Imaging biomarkers in cardiac CT: moving beyond simple coronary anatomical assessment.

Cardiac computed tomography angiography (CCTA) is considered the standard non-invasive tool to rule-out obstructive coronary artery disease (CAD). Moreover, several imaging biomarkers have been developed on cardiac-CT imaging to assess global CAD severity and atherosclerotic burden, including coronary calcium scoring, the segment involvement score, segment stenosis score and the Leaman-score. Myocardial perfusion imaging enables the diagnosis of myocardial ischemia and microvascular damage, and the CT-based fractional flow reserve quantification allows to evaluate non-invasively hemodynamic impact of the coronary stenosis. The texture and density of the epicardial and perivascular adipose tissue, the hypodense plaque burden, the radiomic phenotyping of coronary plaques or the fat radiomic profile are novel CT imaging features emerging as biomarkers of inflammation and plaque instability, which may implement the risk stratification strategies. The ability to perform myocardial tissue characterization by extracellular volume fraction and radiomic features appears promising in predicting arrhythmogenic risk and cardiovascular events. New imaging biomarkers are expanding the potential of cardiac CT for phenotyping the individual profile of CAD involvement and opening new frontiers for the practice of more personalized medicine.

Biopathologic Characterization and Grade Assessment of Breast Cancer With 3-D Multiparametric Ultrasound Combining Shear Wave Elastography and Backscatter Tensor Imaging.

OBJECTIVE: Despite recent improvements in medical imaging, the final diagnosis and biopathologic characterization of breast cancers currently still requires biopsies. Ultrasound is commonly used for clinical examination of breast masses. B-Mode and shear wave elastography (SWE) are already widely used to detect suspicious masses and differentiate benign lesions from cancers. But additional ultrasound modalities such as backscatter tensor imaging (BTI) could provide relevant biomarkers related to tissue organization. Here we describe a 3-D multiparametric ultrasound approach applied to breast carcinomas in the aims of (i) validating the ability of BTI to reveal the underlying organization of collagen fibers and (ii) assessing the complementarity of SWE and BTI to reveal biopathologic features of diagnostic interest. METHODS: Three-dimensional SWE and BTI were performed ex vivo on 64 human breast carcinoma samples using a linear ultrasound probe moved by a set of motors. Here we describe a 3-D multiparametric representation of the breast masses and quantitative measurements combining B-mode, SWE and BTI. RESULTS: Our results reveal for the first time that BTI can capture the orientation of the collagen fibers around tumors. BTI was found to be a relevant marker for assessing cancer stages, revealing a more tangent tissue orientation for in situ carcinomas than for invasive cancers. In invasive cases, the combination of BTI and SWE parameters allowed for classification of invasive tumors with respect to their grade with an accuracy of 95.7%. CONCLUSION: Our results highlight the potential of 3-D multiparametric ultrasound imaging for biopathologic characterization of breast tumors.

MR Fingerprinting for Contrast Agent-free and Quantitative Characterization of Focal Liver Lesions.

Purpose To evaluate the feasibility of liver MR fingerprinting (MRF) for quantitative characterization and diagnosis of focal liver lesions. Materials and Methods This single-site, prospective study included 89 participants (mean age, 62 years ± 15 [SD]; 45 women, 44 men) with various focal liver lesions who underwent MRI between October 2021 and August 2022. The participants underwent routine clinical MRI, non-contrast-enhanced liver MRF, and reference quantitative MRI with a 1.5-T MRI scanner. The bias and repeatability of the MRF measurements were assessed using linear regression, Bland-Altman plots, and coefficients of variation. The diagnostic capability of MRF-derived T1, T2, T2*, proton density fat fraction (PDFF), and a combination of these metrics to distinguish benign from malignant lesions was analyzed according to the area under the receiver operating characteristic curve (AUC). Results Liver MRF measurements showed moderate to high agreement with reference measurements (intraclass correlation = 0.94, 0.77, 0.45, and 0.61 for T1, T2, T2*, and PDFF, respectively), with underestimation of T2 values (mean bias in lesion = -0.5%, -29%, 5.8%, and -8.2% for T1, T2, T2*, and PDFF, respectively). The median coefficients of variation for repeatability of T1, T2, and T2* values were 2.5% (IQR, 3.6%), 3.1% (IQR, 5.6%), and 6.6% (IQR, 13.9%), respectively. After considering multicollinearity, a combination of MRF measurements showed a high diagnostic performance in differentiating benign from malignant lesions (AUC = 0.92 [95% CI: 0.86, 0.98]). Conclusion Liver MRF enabled the quantitative characterization of various focal liver lesions in a single breath-hold acquisition. Keywords: MR Imaging, Abdomen/GI, Liver, Imaging Sequences, Technical Aspects, Tissue Characterization, Technology Assessment, Diagnosis, Liver Lesions, MR Fingerprinting, Quantitative Characterization Supplemental material is available for this article. © RSNA, 2023.

