Heart rate and early progression of cardiac allograft vasculopathy: A prospective study using highly automated 3-D optical coherence tomography analysis.

INTRODUCTION: Heart rate slowing agents are frequently prescribed to manage heart transplant (HTx) patients with the assumption that higher heart rate is a risk factor in cardiovascular disease. PATIENTS AND METHODS: This prospective two-center study investigated early progression of cardiac allograft vasculopathy (CAV) in 116 HTx patients. Examinations by coronary optical coherence tomography and 24-hour ambulatory ECG monitoring were performed both at baseline (1 month after HTx) and during follow-up (12 months after HTx). RESULTS: During the first post-HTx year, we observed a significant reduction in the mean coronary luminal area from 9.0 ± 2.5 to 8.0 ± 2.4 mm2 (P < .001), and progression in mean intimal thickness (IT) from 106.5 ± 40.4 to 130.1 ± 53.0 µm (P < .001). No significant relationship was observed between baseline and follow-up mean heart rates and IT progression (R = .02, P = .83; R = -.13, P = .18). We found a mild inverse association between beta-blocker dosage at 12 months and IT progression (R = -.20, P = .035). CONCLUSION: Our study did not confirm a direct association between mean heart rate and progression of CAV. The role of beta blockers warrants further investigation, with our results indicating that they may play a protective role in early CAV development.

Plaque volume and plaque risk profile in diabetic vs. non-diabetic patients undergoing lipid-lowering therapy: a study based on 3D intravascular ultrasound and virtual histology.

BACKGROUND: Coronary atherosclerosis progresses faster in patients with diabetes mellitus (DM) and causes higher morbidity and mortality in such patients compared to non-diabetics ones (non-DM). We quantify changes in plaque volume and plaque phenotype during lipid-lowering therapy in DM versus non-DM patients using advanced intracoronary imaging. METHODS: We analyzed data from 61 patients with stable angina pectoris included to the PREDICT trial searching for prediction of plaque changes during intensive lipid-lowering therapy (40 mg rosuvastatin daily). Geometrically correct, fully 3-D representation of the vascular wall surfaces and intravascular ultrasound virtual histology (IVUS-VH) defined tissue characterization was obtained via fusion of two-plane angiography and IVUS-VH. Frame-based indices of plaque morphology and virtual histology analyses were computed and averaged in 5 mm long baseline/follow-up registered vessel segments covering the entire length of the two sequential pullbacks (baseline, 1-year). We analyzed 698 5-mm-long segments and calculated the Liverpool active plaque score (LAPS). RESULTS: Despite reaching similar levels of LDL cholesterol (DM 2.12 ± 0.91 mmol/l, non-DM 1.8 ± 0.66 mmol/l, p = 0.21), DM patients experienced, compared to non-DM ones, higher progression of mean plaque area (0.47 ± 1.15 mm2 vs. 0.21 ± 0.97, p = 0.001), percent atheroma volume (0.7 ± 2.8% vs. - 1.4 ± 2.5%, p = 0.007), increase of LAPS (0.23 ± 1.66 vs. 0.13 ± 1.79, p = 0.018), and exhibited more locations with TCFA (Thin-Cap Fibro-Atheroma) plaque phenotype in 5 mm vessel segments (20.3% vs. 12.5%, p = 0.01). However, only non-DM patients reached significant decrease of LDL cholesterol. Plaque changes were more pronounced in PIT (pathologic intimal thickening) compared to TCFA with increased plaque area in both phenotypes in DM patients. CONCLUSION: Based on detailed 3D analysis, we found advanced plaque phenotype and further atherosclerosis progression in DM patients despite the same reached levels of LDLc as in non-DM patients. Trial registration ClinicalTrials.gov identifier: NCT01773512.

The accuracy of detailed analysis of optical coherence tomography in detection of plaque lipid content: dual-imaging study with optical coherence tomography and near-infrared spectroscopy.

