Probabilistic Nested Model Selection in Pharmacokinetic Analysis of DCE-MRI Data in Animal Model of Cerebral Tumor.

Purpose: Best current practice in the analysis of dynamic contrast enhanced (DCE)-MRI is to employ a voxel-by-voxel model selection from a hierarchy of nested models. This nested model selection (NMS) assumes that the observed time-trace of contrast-agent (CA) concentration within a voxel, corresponds to a singular physiologically nested model. However, admixtures of different models may exist within a voxel's CA time-trace. This study introduces an unsupervised feature engineering technique (Kohonen-Self-Organizing-Map (K-SOM)) to estimate the voxel-wise probability of each nested model. Methods: Sixty-six immune-compromised-RNU rats were implanted with human U-251N cancer cells, and DCE-MRI data were acquired from all the rat brains. The time-trace of change in the longitudinalrelaxivity Δ R 1 for all animals' brain voxels was calculated. DCE-MRI pharmacokinetic (PK) analysis was performed using NMS to estimate three model regions: Model-1: normal vasculature without leakage, Model-2: tumor tissues with leakage without back-flux to the vasculature, Model-3: tumor vessels with leakage and back-flux. Approximately two hundred thirty thousand (229,314) normalized Δ R 1 profiles of animals' brain voxels along with their NMS results were used to build a K-SOM (topology-size: 8×8, with competitive-learning algorithm) and probability map of each model. K-fold nested-cross-validation (NCV, k=10) was used to evaluate the performance of the K-SOM probabilistic-NMS (PNMS) technique against the NMS technique. Results: The K-SOM PNMS's estimation for the leaky tumor regions were strongly similar (Dice-Similarity-Coefficient, DSC=0.774 [CI: 0.731-0.823], and 0.866 [CI: 0.828-0.912] for Models 2 and 3, respectively) to their respective NMS regions. The mean-percent-differences (MPDs, NCV, k=10) for the estimated permeability parameters by the two techniques were: -28%, +18%, and +24%, for v p , K trans , and v e , respectively. The KSOM-PNMS technique produced microvasculature parameters and NMS regions less impacted by the arterial-input-function dispersion effect. Conclusion: This study introduces an unsupervised model-averaging technique (K-SOM) to estimate the contribution of different nested-models in PK analysis and provides a faster estimate of permeability parameters.

CMR-based cardiac phenotyping in different forms of heart failure.

Heart failure (HF) is a heterogenous disease requiring precise diagnostics and knowledge of pathophysiological processes. Since structural and functional imaging data are scarce we hypothesized that cardiac magnetic resonance (CMR)-based analyses would provide accurate characterization and mechanistic insights into different HF groups comprising preserved (HFpEF), mid-range (HFmrEF) and reduced ejection fraction (HFrEF). 22 HFpEF, 17 HFmrEF and 15 HFrEF patients as well as 19 healthy volunteers were included. CMR image assessment contained left atrial (LA) and left ventricular (LV) volumetric evaluation as well as left atrioventricular coupling index (LACI). Furthermore, CMR feature-tracking included LV and LA strain in terms of reservoir (Es), conduit (Ee) and active boosterpump (Ea) function. CMR-based tissue characterization comprised T1 mapping as well as late-gadolinium enhancement (LGE) analyses. HFpEF patients showed predominant atrial impairment (Es 20.8%vs.25.4%, p = 0.02 and Ee 8.3%vs.13.5%, p = 0.001) and increased LACI compared to healthy controls (14.5%vs.23.3%, p = 0.004). Patients with HFmrEF showed LV enlargement but mostly preserved LA function with a compensatory increase in LA boosterpump (LA Ea: 15.0%, p = 0.049). In HFrEF LA and LV functional impairment was documented (Es: 14.2%, Ee: 5.4% p < 0.001 respectively; Ea: 8.8%, p = 0.02). This was paralleled by non-invasively assessed progressive fibrosis (T1 mapping and LGE; HFrEF > HFmrEF > HFpEF). CMR-imaging reveals insights into HF phenotypes with mainly atrial affection in HFpEF, ventricular affection with atrial compensation in HFmrEF and global impairment in HFrEF paralleled by progressive LV fibrosis. These data suggest a necessity for a personalized HF management based on imaging findings for future optimized patient management.

