1α analog (ESA), our previously-developed supra-efficient pro-angiogenic chemokine, preserves biaxial LV mechanical properties after MI. Methods: Male Wistar rats (n=46) underwent sham surgery (n=15) or permanent left anterior descending coronary artery ligation (n=31). Rats sustaining MI were randomized for intramyocardial injections of either saline (100 μL, n=15) or ESA (6 μg/kg, n=16), delivered at standardized peri-infarct sites. After 4 weeks, echocardiography was performed, and the hearts were explanted. Biaxial tensile testing of the anterior LV wall was performed using a strain-controlled biaxial load frame (Fig. 1A), producing up to physiologic circumferential and longitudinal strains (ε=20%, each). The modulus was determined along each axis, and maximum shear stress was calculated as a composite metric of the tissue’s response to physiologic strains. Data are expressed as mean±SEM. Results: At 4 weeks post-MI, ESA-treated hearts had smaller end-diastolic LV internal dimension (6.89±0.27 cm vs 7.69±0.22 cm, p=0.03) and improved ejection fraction (63.7±2.9% vs 49.4±4.4%, p=0.01) compared to saline-injected controls. Hearts treated with ESA exhibited lower moduli than saline controls in both the circumferential (269.4±33.2 kPa vs 431.5±55.6 kPa, p=0.02) and longitudinal axes (182.4±25.0 kPa vs 332.3±51.2 kPa, p=0.02, Fig. 1B). The maximum shear stress for ESA-treated hearts was significantly reduced compared to that for saline controls (5.8±0.8 kPa vs 9.0±1.2 kPa, p=0.03) and was similar to that for sham controls (Fig. 1C). Conclusion: Intramyocardial ESA injection mitigates post-MI tissue stiffening and preserves biaxial LV mechanical properties.

Introduction: Current guidelines for elective surgery of ascending thoracic aortic aneurysms (aTAAs) use aneurysm size as primary determinant for risk stratification of adverse events. Biomechanically, dissection may occur when wall stress exceeds wall strength. A widespread method for stress analysis is structural finite-element analysis (FEA). Patient-specific aortic geometries are easily obtainable and stress distributions can potentially predict risk of dissection. However, FEA is a time-consuming and difficult procedure. To bypass this issue, a recent study has developed the first deep learning (DL) approach for a fast and accurate estimation of aortic wall stress distributions. Hypothesis: In this study, we assessed the hypothesis that this deep learning approach can be applied to a large clinical dataset. Model performance was measured by comparing FEA and DL stress predictions in parallel. Methods: Patients with aTAA (n = 169) were studied. Patient-specific aneurysm geometries were obtained from ECG-gated computed tomography. Shapes were represented by hexahedral meshes with 9648 nodes and 6336 solid elements. FEA peak wall stresses and stress distributions were determined using LS-DYNA software with user-defined fiber-embedded material models under systolic pressure. The DL model was implemented in Julia and consisted of unsupervised and supervised learning algorithms. Training was performed on a training set of 152 shapes and testing set of 17 shapes with 10-fold cross-validation. Mean absolute error (MAE) and absolute error of peak stress values (APE) were used to compare DL model predictions with FEA values considered to be ground truth. Results: Average stress values predicted by our DL model were 175.64 ± 4.17 kPa and 95.69 ± 2.15 kPa in the circumferential and longitudinal direction, respectively. We computed a MAE of 5.06 ± 1.08 kPa and APE of 2.58 ± 1.39 kPa in the circumferential direction and MAE of 4.51 ± 0.98 kPa and APE of 2.32 ± 1.84 kPa in the longitudinal direction. Conclusions: DL model trained exclusively on clinical data was able to accurately predict stress distributions on complex aortic geometries. Fast and accurate stress predictions will facilitate real-time clinical applications for the risk assessment of aTAAs.