BACKGROUND: Lipid-rich plaque covered by a thin fibrous cap (FC) has been identified as a frequent morphological substrate for the development of acute coronary syndrome. Optical coherence tomography (OCT) permits the identification and measurement of the FC. Near-infrared spectroscopy (NIRS) has been approved for detection of coronary lipids. AIMS: We aimed to assess the ability of detailed OCT analysis to identify coronary lipids, using NIRS as the reference method. METHODS: In total, 40 patients with acute coronary syndrome underwent imaging of a non-culprit lesion by both NIRS and OCT. For each segment, the NIRS-derived 4 mm segment with maximal lipid core burden index (maxLCBI4mm) was assessed. OCT analysis was performed using a semi-automated method including measurement of the fibrous cap thickness (FCT) of all detected fibroatheromas. Subsequent quantitative volumetric evaluation furnished FCT, FC surface area (FC SA), lipid arc, and FC (fibrous cap) volume data. OCT features of lipid plaques were compared with maxLCBI4mm. Predictors of maxLCBI4mm >400 was assessed by using univariable and multivariable analysis. RESULTS: OCT features (mean FCT, total FC SA, FC volume, maximal, mean, and total lipid arcs) strongly correlated with the maxLCBI4mm (p = 0.012 for the mean FCT, respectively p < 0.001 for all other aforementioned features). The strongest predictors of maxLCBI4mm >400 were the maximal (p = 0.002) and mean (p = 0.002) lipid arc, and total FC SA (p = 0.012). CONCLUSIONS: We found a strong correlation between the OCT-derived features and NIRS findings. Detailed OCT analysis may be reliably used for detection of the presence of coronary lipids.

Validation of a semi-automatic software for optical coherence tomography - analysis in heart transplanted patients.

Optical Coherence Tomography (OCT) is an intravascular imaging modality enabling detailed evaluation of cardiac allograft vasculopathy (CAV) after heart transplantation (HTx). However, its clinical application remains hampered by time-consuming manual quantitative analysis. We aimed to validate a semi-automated quantitative OCT analysis software (Iowa Coronary Wall Analyzer, ICWA-OCT) to improve OCT-analysis in HTx patients. 23 patients underwent OCT evaluation of all three major coronary arteries at 3 months (3M) and 12 months (12M) after HTx. We analyzed OCT recordings using the semiautomatic software and compared results with measurements from a validated manual software. For semi-automated analysis, 31,228 frames from 114 vessels were available. The validation was based on a subset of 4287 matched frames. We applied mixed model statistics to accommodate the multilevel data structure with method as a fixed effect. Lumen (minimum, mean, maximum) and media (mean, maximum) metrics showed no significant differences. Mean and maximum intima area were underestimated by the semi-automated method (ß-methodmean = - 0.289 mm2, p < 0.01; ß-methodmax = - 0.695 mm2, p < 0.01). Bland-Altman analyses showed increasing semi-automatic underestimation of intima measurements with increasing intimal extent. Comparing 3M to 12M progression between methods, mean intimal area showed minor underestimation (ß-methodmean = - 1.03 mm2, p = 0.04). Lumen and media metrics showed excellent agreement between the manual and semi-automated method. Intima metrics and progressions from 3M to 12M were slightly underestimated by the semi-automated OCT software with unknown clinical relevance. The semi-automated software has the future potential to provide robust and time-saving evaluation of CAV progression.

Virtual histology evaluation of atherosclerosis regression during atorvastatin and ezetimibe administration: HEAVEN study.

BACKGROUND: There is no study focusing on changes in coronary atherosclerosis during dual lipid-lowering therapy with statin and ezetimibe. METHODS AND RESULTS: Eighty-nine patients with stable angina randomized in a 1:1 ratio to Group A (aggressive therapy: atorvastatin 80mg, ezetimibe 10mg) and Group S (standard therapy) were analyzed. Treatment period was 12 months. Coronary arteries were examined by intravascular ultrasound and virtual histology. We found a decrease in the percent atheroma volume (PAV) (-0.4%) in Group A compared with an increase (+1.4%) in Group S (P=0.014) and this was accompanied by an increased frequency of combined atherosclerosis regression (increased lumen volume+decreased PAV) in group A (40.5%) compared with group S (14.9%) (P=0.007). The target low-density lipoprotein cholesterol level <2mmol/L, presence of at least 4 of 5 atherosclerotic risk factors, and decreased level of vascular cellular adhesive molecule were independent predictors of plaque regression. There were no significant differences in plaque composition between the 2 groups over the study duration. However, during analysis of the 2 groups together, fibrous and fibro-fatty tissues decreased and dense calcification and necrotic core increased during follow-up. CONCLUSIONS: Dual lipid-lowering therapy starts atherosclerosis regression, but does not lead to significant changes in plaque composition. The continuous shift in plaque from fibro and fibro-fatty to necrotic with calcification was present in both groups.