Cardiac computed tomography with late contrast enhancement: A review.

Cardiac computed tomography (CCT) has assumed an increasingly significant role in the evaluation of coronary artery disease (CAD) during the past few decades, whereas cardiovascular magnetic resonance (CMR) remains the gold standard for myocardial tissue characterization. The discovery of late myocardial enhancement following intravenous contrast administration dates back to the 1970s with ex-vivo CT animal investigations; nevertheless, the clinical application of this phenomenon for cardiac tissue characterization became prevalent for CMR imaging far earlier than for CCT imaging. Recently the technical advances in CT scanners have made it possible to take advantage of late contrast enhancement (LCE) for tissue characterization in CCT exams. Moreover, the introduction of extracellular volume calculation (ECV) on cardiac CT images combined with the possibility of evaluating cardiac function in the same exam is making CCT imaging a multiparametric technique more and more similar to CMR. The aim of our review is to provide a comprehensive overview on the role of CCT with LCE in the evaluation of a wide range of cardiac conditions.

Feature Extraction of Ultrasound Radiofrequency Data for the Classification of the Peripheral Zone of Human Prostate.

Prostate cancer ranks among the most prevalent types of cancer in males, prompting a demand for early detection and noninvasive diagnostic techniques. This paper explores the potential of ultrasound radiofrequency (RF) data to study different anatomic zones of the prostate. The study leverages RF data's capacity to capture nuanced acoustic information from clinical transducers. The research focuses on the peripheral zone due to its high susceptibility to cancer. The feasibility of utilizing RF data for classification is evaluated using ex-vivo whole prostate specimens from human patients. Ultrasound data, acquired using a phased array transducer, is processed, and correlated with B-mode images. A range filter is applied to highlight the peripheral zone's distinct features, observed in both RF data and 3D plots. Radiomic features were extracted from RF data to enhance tissue characterization and segmentation. The study demonstrated RF data's ability to differentiate tissue structures and emphasizes its potential for prostate tissue classification, addressing the current limitations of ultrasound imaging for prostate management. These findings advocate for the integration of RF data into ultrasound diagnostics, potentially transforming prostate cancer diagnosis and management in the future.

Multimodality quantitative ultrasound envelope statistics imaging based support vector machines for characterizing tissue scatterer distribution patterns: Methods and application in detecting microwave-induced thermal lesions.

Ultrasound envelope statistics imaging, including ultrasound Nakagami imaging, homodyned-K imaging, and information entropy imaging, is an important group of quantitative ultrasound techniques for characterizing tissue scatterer distribution patterns, such as scatterer concentrations and arrangements. In this study, we proposed a machine learning approach to integrate the strength of multimodality quantitative ultrasound envelope statistics imaging techniques and applied it to detecting microwave ablation induced thermal lesions in porcine liver ex vivo. The quantitative ultrasound parameters included were homodyned-K α which is a scatterer clustering parameter related to the effective scatterer number per resolution cell, Nakagami m which is a shape parameter of the envelope probability density function, and Shannon entropy which is a measure of signal uncertainty or complexity. Specifically, the homodyned-K log10(α), Nakagami-m, and horizontally normalized Shannon entropy parameters were combined as input features to train a support vector machine (SVM) model to classify thermal lesions with higher scatterer concentrations from normal tissues with lower scatterer concentrations. Through heterogeneous phantom simulations based on Field II, the proposed SVM model showed a classification accuracy above 0.90; the area accuracy and Dice score of higher-scatterer-concentration zone identification exceeded 83% and 0.86, respectively, with the Hausdorff distance <26. Microwave ablation experiments of porcine liver ex vivo at 60-80 W, 1-3 min showed that the SVM model achieved a classification accuracy of 0.85; compared with single log10(α),m, or hNSE parametric imaging, the SVM model achieved the highest area accuracy (89.1%) and Dice score (0.77) as well as the smallest Hausdorff distance (46.38) of coagulation zone identification. We concluded that the proposed multimodality quantitative ultrasound envelope statistics imaging based SVM approach can enhance the capability to characterize tissue scatterer distribution patterns and has the potential to detect the thermal lesions induced by microwave ablation.