Proof of Concept of 3-D Backscatter Tensor Imaging Tomography for Non-invasive Assessment of Human Breast Cancer Collagen Organization.

Tumor growth, similarly to several other pathologies, tends to change the structural orientation of soft tissue fibers, which can become relevant markers for diagnosis. Current diagnosis protocols may require a biopsy for histological analysis, which is an invasive, painful and stressful procedure with a minimum turnaround time of 2 d. Otherwise, diagnosis may involve the use of complex methods with limited availability such as diffusion tensor imaging (magnetic resonance diffusion tensor imaging), which is not widely used in medical practice. Conversely, advanced methodologies in ultrasound imaging such as backscatter tensor imaging (BTI) might become a routine procedure in clinical practice at a limited cost. This method evaluates the local organization of soft tissues based on the spatial coherence of their backscattered ultrasonic echoes. Previous work has proven that BTI applied with matrix probes enables measurement of the orientation of soft tissue fibers, especially in the myocardium. The aims of the study described here were (i) to present for the first time a methodology for performing BTI in a volume on ex vivo human breast tumors using a linear probe and (ii) to display a first proof of concept of the link between BTI measurements and the orientation of collagen fibers.

Cardiovascular/Stroke Risk Assessment in Patients with Erectile Dysfunction-A Role of Carotid Wall Arterial Imaging and Plaque Tissue Characterization Using Artificial Intelligence Paradigm: A Narrative Review.

PURPOSE: The role of erectile dysfunction (ED) has recently shown an association with the risk of stroke and coronary heart disease (CHD) via the atherosclerotic pathway. Cardiovascular disease (CVD)/stroke risk has been widely understood with the help of carotid artery disease (CTAD), a surrogate biomarker for CHD. The proposed study emphasizes artificial intelligence-based frameworks such as machine learning (ML) and deep learning (DL) that can accurately predict the severity of CVD/stroke risk using carotid wall arterial imaging in ED patients. METHODS: Using the PRISMA model, 231 of the best studies were selected. The proposed study mainly consists of two components: (i) the pathophysiology of ED and its link with coronary artery disease (COAD) and CHD in the ED framework and (ii) the ultrasonic-image morphological changes in the carotid arterial walls by quantifying the wall parameters and the characterization of the wall tissue by adapting the ML/DL-based methods, both for the prediction of the severity of CVD risk. The proposed study analyzes the hypothesis that ML/DL can lead to an accurate and early diagnosis of the CVD/stroke risk in ED patients. Our finding suggests that the routine ED patient practice can be amended for ML/DL-based CVD/stroke risk assessment using carotid wall arterial imaging leading to fast, reliable, and accurate CVD/stroke risk stratification. SUMMARY: We conclude that ML and DL methods are very powerful tools for the characterization of CVD/stroke in patients with varying ED conditions. We anticipate a rapid growth of these tools for early and better CVD/stroke risk management in ED patients.

Target-filter combination effects on breast tissue characterization using mammographic X-rays: A Monte Carlo simulation study.