Fibrous Cap Thickness Predicts Stable Coronary Plaque Progression: Early Clinical Validation of a Semiautomated OCT Technology.

Background: Imaging-based characteristics associated with the progression of stable coronary atherosclerotic lesions are poorly defined. Utilizing a combination of optical coherence tomography (OCT) and intravascular ultrasound (IVUS) imaging, we aimed to characterize the lesions prone to progression through clinical validation of a semiautomated OCT computational program. Methods: Patients with stable coronary artery disease underwent nonculprit vessel imaging with IVUS and OCT at baseline and IVUS at the 12-month follow-up. After coregistration of baseline and follow-up IVUS images, paired 5-mm segments from each patient were identified, demonstrating the greatest plaque progression and regression as measured by the change in plaque burden. Experienced readers identified plaque features on corresponding baseline OCT segments, and predictors of plaque progression were assessed by multivariable analysis. Each segment then underwent volumetric assessment of the fibrous cap (FC) using proprietary software. Results: Among 23 patients (70% men; median age, 67 years), experienced-reader analysis demonstrated that for every 100 µm increase in mean FC thickness, plaques were 87% less likely to progress (P = .01), which persisted on multivariable analysis controlling for baseline plaque burden (P = .05). Automated FC analysis (n = 17 paired segments) confirmed this finding (P = .01) and found thinner minimal FC thickness (P = .01) and larger FC surface area of <65 µm (P = .02) and <100 µm (P = .04) in progressing segments than in regressing segments. No additional imaging features predicted plaque progression. Conclusions: A semiautomated FC analysis tool confirmed the significant association between thinner FC and stable coronary plaque progression along entire vessel segments, illustrating the diffuse nature of FC thinning and suggesting a future clinical role in predicting the progression of stable coronary artery disease.

Quantitative assessment of the entire thoracic aorta from magnetic resonance images.

OBJECTIVES: Although magnetic resonance imaging is a primary modality for following patients with connective tissue diseases, only a limited amount of the image data is utilised. The purpose of this study was to show the clinical applicability of an automated four-dimensional analysis method of magnetic resonance images of the aorta and develop normative data for the cross-sectional area of the entire thoracic aorta. STUDY DESIGN: Magnetic resonance imaging was obtained serially over 3 years from 32 healthy individuals and 24 patients with aortopathy and a personal or family history of connective tissue disorder. Graph theory-based segmentation was used to determine the cross-sectional area for the thoracic aorta. Healthy individual data were used to construct a nomogram representing the maximum cross-sectional area 5th-95th percentile along the entire thoracic aorta. Aortic root diameters calculated from the cross-sectional area were compared to measured diameters from echocardiographic data. The cross-sectional area of the entire thoracic aorta in patients was compared to healthy individuals. RESULTS: Calculated aortic root diameters correlated with measured diameters from echo data - correlation coefficient was 0.74-0.87. The cross-sectional area in patients was significantly greater in the aortic root, ascending aorta, and descending aorta compared to healthy individuals. CONCLUSION: The presentation of the dimensional data for the entire thoracic aorta shows an important clinical tool for following patients with connective tissue disorders and aortopathy.

Automated segmentation of choroidal layers from 3-dimensional macular optical coherence tomography scans.