Normative ultrasound values for Achilles tendon thickness in the general population and patients with Achilles tendinopathy: A large international cross-sectional study.

The objective of the study was to obtain adjusted ultrasonographic reference values of the Achilles tendon thickness (maximum anterior-posterior distance) in adults without (previous) Achilles tendinopathy (AT) and to compare these reference values with AT patients. Six hundred participants were consecutively included, comprising 500 asymptomatic individuals and 100 patients with clinically diagnosed chronic AT. The maximum tendon thickness was assessed using Ultrasound Tissue Characterization. A multiple quantile regression model was developed, incorporating covariates (personal characteristics) that were found to have a significant impact on the maximum anterior-posterior distance of the Achilles tendon. A 95% reference interval (RI) was derived (50th, 2.5th-97.5th percentile). In asymptomatic participants median (95% RI) tendon thickness was 4.9 (3.8-6.9) mm for the midportion region and 3.7 (2.8-4.8) mm for the insertional region. Age, height, body mass index, and sex had a significant correlation with maximum tendon thickness. Median tendon thickness for the midportion region was calculated with the normative equation -2.1 + AGE × 0.021 + HEIGHT × 0.032+ BMI × 0.028 + SEX × 0.05. For the insertional region, the normative equation was -0.34 + AGE × 0.010+ HEIGHT × 0.018 + BMI × 0.022 + SEX × -0.05. In the equations, SEX is defined as 0 for males and 1 for females. Mean (95% CI) difference in tendon thickness compared to AT patients was 2.7 mm (2.3-3.2, p < 0.001) for the midportion and 1.4 mm (1.1-1.7, p < 0.001) for the insertional region. Compared to the asymptomatic population 73/100 (73%) AT patients exhibited increased tendon thickening, with values exceeding the 95% RI. This study presents novel reference values for the thickness of midportion and insertional region of the Achilles tendon, which were adjusted for personal characteristics. Our novel web-based openly accessible calculator for determining normative Achilles tendon thickness (www.achillestendontool.com) will be a useful resource in the diagnostic process. Trial registration number: This trial is registered in the Netherlands Trial Register (NL9010).

Microscope-integrated optical coherence tomography for in vivo human brain tumor detection with artificial intelligence.

OBJECTIVE: It has been shown that optical coherence tomography (OCT) can identify brain tumor tissue and potentially be used for intraoperative margin diagnostics. However, there is limited evidence on its use in human in vivo settings, particularly in terms of its applicability and accuracy of residual brain tumor detection (RTD). For this reason, a microscope-integrated OCT system was examined to determine in vivo feasibility of RTD after resection with automated scan analysis. METHODS: Healthy and diseased brain was 3D scanned at the resection edge in 18 brain tumor patients and investigated for its informative value in regard to intraoperative tissue classification. Biopsies were taken at these locations and labeled by a neuropathologist for further analysis as ground truth. Optical OCT properties were obtained, compared, and used for separation with machine learning. In addition, two artificial intelligence-assisted methods were utilized for scan classification, and all approaches were examined for RTD accuracy and compared to standard techniques. RESULTS: In vivo OCT tissue scanning was feasible and easily integrable into the surgical workflow. Measured backscattered light signal intensity, signal attenuation, and signal homogeneity were significantly distinctive in the comparison of scanned white matter to increasing levels of scanned tumor infiltration (p < 0.001) and achieved high values of accuracy (85%) for the detection of diseased brain in the tumor margin with support vector machine separation. A neuronal network approach achieved 82% accuracy and an autoencoder approach 85% accuracy in the detection of diseased brain in the tumor margin. Differentiating cortical gray matter from tumor tissue was not technically feasible in vivo. CONCLUSIONS: In vivo OCT scanning of the human brain has been shown to contain significant value for intraoperative RTD, supporting what has previously been discussed for ex vivo OCT brain tumor scanning, with the perspective of complementing current intraoperative methods for this purpose, especially when deciding to withdraw from further resection toward the end of the surgery.

Thrombus discrimination with electron density: potential implications for non-contrast computed tomography imaging.