BACKGROUND: Characterization of normal and malignant breast tissues using X-ray scattering techniques has shown promising results and applications. OBJECTIVE: To examine possibility of characterizing normal and malignant breast tissues using the scattered photon distribution of polyenergetic beams of 30 kV X-rays. METHODS: A Monte Carlo simulation is upgraded so that it is capable of simulating input mammographic X-ray spectra from different target-filter combinations, tracing photon transport, and producing the distribution of scattered photons. The target-filter combinations include Mo-Mo, Mo-Al, Mo-Rh, Rh-Rh, Rh-Al, W-Rh, and W-Al. Analysis of obtained scattered photon distribution is carried out by comparing the ratio of count under the peak in the momentum transfer region from 0 to 1.55 nm-1, to that in the region from 1.6 to 9.1 nm-1 (covering the regions of scattering from fat and soft tissue, respectively) for breast samples with different percentages of normal tissue (0-100%). RESULTS: Mo-Mo target-filter combination shows a high linear dependence of the count under peak ratio on the percentage of normal tissue in breast samples (R2 = 0.9513). Despite slightly less linear than Mo-Mo, target-filter combinations other than Rh-Rh, W-Rh, and W-Al produce high linear responses (R2 > 0.9)CONCLUSION:Mo-Mo target-filter combination would probably be the most relevant in characterizing normal and malignant breast tissues from their scattered photon distribution.

Assessment of tissue pathology using optical polarimetry.

Optical polarimetry have been extensively used for the non-invasive assessment of biological tissues. However, the knowledge regarding differences in polarimetric signatures of different tissue pathologies is very scattered, confounding the deduction of a global trend of the polarimetric variables for healthy and pathological tissues. The purpose of this study was to bridge this gap. We conducted a rigorous online survey to collect all published studies that report the two most common polarimetric variables (i.e., depolarization and retardance) for any type of tissue pathology. A total of 101 studies describing the polarimetric assessment of tissues were collected, wherein 253 (i.e., nhuman = 149, nanimal = 104) different type of tissues were optically characterized. Most tissue samples (172/253) were investigated in ex vivo settings. The data showed 32 different types of tissues pathologies, where the most common pathology was cancer and its subtypes. The skin tissues were the most frequently explored tissues, followed by tissue samples from breast, colon, liver, and cervix. Although differences in polarimetric signatures of different tissue pathologies were summarized from the included studies, generalization of the results was hindered by the presentation of polarimetric data in a non-uniform format. The analyses presented in this study may provide an important reference for future polarimetric studies that conduct optical assessment of tissues at greater depth, particularly in the context of optical biopsy/digital staining.

Effects of lung tissue characterization in radiotherapy of breast cancer under deep inspiration breath hold when using Monte Carlo dosimetry.

PURPOSE: To investigate the sensitivity of Monte Carlo (MC) calculated lung dose distributions to lung tissue characterization in external beam radiotherapy of breast cancer under Deep Inspiration Breath Hold (DIBH). METHODS: EGSnrc based MC software was employed. Mean lung densities for one hundred patients were analysed. CT number frequency and clinical dose distributions were calculated for 15 patients with mean lung density below 0.14 g/cm3. Lung volume with a pre-defined CT numbers was also considered. Lung tissue was characterized by applying different CT calibrations in the low-density region and air-lung tissue thresholds. Dose impact was estimated by Dose Volume Histogram (DVH) parameters. RESULTS: Mean lung densities below 0.14 g/cm3 were found in 10% of the patients. CT numbers below -960 HU dominated the CT frequency distributions with a high rate of CT numbers at -990 HU. Mass density conversion approach influenced the DVH shape. V4Gy and V8Gy varied by 7% and 5% for the selected patients and by 9% and 3.5% for the pre-defined lung volume. V16Gy and V20Gy, were within 2.5%. Regions above 20 Gy were affected. Variations in air- lung tissue differentiation resulted in DVH parameters within 1%. Threshold at -990 HU was confirmed by the CT number frequency distributions. CONCLUSIONS: Lung dose distributions were more sensitive to variations in the CT calibration curve below lung (inhale) density than to air-lung tissue differentiation. Low dose regions were mostly affected. The dosimetry effects were found to be potentially important to 10% of the patients treated under DIBH.

Accelerated in Vivo Cardiac Diffusion-Tensor MRI Using Residual Deep Learning-based Denoising in Participants with Obesity.