BACKGROUND: Changes in choroidal thickness are associated with various ocular diseases, and the choroid can be imaged using spectral-domain optical coherence tomography (SD-OCT) and enhanced depth imaging OCT (EDI-OCT). NEW METHOD: Eighty macular SD-OCT volumes from 80 patients were obtained using the Zeiss Cirrus machine. Eleven additional control subjects had two Cirrus scans done in one visit along with enhanced depth imaging (EDI-OCT) using the Heidelberg Spectralis machine. To automatically segment choroidal layers from the OCT volumes, our graph-theoretic approach was utilized. The segmentation results were compared with reference standards from two independent graders, and the accuracy of automated segmentation was calculated using unsigned/signed border positioning/thickness errors and Dice similarity coefficient (DSC). The repeatability and reproducibility of our choroidal thicknesses were determined by intraclass correlation coefficient (ICC), coefficient of variation (CV), and repeatability coefficient (RC). RESULTS: The mean unsigned/signed border positioning errors for the choroidal inner and outer surfaces are 3.39 ± 1.26 µm (mean ± standard deviation)/- 1.52 ± 1.63 µm and 16.09 ± 6.21 µm/4.73 ± 9.53 µm, respectively. The mean unsigned/signed choroidal thickness errors are 16.54 ± 6.47 µm/6.25 ± 9.91 µm, and the mean DSC is 0.949 ± 0.025. The ICC (95% confidence interval), CV, RC values are 0.991 (0.977-0.997), 2.48%, 14.25 µm for the repeatability and 0.991 (0.977-0.997), 2.49%, 14.30 µm for the reproducibility studies, respectively. COMPARISON WITH EXISTING METHOD(S): The proposed method outperformed our previous method using choroidal vessel segmentation and inter-grader variability. CONCLUSIONS: This automated segmentation method can reliably measure choroidal thickness using different OCT platforms.

Intravitreal Fluocinolone Acetonide May Decelerate Diabetic Retinal Neurodegeneration.

Purpose: There is no prevention or treatment for diabetic retinal neurodegeneration (DRN), which is a complication of diabetes that can occur independently of diabetic retinopathy (DR). We hypothesized that an intravitreal fluocinolone acetonide (FAc) implant may affect the rate of DRN when used in patients with diabetic macular edema (DME). Methods: In this retrospective analysis, optical coherence tomography with neuroretinal analysis was obtained at 3-month intervals from 130 patients in the USER study both before (mean duration 903 days, range 35-4005 days) and after administration of FAc (mean 408 days, range 7 to 756 days). The rate of DRN was defined as the change over time on inner neuroretinal thickness using logistic regression. A DRN rate was calculated independently for two areas: region 1 located within 1.5 mm of the fovea, and region 2 from 1.5 mm to 3.0 mm from the fovea. Results: In regions of the macula more than 1.5 mm from the central fovea, there was a statistically significant decrease in the rate of DRN in the post-FAc period. The pre-FAc neuroretinal loss in this area occurred at 4.0 µm/y, compared with a post-FAc loss rate of 1.1 µm/y (P = 0.001). Conclusions: This retrospective study suggests that FAc may decelerate the rate of inner retinal thinning in patients with persistent DME. Further prospective studies are necessary to determine the effects of FAc on the rate of DRN in patients with DME.

Predicting Locations of High-Risk Plaques in Coronary Arteries in Patients Receiving Statin Therapy.

Features of high-risk coronary artery plaques prone to major adverse cardiac events (MACE) were identified by intravascular ultrasound (IVUS) virtual histology (VH). These plaque features are: thin-cap fibroatheroma (TCFA), plaque burden PB ≥ 70%, or minimal luminal area MLA ≤ 4 mm2. Identification of arterial locations likely to later develop such high-risk plaques may help prevent MACE. We report a machine learning method for prediction of future high-risk coronary plaque locations and types in patients under statin therapy. Sixty-one patients with stable angina on statin therapy underwent baseline and one-year follow-up VH-IVUS non-culprit vessel examinations followed by quantitative image analysis. For each segmented and registered VH-IVUS frame pair ( ), location-specific ( mm) vascular features and demographic information at baseline were identified. Seven independent support vector machine classifiers with seven different feature subsets were trained to predict high-risk plaque types one year later. A leave-one-patient-out cross-validation was used to evaluate the prediction power of different feature subsets. The experimental results showed that our machine learning method predicted future TCFA with correctness of 85.9%, 81.7%, and 77.0% (G-mean) for baseline plaque phenotypes of TCFA, thick-cap fibroatheroma, and non-fibroatheroma, respectively. For predicting PB ≥ 70%, correctness was 80.8% for baseline PB ≥ 70% and 85.6% for 50% ≤ PB < 70%. Accuracy of predicted MLA ≤ 4 mm2 was 81.6% for baseline MLA ≤ 4 mm2 and 80.2% for 4 mm2 < MLA ≤ 6 mm2. Location-specific prediction of future high-risk coronary artery plaques is feasible through machine learning using focal vascular features and demographic variables. Our approach outperforms previously reported results and shows the importance of local factors on high-risk coronary artery plaque development.