The potential clinical usefulness of electron density (ED) imaging, that can be directly estimated using dual-layer spectral computed tomography (CT), has been poorly investigated. We explored whether ED imaging might improve thrombus identification compared to conventional imaging in vitro. We evaluated mechanical thrombectomy material obtained from patients with acute ischemic stroke (AIS) treated in a tertiary level stroke center and immediately fixed in 10% neutral buffered formalin and stored in polystyrene test tubes. The test tubes were immersed in a bucket of water for evaluation by spectral CT, along with scattered control tubes. All images were obtained using a dual-layer detector CT scanner. Each tube was assessed using multiparametric side-by-side view of conventional CT (120 kVp), low monoenergetic imaging (40 keV), and ED images. Fifty-eight polystyrene tubes were analyzed, comprising 52 tubes with thrombectomy material of at least 1 mm2 size obtained from 52 AIS patients, and six control tubes filled with formalin. ED imaging identified accurately the presence of material in all tubes, whereas 2 (3%) of the tubes containing thrombus were not identified by conventional CT, leading to a very good agreement between observers for the presence of material using conventional CT and ED imaging (kappa =0.84, P<0.001). Using ED imaging, thrombus material showed a mean density of 108.8±2.9 percent ED relative to water (%EDW), water had a mean density of 100.0±0.3 %EDW, and formalin a mean density of 103.5±1.2 %EDW. Compared to conventional imaging and 40 keV monoenergetic, ED imaging had a significantly higher signal-to-noise ratio (conventional 10.4±7.0, vs. 40 keV 11.5±8.4, vs. ED 490.0±304.5, P<0.001) and contrast-to-noise ratio (CNR) (conventional 4.3±4.3, vs. 40 keV 5.7±11.2, vs. ED 37.8±29.1, P<0.001). In this in-vitro study, we demonstrated improved visualization of thrombus with ED imaging compared to conventional imaging and low monoenergetic imaging, with a significant increase in CNR.

Deep cardiac phenotyping by cardiovascular magnetic resonance reveals subclinical focal and diffuse myocardial injury in patients with psoriasis (PSOR-COR study).

BACKGROUND: Psoriasis vulgaris (PV) is a chronic inflammatory disorder frequently associated with cardiovascular disease (CVD). This study aims to provide a prospective tissue characterization in patients with PV without major CVD using cardiovascular magnetic resonance (CMR). METHODS: Patients with PV underwent laboratory assessment, a 12-lead and 24-h ECG, and a CMR exam at a 1.5-T scanner. Scan protocol included assessment of left (LV) and right (RV) ventricular function and strain analysis, native and post-contrast T1 mapping, T2 mapping and late gadolinium enhancement (LGE). RESULTS: In total, 60 PV patients (median(IQR) age in years: 50.0 (36.0-60.8); 34 men (56.7%)) were recruited and compared to 40 healthy volunteers (age in years: 49.5 (37.3-57.8); 21 men (53.0%)). No differences were found regarding LV and RV function (p = 0.78 and p = 0.75). Global radial and circumferential strains were lower in patients (p < 0.001 and p < 0.001, respectively). PV had higher global T1 times (1001 (982-1026) ms vs. 991 (968-1005) ms; p = 0.01) and lower global T2 times (48 (47-49) ms vs. 50 (48-51) ms; p < 0.001); however, all values were within local reference ranges. Focal non-ischemic fibrosis was observed in 17 (28.3%) PV patients. CONCLUSION: Deep cardiac phenotyping by CMR revealed subclinical myocardial injury in patients with PV without major CVD, despite preserved LV and RV function. Diffuse and focal fibrosis might be the first detectable signs of adverse tissue remodeling leading to reduced circumferential and radial myocardial deformation. In the background of local and systemic immunomodulatory therapy, no signs of myocardial inflammation were detected. The exact impact of immunomodulatory therapies on the myocardium needs to be addressed in future studies. STUDY REGISTRATION: ISRCTN71534700.

Correlation between diffusion-weighted image-derived parameters and dynamic contrast-enhanced magnetic resonance imaging-derived parameters in the orofacial region.