PURPOSE: To develop and assess a residual deep learning algorithm to accelerate in vivo cardiac diffusion-tensor MRI (DT-MRI) by reducing the number of averages while preserving image quality and DT-MRI parameters. MATERIALS AND METHODS: In this prospective study, a denoising convolutional neural network (DnCNN) for DT-MRI was developed; a total of 26 participants, including 20 without obesity (body mass index [BMI] < 30 kg/m2; mean age, 28 years ± 3 [standard deviation]; 11 women) and six with obesity (BMI ≥ 30 kg/m2; mean age, 48 years ± 11; five women), were recruited from June 19, 2019, to July 29, 2020. DT-MRI data were constructed at four averages (4Av), two averages (2Av), and one average (1Av) without and with the application of the DnCNN (4AvDnCNN, 2AvDnCNN, 1AvDnCNN). All data were compared against the reference DT-MRI data constructed at eight averages (8Av). Image quality, characterized by using the signal-to-noise ratio (SNR) and structural similarity index (SSIM), and the DT-MRI parameters of mean diffusivity (MD), fractional anisotropy (FA), and helix angle transmurality (HAT) were quantified. RESULTS: No differences were found in image quality or DT-MRI parameters between the accelerated 4AvDnCNN DT-MRI and the reference 8Av DT-MRI data for the SNR (29.1 ± 2.7 vs 30.5 ± 2.9), SSIM (0.97 ± 0.01), MD (1.3 µm2/msec ± 0.1 vs 1.31 µm2/msec ± 0.11), FA (0.32 ± 0.05 vs 0.30 ± 0.04), or HAT (1.10°/% ± 0.13 vs 1.11°/% ± 0.09). The relationship of a higher MD and lower FA and HAT in individuals with obesity compared with individuals without obesity in reference 8Av DT-MRI measurements was retained in 4AvDnCNN and 2AvDnCNN DT-MRI measurements but was not retained in 4Av or 2Av DT-MRI measurements. CONCLUSION: Cardiac DT-MRI can be performed at an at least twofold-accelerated rate by using DnCNN to preserve image quality and DT-MRI parameter quantification.Keywords: Adults, Cardiac, Obesity, Technology Assessment, MR-Diffusion Tensor Imaging, Heart, Tissue CharacterizationSupplemental material is available for this article.© RSNA, 2021.

Stochastic Sequential Modeling: Toward Improved Prostate Cancer Diagnosis Through Temporal-Ultrasound.

Prostate cancer (PCa) is a common, serious form of cancer in men that is still prevalent despite ongoing developments in diagnostic oncology. Current detection methods lead to high rates of inaccurate diagnosis. We present a method to directly model and exploit temporal aspects of temporal enhanced ultrasound (TeUS) for tissue characterization, which improves malignancy prediction. We employ a probabilistic-temporal framework, namely, hidden Markov models (HMMs), for modeling TeUS data obtained from PCa patients. We distinguish malignant from benign tissue by comparing the respective log-likelihood estimates generated by the HMMs. We analyze 1100 TeUS signals acquired from 12 patients. Our results show improved malignancy identification compared to previous results, demonstrating over 85% accuracy and AUC of 0.95. Incorporating temporal information directly into the models leads to improved tissue differentiation in PCa. We expect our method to generalize and be applied to other types of cancer in which temporal-ultrasound can be recorded.

Ultrasound imaging, a stethoscope for body composition assessment.

Dysregulation of the human's energy balance, mediated by non-performing endocrine organs (liver, skeletal muscle and adipose tissue, above all), can be related to human metabolic disorders characterized by an impaired body composition (BC), such as obesity and sarcopenia. While it is possible to monitor the BC and its variations at different levels, the tissue-organ composition studies have been proven to provide the most clinically applicable information. Ultrasonography (US), a fast, non-invasive, low-cost and widely available technique, holds great potential in the study of BC, as it can directly measure muscles, organs, visceral and subcutaneous fat tissue in different sections of the abdomen and body, overcoming some limits of anthropometric evaluation and other imaging techniques. Purpose of this review article is to explore the technical aspects and the applied methods of US examination to assess the potential clinical role of this technique in the context of BC characterization, investigating four pivotal topics [abdominal fat compartments, subcutaneous adipose tissue (SAT), skeletal muscle, liver].