Quantitative 3D Analysis of Coronary Wall Morphology in Heart Transplant Patients: OCT-Assessed Cardiac Allograft Vasculopathy Progression.

Cardiac allograft vasculopathy (CAV) accounts for about 30% of all heart-transplant (HTx) patient deaths. For patients at high risk for CAV complications after HTx, therapy must be initiated early to be effective. Therefore, new phenotyping approaches are needed to identify such HTx patients at the earliest possible time. Coronary optical coherence tomography (OCT) images were acquired from 50 HTx patients 1 and 12 months after HTx. Quantitative analysis of coronary wall morphology used LOGISMOS segmentation strategy to simultaneously identify three wall-layer surfaces for the entire pullback length in 3D: luminal, outer intimal, and outer medial surfaces. To quantify changes of coronary wall morphology between 1 and 12 months after HTx, the two pullbacks were mutually co-registered. Validation of layer thickness measurements showed high accuracy of performed layer analyses with layer thickness measures correlating well with manually-defined independent standard (Rautomated2 = 0.93, y=1.0x-6.2µm), average intimal+medial thickness errors were 4.98 ±â€¯31.24 µm, comparable with inter-observer variability. Quantitative indices of coronary wall morphology 1 month and 12 months after HTx showed significant local as well as regional changes associated with CAV progression. Some of the newly available fully-3D baseline indices (intimal layer brightness, medial layer brightness, medial thickness, and intimal+medial thickness) were associated with CAV-related progression of intimal thickness showing promise of identifying patients subjected to rapid intimal thickening at 12 months after HTx from OCT-image data obtained just 1 month after HTx. Our approach allows quantification of location-specific alterations of coronary wall morphology over time and is sensitive even to very small changes of wall layer thicknesses that occur in patients following heart transplant.

Early detection of cardiac allograft vasculopathy using highly automated 3-dimensional optical coherence tomography analysis.

BACKGROUND: Optical coherence tomography (OCT)-based studies of cardiac allograft vasculopathy (CAV) published thus far have focused mainly on frame-based qualitative analysis of the vascular wall. Full capabilities of this inherently 3-dimensional (3D) imaging modality to quantify CAV have not been fully exploited. METHODS: Coronary OCT imaging was performed at 1 month and 12 months after heart transplant (HTx) during routine surveillance cardiac catheterization. Both baseline and follow-up OCT examinations were analyzed using proprietary, highly automated 3D graph-based optimal segmentation software. Automatically identified borders were efficiently adjudicated using our "just-enough-interaction" graph-based segmentation approach that allows to efficiently correct local and regional segmentation errors without slice-by-slice retracing of borders. RESULTS: A total of 50 patients with paired baseline and follow-up OCT studies were included. After registration of baseline and follow-up pullbacks, a total of 356 ± 89 frames were analyzed per patient. During the first post-transplant year, significant reduction in the mean luminal area (p = 0.028) and progression in mean intimal thickness (p = 0.001) were observed. Proximal parts of imaged coronary arteries were affected more than distal parts (p < 0.001). High levels of LDL cholesterol (p = 0.02) and total cholesterol (p = 0.031) in the first month after HTx were the main factors associated with early CAV development. CONCLUSIONS: Our novel, highly automated 3D OCT image analysis method for analyzing intimal and medial thickness in HTx recipients provides fast, accurate, and highly detailed quantitative data on early CAV changes, which are characterized by significant luminal reduction and intimal thickness progression as early as within the first 12 months after HTx.

Nerve Fiber Layer Thickness and Characteristics Associated with Glaucoma in Community Living Older Adults: Prelude to a Screening Trial?

