Faculty Bibliography

BACKGROUND:Echocardiographic strain measurements require extensive operator experience and have significant intervendor variability. Creating an automated, open-source, vendor-agnostic method to retrospectively measure global longitudinal strain (GLS) from standard echocardiography B-mode images would greatly improve post hoc research applications and may streamline patient analyses. OBJECTIVES/OBJECTIVE:This study was seeking to develop an automated deep learning strain (DLS) analysis pipeline and validate its performance across multiple applications and populations. METHODS:Interobserver/-vendor variation of traditional GLS, and simulated effects of variation in contour on speckle-tracking measurements were assessed. The DLS pipeline was designed to take semantic segmentation results from EchoNet-Dynamic and derive longitudinal strain by calculating change in the length of the left ventricular endocardial contour. DLS was evaluated for agreement with GLS on a large external dataset and applied across a range of conditions that result in cardiac hypertrophy. RESULTS:In patients scanned by 2 sonographers using 2 vendors, GLS had an intraclass correlation of 0.29 (95% CI: -0.01 to 0.53, P = 0.03) between vendor measurements and 0.63 (95% CI: 0.48-0.74, P < 0.001) between sonographers. With minor changes in initial input contour, step-wise pixel shifts resulted in a mean absolute error of 3.48% and proportional strain difference of 13.52% by a 6-pixel shift. In external validation, DLS maintained moderate agreement with 2-dimensional GLS (intraclass correlation coefficient [ICC]: 0.56, P = 0.002) with a bias of -3.31% (limits of agreement: -11.65% to 5.02%). The DLS method showed differences (P < 0.0001) between populations with cardiac hypertrophy and had moderate agreement in a patient population of advanced cardiac amyloidosis: ICC was 0.64 (95% CI: 0.53-0.72), P < 0.001, with a bias of 0.57%, limits of agreement of -4.87% to 6.01% vs 2-dimensional GLS. CONCLUSIONS:The open-source DLS provides lower variation than human measurements and similar quantitative results. The method is rapid, consistent, vendor-agnostic, publicly released, and applicable across a wide range of imaging qualities.

BACKGROUND/UNASSIGNED:Conotruncal defects due to developmental abnormalities of the outflow tract (OFT) are an important cause of cyanotic congenital heart disease. Dysregulation of transcriptional programs tuned by NKX2-5 (NK2 homeobox 5), GATA6 (GATA binding protein 6), and TBX1 (T-box transcription factor 1) have been implicated in abnormal OFT morphogenesis. However, there remains no consensus on how these transcriptional programs function in a unified gene regulatory network within the OFT. METHODS/UNASSIGNED: RESULTS/UNASSIGNED: CONCLUSIONS/UNASSIGNED:Our results using human and mouse models reveal an essential gene regulatory network of the OFT that requires an anterior second heart field enhancer to link GATA6 with NKX2-5-dependent rotation and septation gene programs.

We report the development of a novel otoscopy probe for assessing middle ear anatomy and function. Video imaging and phase-sensitive optical coherence tomography are combined within the same optical path. A sound stimuli channel is incorporated as well to study middle ear function. Thus, besides visualizing the morphology of the middle ear, the vibration amplitude and frequency of the eardrum and ossicles are retrieved as well. Preliminary testing on cadaveric human temporal bone models has demonstrated the capability of this instrument for retrieving middle ear anatomy with micron scale resolution, as well as the vibration of the tympanic membrane and ossicles with sub-nm resolution.

The mechanical stability of the cornea is critical for maintaining its normal shape and refractive function. Here, we report an observation of the mechanical resonance modes of the cornea excited by sound waves and detected by using phase-sensitive optical coherence tomography. The cornea in bovine eye globes exhibited three resonance modes in a frequency range of 50-400 Hz. The vibration amplitude of the fundamental mode at 80-120 Hz was ~8 µm at a sound pressure level of 100 dB (2 Pa). Vibrography allows the visualization of the radially symmetric profiles of the resonance modes. A dynamic finite-element analysis supports our observation.

We present a new method for generating micron-scale OCT images of interstitial tissue with a hand scanning probe and a linear optical encoder that senses probe movement relative to a fixed reference point, i.e., tissue surface. Based on this approach, we demonstrate high resolution optical imaging of biological tissues through a very long biopsy needle. Minor artifacts caused by tissue noncompliance are corrected using a software algorithm which detects the simple repetition of the adjacent A-scans. This hand-scanning OCT imaging approach offers the physician the freedom to access imaging sites of interest repeatedly.

Most techniques measuring corneal biomechanics in vivo are biased by side factors. We demonstrate the ability of optical coherence tomographic (OCT) vibrography to determine corneal material parameters, while reducing current prevalent restrictions of other techniques (such as intraocular pressure (IOP) and thickness dependency). Modal analysis was performed in a finite-element (FE) model to study the oscillation response in isolated thin corneal flaps/eye globes and to analyse the dependency of the frequency response function on: corneal elasticity, viscoelasticity, geometry (thickness and curvature), IOP and density. The model was verified experimentally in flaps from three bovine corneas and in two enucleated porcine eyes using sound excitation (100-110 dB) together with a phase-sensitive OCT to measure the frequency response function (range 50-510 Hz). Simulations showed that corneal vibration in flaps is sensitive to both, geometrical and biomechanical parameters, whereas in whole globes it is primarily sensitive to corneal biomechanical parameters only. Calculations based on the natural frequency shift revealed that flaps of the posterior cornea were 0.8 times less stiff than flaps from the anterior cornea and cross-linked corneas were 1.6 times stiffer than virgin corneas. Sensitivity analysis showed that natural vibration frequencies of whole globes were nearly independent from corneal thickness and IOP within the physiological range. OCT vibrography is a promising non-invasive technique to measure corneal elasticity without biases from corneal thickness and IOP.

Optical coherence tomography (OCT) is a promising tool for detecting micro channels, metal prints, defects and delaminations embedded in alumina and zirconia ceramic layers at hundreds of micrometers beneath surfaces. The effect of surface roughness and scattering of probing radiation within sample on OCT inspection is analyzed from the experimental and simulated OCT images of the ceramic samples with varying surface roughnesses and operating wavelengths. By Monte Carlo simulations of the OCT images in the mid-IR the optimal operating wavelength is found to be 4 µm for the alumina samples and 2 µm for the zirconia samples for achieving sufficient probing depth of about 1 mm. The effects of rough surfaces and dispersion on the detection of the embedded boundaries are discussed. Two types of image artefacts are found in OCT images due to multiple reflections between neighboring boundaries and inhomogeneity of refractive index.

This study aimed to evaluate the concept of using high-resolution optical coherence tomography (OCT) imaging to rapidly assess surgical specimens and determine if cancer positive margins were left behind in the surgical bed. A mouse model of breast cancer was used in this study. Surgical specimens from 30 animals were investigated with OCT and automated interpretation of the OCT images was performed and tested against histopathology findings. Specimens from 10 animals were used to build a training set of OCT images, while the remaining 20 specimens were used for a validation set of images. The validation study showed that automated interpretation of OCT images can differentiate tissue types and detect cancer positive margins with at least 81% sensitivity and 89% specificity. The findings of this pilot study suggest that OCT imaging of surgical specimens and automated interpretation of OCT data may enable in the future real-time feedback to the surgeon about margin status in patients with breast cancer, and potentially with other types of cancers. Currently, such feedback is not provided and if positive margins are left behind, patients have to undergo another surgical procedure. Therefore, this approach can have a potentially high impact on breast surgery outcome.