Background: Diffusion-weighted imaging (DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) are widely used in the orofacial region. Furthermore, quantitative analyses have proven useful. However, a few reports have described the correlation between DWI-derived parameters and DCE-MRI-derived parameters, and the results have been controversial. Purpose: To evaluate the correlation among parameters obtained by DWI and DCE-MRI and to compare them between benign and malignant lesions. Material and Methods: Fifty orofacial lesions were analysed. The apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudodiffusion coefficient (D*) and perfusion fraction (f) were estimated by DWI. For DCE-MRI, TK model analysis was performed to estimate physiological parameters, for example, the influx forward volume transfer constant into the extracellular-extravascular space (EES) (Ktrans) and fractional volumes of EES and plasma components (ve and vp). Results: Both ADC and D showed a moderate positive correlation with ve (ρ = 0.640 and 0.645, respectively). Ktrans showed a marginally weak correlation with f (ρ = 0.296), while vp was not correlated with f or D*; therefore, IVIM perfusion-related parameters and TK model perfusion-related parameters were not straightforward. Both D and ve yielded high diagnostic power between benign lesions and malignant tumours with areas under the curve (AUCs) of 0.830 and 0.782, respectively. Conclusion: Both D and ve were reliable parameters that were useful for the differential diagnosis. In addition, the true diffusion coefficient (D) was affected by the fractional volume of EES.

Rare cardiac inflammatory pseudotumor in a toddler: Complementary roles of cardiac magnetic resonance and positron emission tomography.

We present a rare pediatric case of cardiac inflammatory pseudotumor (IPT) with a unique presentation of fever of unknown origin with markedly elevated inflammatory markers. A right atrial mass was discovered incidentally by echocardiography. The cardiac magnetic resonance (CMR) signal characteristics and mass location were not consistent with any of the common benign cardiac tumors of childhood. The presence of high signal intensity on T2 imaging and late gadolinium enhancement, in conjunction with intense metabolic activity at the mass site on positron emission tomography (PET), raised the possibility of an inflammatory or malignant mass. The diagnosis of IPT was confirmed by biopsy. Our case highlights the utility of PET imaging to confirm the inflammatory nature and extent of an IPT.

Light-Chain Cardiac Amyloidosis: Cardiac Magnetic Resonance for Assessing Response to Chemotherapy.

OBJECTIVE: Cardiac magnetic resonance (CMR) is a diagnostic tool that provides precise and reproducible information about cardiac structure, function, and tissue characterization, aiding in the monitoring of chemotherapy response in patients with light-chain cardiac amyloidosis (AL-CA). This study aimed to evaluate the feasibility of CMR in monitoring responses to chemotherapy in patients with AL-CA. MATERIALS AND METHODS: In this prospective study, we enrolled 111 patients with AL-CA (50.5% male; median age, 54 [interquartile range, 49-63] years). Patients underwent longitudinal monitoring using biomarkers and CMR imaging. At follow-up after chemotherapy, patients were categorized into superior and inferior response groups based on their hematological and cardiac laboratory responses to chemotherapy. Changes in CMR findings across therapies and differences between response groups were analyzed. RESULTS: Following chemotherapy (before vs. after), there were significant increases in myocardial T2 (43.6 ± 3.5 ms vs. 44.6 ± 4.1 ms; P = 0.008), recovery in right ventricular (RV) longitudinal strain (median of -9.6% vs. -11.7%; P = 0.031), and decrease in RV extracellular volume fraction (ECV) (median of 53.9% vs. 51.6%; P = 0.048). These changes were more pronounced in the superior-response group. Patients with superior cardiac laboratory response showed significantly greater reductions in RV ECV (-2.9% [interquartile range, -8.7%-1.1%] vs. 1.7% [-5.5%-7.1%]; P = 0.017) and left ventricular ECV (-2.0% [-6.0%-1.3%] vs. 2.0% [-3.0%-5.0%]; P = 0.01) compared with those with inferior response. CONCLUSION: Cardiac amyloid deposition can regress following chemotherapy in patients with AL-CA, particularly showing more prominent regression, possibly earlier, in the RV. CMR emerges as an effective tool for monitoring associated tissue characteristics and ventricular functional recovery in patients with AL-CA undergoing chemotherapy, thereby supporting its utility in treatment response assessment.