PURPOSE: To examine the associations of nerve fiber layer (NFL) thickness with other ocular characteristics in older adults. METHODS: Participants in the Beaver Dam Eye Study (2008-2010) underwent spectral domain optical coherence tomography (SD-OCT) scans of the optic nerve head, imaging of optic discs, frequency doubling technology (FDT) perimetry, measurement of intraocular pressure (IOP), and an interview concerning their history of glaucoma and use of drops to lower eye pressure. Self-reported histories of glaucoma and the use of drops to lower eye pressure were obtained at follow-up examinations (2014-2016). RESULTS: NFL thickness measured on OCTs varied by location around the optic nerve. Age was associated with mean NFL thickness. Mean NFL was thinnest in eyes with larger cup/disc (C/D) ratios. Horizontal hemifield defects or other optic nerve-field defects were associated with thinner NFL. NFL in persons who reported taking eye drops for high intraocular pressure was thinner compared to those not taking drops. After accounting for the presence of high intraocular pressure, large C/D ratios or hemifield defects, eyes with thinner NFL in the arcades were more likely (OR = 2.3 for 30 micron thinner NFL, p = 0.04) to have incident glaucoma at examination 5 years later. CONCLUSION: Retinal NFL thickness was associated with a new history of self-reported glaucoma 5 years later. A trial testing the usefulness of NFL as part of a screening battery for predicting glaucoma in those previously undiagnosed might lead to improved case finding and, ultimately, to diminishing the risk of visual field loss.

Pathologic Intimal Thickening Plaque Phenotype: Not as Innocent as Previously Thought. A Serial 3D Intravascular Ultrasound Virtual Histology Study.

INTRODUCTION AND OBJECTIVES: Pathologic intimal thickening (PIT) has been considered a benign plaque phenotype. We report plaque phenotypic changes in a baseline/follow-up intravascular ultrasound-based virtual histology study. METHODS: A total of 61 patients with stable coronary artery disease were analyzed from the HEAVEN trial (89 patients randomized between routine statin therapy vs atorvastatin 80mg and ezetimibe 10mg) with serial intravascular ultrasound imaging of nonculprit vessels. We compared changes in 693 baseline and follow-up 5-mm long segments in a novel risk score, Liverpool Active Plaque Score (LAPS), plaque parameters, and plaque composition. RESULTS: The PIT showed the highest increase of risk score and, with fibrous plaque, also the LAPS. Necrotic core (NC) abutting to the lumen increased in PIT (22 ± 51.7; P = .0001) and in fibrous plaque (17.9 ± 42.6; P = .004) but decreased in thin cap fibroatheroma (TCFA) (â¿¿15.14 ± 52.2; P = .001). The PIT was the most likely of all nonthin cap fibroatheroma plaque types to transform into TCFA at follow-up (11% of all TCFA found during follow-up and 35.9% of newly-developed TCFA), but showed (together with fibrous plaque) the lowest stability during lipid-lowering therapy (24.7% of PIT remained PIT and 24.5% of fibrous plaque remained fibrous plaque). CONCLUSIONS: Over the 1-year follow-up, PIT was the most dynamic of the plaque phenotypes and was associated with an increase of risk score and LAPS (together with fibrous plaque), NC percentage (together with fibrous plaque) and NC abutting to the lumen, despite a small reduction of plaque volume during lipid-lowering therapy. The PIT was the main source for new TCFA segments.

Optical Coherence Tomography Analysis Based Prediction of Humphrey 24-2 Visual Field Thresholds in Patients With Glaucoma.

Purpose: A pilot study showed that prediction of individual Humphrey 24-2 visual field (HVF 24-2) sensitivity thresholds from optical coherence tomography (OCT) image analysis is possible. We evaluate performance of an improved approach as well as 3 other predictive algorithms on a new, fully independent set of glaucoma subjects. Methods: Subjects underwent HVF 24-2 and 9-field OCT (Heidelberg Spectralis) testing. Nerve fiber (NFL), and ganglion cell and inner plexiform (GCL+IPL) layers were cosegmented and partitioned into 52 sectors matching HVF 24-2 test locations. The Wilcoxon rank sum test was applied to test correlation R, root mean square error (RMSE), and limits of agreement (LoA) between actual and predicted thresholds for four prediction models. The training data consisted of the 9-field OCT and HVF 24-2 thresholds of 111 glaucoma patients from our pilot study. Results: We studied 112 subjects (112 eyes) with early, moderate, or advanced primary and secondary open angle glaucoma. Subjects with less than 9 scans (15/112) or insufficient quality segmentations (11/97) were excluded. Retinal ganglion cell axonal complex (RGC-AC) optimized had superior average R = 0.74 (95% confidence interval [CI], 0.67-0.76) and RMSE = 5.42 (95% CI, 5.1-5.7) dB, which was significantly better (P < 0.05/3) than the other three models: Naïve (R = 0.49; 95% CI, 0.44-0.54; RMSE = 7.24 dB; 95% CI, 6.6-7.8 dB), Garway-Heath (R = 0.66; 95% CI, 0.60-0.68; RMSE = 6.07 dB; 95% CI, 5.7-6.5 dB), and Donut (R = 0.67; 95% CI, 0.61-0.69; RMSE = 6.08 dB, 95% CI, 5.8-6.4 dB). Conclusions: The proposed RGC-AC optimized predictive algorithm based on 9-field OCT image analysis and the RGC-AC concept is superior to previous methods and its performance is close to the reproducibility of HVF 24-2.