A low-cost texture-based pipeline for predicting myocardial tissue remodeling and fibrosis using cardiac ultrasound.

BACKGROUND: Maturation of ultrasound myocardial tissue characterization may have far-reaching implications as a widely available alternative to cardiac magnetic resonance (CMR) for risk stratification in left ventricular (LV) remodeling. METHODS: We extracted 328 texture-based features of myocardium from still ultrasound images. After we explored the phenotypes of myocardial textures using unsupervised similarity networks, global LV remodeling parameters were predicted using supervised machine learning models. Separately, we also developed supervised models for predicting the presence of myocardial fibrosis using another cohort who underwent cardiac magnetic resonance (CMR). For the prediction, patients were divided into a training and test set (80:20). FINDINGS: Texture-based tissue feature extraction was feasible in 97% of total 534 patients. Interpatient similarity analysis delineated two patient groups based on the texture features: one group had more advanced LV remodeling parameters compared to the other group. Furthermore, this group was associated with a higher incidence of cardiac deaths (p = 0.001) and major adverse cardiac events (p < 0.001). The supervised models predicted reduced LV ejection fraction (<50%) and global longitudinal strain (<16%) with area under the receiver-operator-characteristics curves (ROC AUC) of 0.83 and 0.87 in the hold-out test set, respectively. Furthermore, the presence of myocardial fibrosis was predicted from only ultrasound myocardial texture with an ROC AUC of 0.84 (sensitivity 86.4% and specificity 83.3%) in the test set. INTERPRETATION: Ultrasound texture-based myocardial tissue characterization identified phenotypic features of LV remodeling from still ultrasound images. Further clinical validation may address critical barriers in the adoption of ultrasound techniques for myocardial tissue characterization. FUNDING: None.

Experimental Measurements of Ultrasound Attenuation in Human Chest Wall and Assessment of the Mechanical Index for Lung Ultrasound.

Knowledge of the acoustic attenuation characteristics of the chest wall is necessary to estimate the acoustic exposure at the pleural surface during lung ultrasound and is useful in the prediction of bio-effects (e.g., pulmonary capillary hemorrhage) and the development of safe, effective lung imaging. Currently, this property is not well characterized in humans. The aim of this work was to characterize ultrasonic attenuation in human chest wall such that the ultrasound exposures of the lung can be estimated for clinically relevant conditions. In this study, we experimentally measured ultrasound transmitted through the intercostal tissue of 15 human cadaver chest wall samples relative to ultrasound transmitted through saline to determine attenuation coefficients for each sample. A GE Vivid 7 diagnostic ultrasound machine (GE Vingmed, Horten, Norway) and 3 S and 5 S phased array probes were used at center frequencies from 1.6 to 5 MHz. The chest wall samples varied in thickness from 2.3-5.5 cm with a median thickness of 3.8 cm. The frequency-normalized attenuation coefficient was approximately 1.44 dB/cm/MHz based on a linear best fit through all attenuation measurements. Attenuation characteristics varied appreciably between samples, and the sample-averaged linear attenuation coefficient was 1.43 ± 0.32 (mean ± standard deviation) dB/cm/MHz. This attenuation is higher than that previously measured in mammalian chest wall samples (1.1-1.3 dB/cm/MHz for mice and rats) and is much greater than that used by the mechanical index (0.3 dB/cm/MHz). Mechanical index values calculated using saline values de-rated by 0.3 dB/cm/MHz were up to 1.2 MPa/MHz1/2 greater than those calculated using the measured through-tissue ultrasound waves. We conclude that the mechanical index overestimates exposures for lung ultrasound and thus may not be an appropriate dosimetry metric for pulmonary ultrasound.

The recovery after Achilles tendon rupture: a protocol for a multicenter prospective cohort study.

