Automated Classification and Detection of Staphyloma with Ultrasound Images in Pathologic Myopia Eyes

The aim of this study was to develop an eyewall curvature- and axial length (AxL)-based algorithm to automate detection (clinician-free) of staphyloma ridge and apex locations using ultrasound (US). Forty-six individuals (with emmetropia, high myopia or pathologic myopia) were enrolled in this study (AxL range: 22.3-39.3 mm), yielding 130 images in total. An intensity-based segmentation algorithm automatically tracked the posterior eyewall, calculating the posterior eyewall local curvature (K) and distance (L) to the transducer and the location of the staphyloma apex. By use of the area under the receiver operator characteristic (AUROC) curve to evaluate the diagnostic ability of eight local statistics derived from K, L and AxL, the algorithm successfully quantified non-uniformity of eye shape with an AUROC > 0.70 for most K-based parameters. The performance of binary classification (staphyloma absence vs. presence) was assessed with the best classifier (the combination of AxL, standard deviation of K and standard deviation of L) yielding a diagnostic validation performance of 0.897, which was comparable to the diagnostic performance of junior clinicians. The staphyloma apex was localized with an average error of 1.35 ± 1.34 mm. Combined with the real-time data acquisition capabilities of US, this method can be employed as a screening tool for clinician-free in vivo staphyloma detection.

Quantitative Ultrasound Assessment of Early Osteoarthritis in Human Articular Cartilage Using a High-Frequency Linear Array Transducer

Quantitative ultrasound (QUS) assessment of osteoarthritis (OA) using high-frequency, research-grade single-element ultrasound systems has been reported. The objective of this ex vivo study was to assess the performance of QUS in detecting early OA using a high-frequency linear array transducer. Osteochondral plugs (n = 26) of human articular cartilage were scanned with ExactVu Micro-Ultrasound using an EV29L side-fire transducer. For comparison, the samples were also imaged with SAM200Ex, a custom 40-MHz scanning acoustic microscope with a single-element, focused transducer. Thirteen QUS parameters were derived from the ultrasound data. Magnetic resonance imaging (MRI) data, with T1 and T2 extracted as the quantitative parameters, were also acquired for comparison. Cartilage degeneration was graded from histology and correlated to all quantitative parameters. A maximum Spearman rank correlation coefficient (ρ) of 0.75 was achieved using a combination of ExactVu QUS parameters, while a maximum ρ of 0.62 was achieved using a combination of parameters from SAM200Ex. A maximum ρ of 0.75 was achieved using the T1 and T2 MRI parameters. This study illustrates the potential of a high-frequency linear array transducer to provide a convenient method for early OA screening with results comparable to those of research-grade single-element ultrasound and MRI.

In vivo assessment of pulmonary fibrosis and edema in rodents using the backscatter coefficient and envelope statistics

Quantitative ultrasound methods based on the backscatter coefficient (BSC) and envelope statistics have been used to quantify disease in a wide variety of tissues, such as prostate, lymph nodes, breast, and thyroid. However, to date, these methods have not been investigated in the lung. In this study, lung properties were quantified by BSC and envelope statistical parameters in normal, fibrotic, and edematous rat lungs in vivo. The average and standard deviation of each parameter were calculated for each lung as well as the evolution of each parameter with acoustic propagation time within the lung. The transport mean free path and backscattered frequency shift, two parameters that have been successfully used to assess pulmonary fibrosis and edema in prior work, were evaluated in combination with the BSC and envelope statistical parameters. Multiple BSC and envelope statistical parameters were found to provide contrast between control and diseased lungs. BSC and envelope statistical parameters were also significantly correlated with fibrosis severity using the modified Ashcroft fibrosis score as the histological gold standard. These results demonstrate the potential for BSC and envelope statistical parameters to improve the diagnosis of pulmonary fibrosis and edema as well as monitor pulmonary fibrosis.

Multiparametric Ultrasound for Targeting Prostate Cancer: Combining ARFI, SWEI, QUS and B-Mode

Diagnosing prostate cancer through standard transrectal ultrasound (TRUS)-guided biopsy is challenging because of the sensitivity and specificity limitations of B-mode imaging. We used a linear support vector machine (SVM) to combine standard TRUS imaging data with acoustic radiation force impulse (ARFI) imaging data, shear wave elasticity imaging (SWEI) data and quantitative ultrasound (QUS) midband fit data to enhance lesion contrast into a synthesized multiparametric ultrasound volume. This SVM was trained and validated using a subset of 20 patients and tested on a second subset of 10 patients. Multiparametric US led to a statistically significant improvements in contrast, contrast-to-noise ratio (CNR) and generalized CNR (gCNR) when compared with standard TRUS B-mode and SWEI; in contrast and CNR when compared with MF; and in CNR when compared with ARFI. ARFI, MF and SWEI also outperformed TRUS B-mode in contrast, with MF outperforming B-mode in CNR and gCNR as well. ARFI, although only yielding statistically significant differences in contrast compared with TRUS B-mode, captured critical qualitative features for lesion identification. Multiparametric US enhanced lesion visibility metrics and is a promising technique for targeted TRUS-guided prostate biopsy in the future.