Pulse-echo ultrasound attenuation tomography.

Objective.We present the first fully two-dimensional attenuation imaging technique developed for pulse-echo ultrasound systems. Unlike state-of-the-art techniques, which use line-by-line acquisitions, our method uses steered emissions to constrain attenuation values at each location with multiple crossing wave paths, essential to resolve the spatial variations of this tissue property.Approach.At every location, we compute normalized cross-correlations between the beamformed images that are obtained from emissions at different steering angles. We demonstrate that their log-amplitudes provide the changes between attenuation-induced amplitude losses undergone by the different incident waves. This allows us to formulate a linear tomographic problem, which we efficiently solve via a Tikhonov-regularized least-squares approach.Main results.The performance of our tomography technique is first validated in numerical examples and then experimentally demonstrated in custom-made tissue-mimicking phantoms with inclusions of varying size, echogenicity, and attenuation. We show that this technique is particularly good at resolving lateral variations in tissue attenuation and remains accurate in media with varying echogenicity.Significance.Based on a similar principle, this method can be easily combined with computed ultrasound tomography in echo mode for speed-of-sound imaging, paving the way towards a multi-modal ultrasound tomography framework characterizing multiple acoustic tissue properties simultaneously.

Fractal-Based Analysis of Histological Features of Brain Tumors.

The structural complexity of brain tumor tissue represents a major challenge for effective histopathological diagnosis. Tumor vasculature is known to be heterogeneous, and mixtures of patterns are usually present. Therefore, extracting key descriptive features for accurate quantification is not a straightforward task. Several steps are involved in the texture analysis process where tissue heterogeneity contributes to the variability of the results. One of the interesting aspects of the brain lies in its fractal nature. Many regions within the brain tissue yield similar statistical properties at different scales of magnification. Fractal-based analysis of the histological features of brain tumors can reveal the underlying complexity of tissue structure and angiostructure, also providing an indication of tissue abnormality development. It can further be used to quantify the chaotic signature of disease to distinguish between different temporal tumor stages and histopathological grades.Brain meningioma subtype classifications' improvement from histopathological images is the main focus of this chapter. Meningioma tissue texture exhibits a wide range of histological patterns whereby a single slide may show a combination of multiple patterns. Distinctive fractal patterns quantified in a multiresolution manner would be for better spatial relationship representation. Fractal features extracted from textural tissue patterns can be useful in characterizing meningioma tumors in terms of subtype classification, a challenging problem compared to histological grading, and furthermore can provide an objective measure for quantifying subtle features within subtypes that are hard to discriminate.

Variability of intervertebral joint stiffness between specimens and spine levels.

Introduction: Musculoskeletal multibody models of the spine can be used to investigate the biomechanical behaviour of the spine. In this context, a correct characterisation of the passive mechanical properties of the intervertebral joint is crucial. The intervertebral joint stiffness, in particular, is typically derived from the literature, and the differences between individuals and spine levels are often disregarded. Methods: This study tested if an optimisation method of personalising the intervertebral joint stiffnesses was able to capture expected stiffness variation between specimens and between spine levels and if the variation between spine levels could be accurately captured using a generic scaling ratio. Multibody models of six T12 to sacrum spine specimens were created from computed tomography data. For each specimen, two models were created: one with uniform stiffnesses across spine levels, and one accounting for level dependency. Three loading conditions were simulated. The initial stiffness values were optimised to minimize the kinematic error. Results: There was a range of optimised stiffnesses across the specimens and the models with level dependent stiffnesses were less accurate than the models without. Using an optimised stiffness substantially reduced prediction errors. Discussion: The optimisation captured the expected variation between specimens, and the prediction errors demonstrated the importance of accounting for level dependency. The inaccuracy of the predicted kinematics for the level-dependent models indicated that a generic scaling ratio is not a suitable method to account for the level dependency. The variation in the optimised stiffnesses for the different loading conditions indicates personalised stiffnesses should also be considered load-specific.

Characterization of the collagen network of human cheek skin using ultrasonic microscopy.