BACKGROUND: Achilles tendon rupture (ATR) is a common sports injury, with a rising incidence and significant impairments. Due to the lack of treatment guidelines, there is no consensus about diagnostic methods, primary treatment (non-surgical or surgical) and rehabilitation. It is hypothesized that this lack of consensus and guidelines leads to sub-optimal recovery and higher societal costs. The primary aim of this study is to give a broad insight into the recovery after ATR. Secondarily this study aims to explore factors contributing to recovery and gain insight into the cost-effectiveness of ATR management. METHODS: This multicenter prospective cohort study will include all adult (≥ 18 years) patients with an ATR treated at the three main hospitals in the Northern Netherlands: University Medical Center Groningen, Martini Hospital Groningen and Medical Center Leeuwarden. All subjects will be invited for three visits at 3, 6 and 12 months post-injury. The following data will be collected: patient-reported outcome measures (PROMs), physical tests, imaging and economic questionnaires. At 3 months post-injury personal, injury, and treatment data will be collected through a baseline questionnaire and assessment of the medical file. The PROMs concern the Dutch version of the Achilles Tendon Total Rupture Score, EQ-5D-5 L, Oslo Sport Trauma Research Center Overuse Injury Questionnaire, Injury Psychological Readiness Return to Sport Scale, Tampa Scale of Kinesiophobia, Expectations, Motivation and Satisfaction questionnaire and a ranking of reasons for not returning to sport. The administered physical tests are the heel-rise test, standing dorsiflexion range of motion, resting tendon length and single leg hop for distance. Ultrasound Tissue Characterization will be used for imaging. Finally, economic data will be collected using the Productivity Cost Questionnaire and Medical Consumption Questionnaire. DISCUSSION: This prospective cohort study will contribute to optimal decision making in the primary treatment and rehabilitation of ATRs by providing insight into (1) ATR recovery (2) novel imaging for monitoring recovery (3) (barriers to) return to sport and (4) cost-effectiveness of management. The analysis of these data strives to give a broad insight into the recovery after ATR as well as provide data on novel imaging and costs, contributing to individualized ATR management. TRIAL REGISTRATION: Trialregister.nl. NTR6484 . 20/06/2017. 20/07/2017.

Rheumatoid Arthritis: Atherosclerosis Imaging and Cardiovascular Risk Assessment Using Machine and Deep Learning-Based Tissue Characterization.

PURPOSE OF THE REVIEW: Rheumatoid arthritis (RA) is a chronic, autoimmune disease which may result in a higher risk of cardiovascular (CV) events and stroke. Tissue characterization and risk stratification of patients with rheumatoid arthritis are a challenging problem. Risk stratification of RA patients using traditional risk factor-based calculators either underestimates or overestimates the CV risk. Advancements in medical imaging have facilitated early and accurate CV risk stratification compared to conventional cardiovascular risk calculators. RECENT FINDING: In recent years, a link between carotid atherosclerosis and rheumatoid arthritis has been widely discussed by multiple studies. Imaging the carotid artery using 2-D ultrasound is a noninvasive, economic, and efficient imaging approach that provides an atherosclerotic plaque tissue-specific image. Such images can help to morphologically characterize the plaque type and accurately measure vital phenotypes such as media wall thickness and wall variability. Intelligence-based paradigms such as machine learning- and deep learning-based techniques not only automate the risk characterization process but also provide an accurate CV risk stratification for better management of RA patients. This review provides a brief understanding of the pathogenesis of RA and its association with carotid atherosclerosis imaged using the B-mode ultrasound technique. Lacunas in traditional risk scores and the role of machine learning-based tissue characterization algorithms are discussed and could facilitate cardiovascular risk assessment in RA patients. The key takeaway points from this review are the following: (i) inflammation is a common link between RA and atherosclerotic plaque buildup, (ii) carotid ultrasound is a better choice to characterize the atherosclerotic plaque tissues in RA patients, and (iii) intelligence-based paradigms are useful for accurate tissue characterization and risk stratification of RA patients.

Hepatic steatosis assessment using ultrasound homodyned-K parametric imaging: the effects of estimators.