Characterization of the human myocardium by optical coherence tomography

Imaging of cardiac tissue structure plays a critical role in the treatment and understanding of cardiovascular disease. Optical coherence tomography (OCT) offers the potential to provide valuable, high-resolution imaging of cardiac tissue. However, there is a lack of comprehensive OCT imaging data of the human heart, which could improve identification of structural substrates underlying cardiac abnormalities. The objective of this study was to provide qualitative and quantitative analysis of OCT image features throughout the human heart. Fifty human hearts were acquired, and tissues from all chambers were imaged with OCT. Histology was obtained to verify tissue composition. Statistical differences between OCT image features corresponding to different tissue types and chambers were estimated using analysis of variance. OCT imaging provided features that were able to distinguish structures such as thickened collagen, as well as adipose tissue and fibrotic myocardium. Statistically significant differences were found between atria and ventricles in attenuation coefficient, and between adipose and all other tissue types. This study provides an overview of OCT image features throughout the human heart, which can be used for guiding future applications such as OCT-integrated catheter-based treatments or ex vivo investigation of structural substrates.

Imaging of subendocardial adipose tissue and fiber orientation distributions in the human left atrium using optical coherence tomography

Background

Optical coherence tomography (OCT) has the potential to provide real‐time imaging guidance for atrial fibrillation ablation, with promising results for lesion monitoring. OCT can also offer high‐resolution imaging of tissue composition, but there is insufficient cardiac OCT data to inform the use of OCT to reveal important tissue architecture of the human left atrium. Thus, the objective of this study was to define OCT imaging data throughout the human left atrium, focusing on the distribution of adipose tissue and fiber orientation as seen from the endocardium.

Methods and Results

Human hearts (n = 7) were acquired for imaging the left atrium with OCT. A spectral‐domain OCT system with 1325 nm center wavelength, 6.5 μm axial resolution, 15 μm lateral resolution, and a maximum imaging depth of 2.51 mm in the air was used. Large‐scale OCT image maps of human left atrial tissue were developed, with adipose thickness and fiber orientation extracted from the imaging data. OCT imaging showed scattered distributions of adipose tissue around the septal and pulmonary vein regions, up to a depth of about 0.43 mm from the endocardial surface. The total volume of adipose tissue detected by OCT over one left atrium ranged from 1.42 to 28.74 mm³. Limited fiber orientation information primarily around the pulmonary veins and the septum could be identified.

Conclusion

OCT imaging could provide adjunctive information on the distribution of subendocardial adipose tissue, particularly around thin areas around the pulmonary veins and septal regions. Variations in OCT‐detected tissue composition could potentially assist ablation guidance.

High-speed collagen fiber modeling and orientation quantification for optical coherence tomography imaging

Quantifying collagen fiber architecture has clinical and scientific relevance across a variety of tissue types and adds functionality to otherwise largely qualitative imaging modalities. Optical coherence tomography (OCT) is uniquely suited for this task due to its ability to capture the collagen microstructure over larger fields of view than traditional microscopy. Existing image processing techniques for quantifying fiber architecture, while accurate and effective, are very slow for processing large datasets and tend to lack structural specificity. We describe here a computationally efficient method for quantifying and visualizing collagen fiber organization. The algorithm is demonstrated on swine atria, bovine anterior cruciate ligament, and human cervical tissue samples. Additionally, we show an improved performance for images with crimped fiber textures and low signal to noise when compared to similar methods.

Optical coherence tomography imaging of cardiac substrates

Cardiovascular disease is the leading cause of morbidity and mortality in the United States. Knowledge of a patient's heart structure will help to plan procedures, potentially identifying arrhythmia substrates, critical structures to avoid, detect transplant rejection, and reduce ambiguity when interpreting electrograms and functional measurements. Similarly, basic research of numerous cardiac diseases would greatly benefit from structural imaging at cellular scale. For both applications imaging on the scale of a myocyte is needed, which is approximately 100 µm × 10 µm. The use of optical coherence tomography (OCT) as a tool for characterizing cardiac tissue structure and function has been growing in the past two decades. We briefly review OCT principles and highlight important considerations when imaging cardiac muscle. In particular, image penetration, tissue birefringence, and light absorption by blood during in vivo imaging are important factors when imaging the heart with OCT. Within the article, we highlight applications of cardiac OCT imaging including imaging heart tissue structure in small animal models, quantification of myofiber organization, monitoring of radiofrequency ablation (RFA) lesion formation, structure-function analysis enabled by functional extensions of OCT and multimodal analysis and characterizing important substrates within the human heart. The review concludes with a summary and future outlook of OCT imaging the heart, which is promising with progress in optical catheter development, functional extensions of OCT, and real time image processing to enable dynamic imaging and real time tracking during therapeutic procedures.

Mapping the human pulmonary venoatrial junction with optical coherence tomography

Imaging guidance provided by optical coherence tomography (OCT) could improve the outcomes of atrial fibrillation (AF) ablation by providing detailed structural information of the pulmonary veins, which are critical targets during ablation. In this study, stitched volumetric OCT images of venoatrial junctions from post-mortem human hearts were acquired and compared to histology. Image features corresponding to venous media and myocardial sleeves, as well as fiber orientation and fibrosis, were identified and found to vary between veins. Imaging of detailed tissue architecture could improve understanding of the AF structural substrate within the pulmonary veins and assist the guidance of ablation procedures.