Dermal collagen is the most abundant component of human skin and has a network structure that regulates the mechanical properties of the skin. Therefore, non-invasive characterization of the collagen network would be beneficial for the evaluation of skin conditions. The microscopic substructures of the network, which are individual bundles and fibers, have been optically investigated. However, the macroscopic structure of the collagen network has not been assessed. To evaluate the dermal collagen network, we developed two new indicators, volume filling factor (VFF) and collagen fiber texture (CFT), to analyze three-dimensional echo intensity maps of high-frequency ultrasonic microscopy. By identifying the difference in the elastic modulus components of the dermal layer of facial skin, the density and texture of the collagen network were characterized using VFF and CFT, respectively. These new indicators revealed that the density decreased and the texture became fine with facial age. This study demonstrates that ultrasonic microscopy is useful for investigating skin conditions, paving the way for diagnostic applications in dermatology and aesthetic medicine.

3D whole heart k-space-based super-resolution cardiac T1 mapping using rotated stacks.

Objective. To provide three-dimensional (3D) whole-heart high-resolution isotropic cardiac T1 maps using a k-space-based through-plane super-resolution reconstruction (SRR) with rotated multi-slice stacks.Approach. Due to limited SNR and cardiac motion, often only 2D T1 maps with low through-plane resolution (4-8 mm) can be obtained. Previous approaches used SRR to calculate 3D high-resolution isotropic cardiac T1 maps. However, they were limited to the ventricles. The proposed approach acquires rotated stacks in long-axis orientation with high in-plane resolution but low through-plane resolution. This results in radially overlapping stacks from which high-resolution T1 maps of the whole heart are reconstructed using a k-space-based SRR framework considering the complete acquisition model. Cardiac and residual respiratory motion between different breath holds is estimated and incorporated into the reconstruction. The proposed approach was evaluated in simulations and phantom experiments and successfully applied to ten healthy subjects.Main results. 3D T1 maps of the whole heart were obtained in the same acquisition time as previous methods covering only the ventricles. T1 measurements were possible even for small structures, such as the atrial wall. The proposed approach provided accurate (P> 0.4;R2> 0.99) and precise T1 values (SD of 64.32 ± 22.77 ms in the proposed approach, 44.73 ± 31.9 ms in the reference). The edge sharpness of the T1 maps was increased by 6.20% and 4.73% in simulation and phantom experiments, respectively. Contrast-to-noise ratios between the septum and blood pool increased by 14.50% inin vivomeasurements with a k-space compared to an image-space-based SRR.Significance. The proposed approach provided whole-heart high-resolution 1.3 mm isotropic T1 maps in an overall acquisition time of approximately three minutes. Small structures, such as the atrial and right ventricular walls, could be visualized in the T1 maps.

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.

STEAM-SASHA: a novel approach for blood- and fat-suppressed native T1 measurement in the right ventricular myocardium.

OBJECTIVE: The excellent blood and fat suppression of stimulated echo acquisition mode (STEAM) can be combined with saturation recovery single-shot acquisition (SASHA) in a novel STEAM-SASHA sequence for right ventricular (RV) native T1 mapping. MATERIALS AND METHODS: STEAM-SASHA splits magnetization preparation over two cardiac cycles, nulling blood signal and allowing fat signal to decay. Breath-hold T1 mapping was performed in a T1 phantom and twice in 10 volunteers using STEAM-SASHA and a modified Look-Locker sequence at peak systole at 3T. T1 was measured in 3 RV regions, the septum and left ventricle (LV). RESULTS: In phantoms, MOLLI under-estimated while STEAM-SASHA over-estimated T1, on average by 3.0% and 7.0% respectively, although at typical 3T myocardial T1 (T1 > 1200 ms) STEAM-SASHA was more accurate. In volunteers, T1 was higher using STEAM-SASHA than MOLLI in the LV and septum (p = 0.03, p = 0.006, respectively), but lower in RV regions (p > 0.05). Inter-study, inter-observer and intra-observer coefficients of variation in all regions were < 15%. Blood suppression was excellent with STEAM-SASHA and noise floor effects were minimal. DISCUSSION: STEAM-SASHA provides accurate and reproducible T1 in the RV with excellent blood and fat suppression. STEAM-SASHA has potential to provide new insights into pathological changes in the RV in future studies.

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.