BACKGROUND: The homodyned-K (HK) distribution is an important statistical model for describing ultrasound backscatter envelope statistics. HK parametric imaging has shown potential for characterizing hepatic steatosis. However, the feasibility of HK parametric imaging in assessing human hepatic steatosis in vivo remains unclear. METHODS: In this paper, ultrasound HK µ parametric imaging was proposed for assessing human hepatic steatosis in vivo. Two recent estimators for the HK model, RSK (the level-curve method that uses the signal-to-noise ratio (SNR), skewness, and kurtosis based on the fractional moments of the envelope) and XU (the estimation method based on the first moment of the intensity and two log-moments, namely X- and U-statistics), were investigated. Liver donors (n=72) and patients (n=204) were recruited to evaluate hepatic fat fractions (HFFs) using magnetic resonance spectroscopy and to evaluate the stages of fatty liver disease (normal, mild, moderate, and severe) using liver biopsy with histopathology. Livers were scanned using a 3-MHz ultrasound to construct µ RSK and µ XU images to correlate with HFF analyses and fatty liver stages. The µ RSK and µ XU parametric images were constructed using the sliding window technique with the window side length (WSL) =1-9 pulse lengths (PLs). The diagnostic values of the µ RSK and µ XU parametric imaging methods were evaluated using receiver operating characteristic (ROC) curves. RESULTS: For the 72 participants in Group A, the µ RSK parametric imaging with WSL =2-9 PLs exhibited similar correlation with log10(HFF), and the µ RSK parametric imaging with WSL = 3 PLs had the highest correlation with log10(HFF) (r=0.592); the µ XU parametric imaging with WSL =1-9 PLs exhibited similar correlation with log10(HFF), and the µ XU parametric imaging with WSL =1 PL had the highest correlation with log10(HFF) (r=0.628). For the 204 patients in Group B, the areas under the ROC (AUROCs) obtained using µ RSK for fatty stages ≥ mild (AUROC1), ≥ moderate (AUROC2), and ≥ severe (AUROC3) were (AUROC1, AUROC2, AUROC3) = (0.56, 0.57, 0.53), (0.68, 0.72, 0.75), (0.73, 0.78, 0.80), (0.74, 0.77, 0.79), (0.74, 0.78, 0.79), (0.75, 0.80, 0.82), (0.74, 0.77, 0.83), (0.74, 0.78, 0.84) and (0.73, 0.76, 0.83) for WSL =1, 2, 3, 4, 5, 6, 7, 8 and 9 PLs, respectively. The AUROCs obtained using µ XU for fatty stages ≥ mild, ≥ moderate, and ≥ severe were (AUROC1, AUROC2, AUROC3) = (0.75, 0.83, 0.81), (0.74, 0.80, 0.80), (0.76, 0.82, 0.82), (0.74, 0.80, 0.84), (0.76, 0.80, 0.83), (0.75, 0.80, 0.84), (0.75, 0.79, 0.85), (0.75, 0.80, 0.85) and (0.73, 0.77, 0.83) for WSL = 1, 2, 3, 4, 5, 6, 7, 8 and 9 PLs, respectively. CONCLUSIONS: Both the µ RSK and µ XU parametric images are feasible for evaluating human hepatic steatosis. The WSL exhibits little impact on the diagnosing performance of the µ RSK and µ XU parametric imaging. The µ XU parametric imaging provided improved performance compared to the µ RSK parametric imaging in characterizing human hepatic steatosis in vivo.

Biomechanical assessment of myocardial infarction using optical coherence elastography.

Myocardial infarction (MI) leads to cardiomyocyte loss, impaired cardiac function, and heart failure. Molecular genetic analyses of myocardium in mouse models of ischemic heart disease have provided great insight into the mechanisms of heart regeneration, which is promising for novel therapies after MI. Although biomechanical factors are considered an important aspect in cardiomyocyte proliferation, there are limited methods for mechanical assessment of the heart in the mouse MI model. This prevents further understanding the role of tissue biomechanics in cardiac regeneration. Here we report optical coherence elastography (OCE) of the mouse heart after MI. Surgical ligation of the left anterior descending coronary artery was performed to induce an infarction in the heart. Two OCE methods with assessment of the direction-dependent elastic wave propagation and the spatially resolved displacement damping provide complementary analyses of the left ventricle. In comparison with sham, the infarcted heart features a fibrotic scar region with reduced elastic wave velocity, decreased natural frequency, and less mechanical anisotropy at the tissue level at the sixth week post-MI, suggesting lower and more isotropic stiffness. Our results indicate that OCE can be utilized for nondestructive biomechanical characterization of MI in the mouse model, which could serve as a useful tool in the study of heart repair.

Quantitative Optical Coherence Elastography for Robust Stiffness Assessment.

We demonstrated the capability of quantitative optical coherence elastography (qOCE) for robust assessment of material stiffness under different boundary conditions using the reaction force and displacement field established in the sample.

Near-infrared human finger measurements based on self-calibration point: Simulation and in vivo experiments.

Near-infrared light allows measuring tissue oxygenation. These measurements relay on oxygenation-dependent absorption spectral changes. However, the tissue scattering, which is also spectral dependent, introduces an intrinsic error. Most methods focus on the volume reflectance from a semi-infinite sample. We have proposed examining the full scattering profile (FSP), which is the angular intensity distribution. A point was found, that is, the iso-path length (IPL) point, which is not dependent on the tissue scattering, and can serve for self-calibration. This point is geometric dependent, hence in cylindrical tissues depends solely on the diameter. In this work, we examine an elliptic tissue cross section via Monte Carlo simulation. We have found that the IPL point of an elliptic tissue cross section is indifferent to the input illumination orientation. Furthermore, the IPL point is the same as in a circular cross section with a radius equal to the effective ellipse radius. This is despite the fact that the FSPs of the circular and elliptical cross sections are different. Hence, changing the orientation of the input illumination reveals the IPL point. In order to demonstrate this experimentally, the FSPs of a few female fingers were measured at 2 perpendicular orientations. The crossing point between these FSPs was found equivalent to the IPL point of a cylindrical phantom with a radius similar to the effective radius. The findings of this work will allow accurate pulse oximetry assessment of blood saturation.

Temporally resolved parametric assessment of Z-magnetization recovery (TOPAZ): Dynamic myocardial T1 mapping using a cine steady-state look-locker approach.

PURPOSE: To develop and evaluate a cardiac phase-resolved myocardial T1 mapping sequence. METHODS: The proposed method for temporally resolved parametric assessment of Z-magnetization recovery (TOPAZ) is based on contiguous fast low-angle shot imaging readout after magnetization inversion from the pulsed steady state. Thereby, segmented k-space data are acquired over multiple heartbeats, before reaching steady state. This results in sampling of the inversion-recovery curve for each heart phase at multiple points separated by an R-R interval. Joint T1 and B1+ estimation is performed for reconstruction of cardiac phase-resolved T1 and B1+ maps. Sequence parameters are optimized using numerical simulations. Phantom and in vivo imaging are performed to compare the proposed sequence to a spin-echo reference and saturation pulse prepared heart rate-independent inversion-recovery (SAPPHIRE) T1 mapping sequence in terms of accuracy and precision. RESULTS: In phantom, TOPAZ T1 values with integrated B1+ correction are in good agreement with spin-echo T1 values (normalized root mean square error = 4.2%) and consistent across the cardiac cycle (coefficient of variation = 1.4 ± 0.78%) and different heart rates (coefficient of variation = 1.2 ± 1.9%). In vivo imaging shows no significant difference in TOPAZ T1 times between the cardiac phases (analysis of variance: P = 0.14, coefficient of variation = 3.2 ± 0.8%), but underestimation compared with SAPPHIRE (T1 time ± precision: 1431 ± 56 ms versus 1569 ± 65 ms). In vivo precision is comparable to SAPPHIRE T1 mapping until middiastole (P > 0.07), but deteriorates in the later phases. CONCLUSIONS: The proposed sequence allows cardiac phase-resolved T1 mapping with integrated B1+ assessment at a temporal resolution of 40 ms. Magn Reson Med 79:2087-2100, 2018. © 2017 International Society for Magnetic Resonance in Medicine.