Remodeling characteristics of minimally diseased coronary arteries are consistent along the length of the artery.

Using a method that creates anatomically correct, 3-dimensional arterial reconstructions, 55 minimally diseased coronary arteries from 40 patients were studied. Homogenous remodeling characteristics along the entire length of the artery were observed in 48 arteries (87%). In the aggregate, arteries exhibited compensatory expansive remodeling. Individually, the full spectrum of compensatory expansive remodeling (60%), excessive expansive remodeling (21%), and constrictive remodeling (19%) was observed across arteries. Each artery was consistent in its remodeling characteristics from proximal to distal portions of the artery, and the remodeling pattern of each artery was independent within the same patient.

Coronary arteries: imaging, reconstruction, and fluid dynamic analysis.

Atherosclerosis is the underlying cause of most cardiovascular-related deaths in industrialized nations. Determining the etiology of atherosclerosis and detecting lesions in the early stages of the disease for possible pharmacological or mechanical intervention have been challenges facing cardiovascular researchers. In addition to genetic and environmental factors, the formation and growth of atheroma have been linked to the complex fluid dynamics and mass transport in these arterial segments. This article reviews the current state of affairs in imaging modalities and image processing techniques that allow the visualization and morphologically realistic reconstruction of coronary arterial geometry to aid in the diagnosis and treatment of coronary artery disease (CAD). In addition, studies pertaining to our current understanding of the complex flow dynamics in the coronary arteries and the relationship between fluid-induced stresses on the initiation and growth of the atherosclerotic lesions are also reviewed. The article concludes with a brief discussion on possible future directions of research that will advance our knowledge of this challenging problem.

Plaque development, vessel curvature, and wall shear stress in coronary arteries assessed by X-ray angiography and intravascular ultrasound.

The relationships among vascular geometry, hemodynamics, and plaque development in the coronary arteries are complex and not yet well understood. This paper reports a methodology for the quantitative analysis of in vivo coronary morphology and hemodynamics, with particular emphasis placed on the critical issues of image segmentation and the automated classification of disease severity. We were motivated by the observation that plaque more often developed at the inner curvature of a vessel, presumably due to the relatively lower wall shear stress at these locations. The presented studies are based on our validated methodology for the three-dimensional fusion of intravascular ultrasound (IVUS) and X-ray angiography, introducing a novel approach for IVUS segmentation that incorporates a robust, knowledge-based cost function and a fully optimal, three-dimensional segmentation algorithm. Our first study shows that circumferential plaque distribution depends on local vessel curvature in the majority of vessels. The second study analyzes the correlation between plaque distribution and wall shear stress in a set of 48 in vivo vessel segments. The results were conclusive for both studies, with a stronger correlation of circumferential plaque thickness with local curvature than with wall shear stress. The inverse relationship between local wall shear stress and plaque thickness was significantly more pronounced (p<0.025) in vessel cross sections exhibiting compensatory enlargement (positive remodeling) without luminal narrowing than when the full spectrum of disease severity was considered. The inverse relationship was no longer observed in vessels where less than 35% of vessel cross sections remained without luminal narrowing. The findings of this study confirm, in vivo, the hypothesis that relatively lower wall shear stress is associated with early plaque development.

DICOM for quantitative imaging biomarker development: a standards based approach to sharing clinical data and structured PET/CT analysis results in head and neck cancer research.

Background. Imaging biomarkers hold tremendous promise for precision medicine clinical applications. Development of such biomarkers relies heavily on image post-processing tools for automated image quantitation. Their deployment in the context of clinical research necessitates interoperability with the clinical systems. Comparison with the established outcomes and evaluation tasks motivate integration of the clinical and imaging data, and the use of standardized approaches to support annotation and sharing of the analysis results and semantics. We developed the methodology and tools to support these tasks in Positron Emission Tomography and Computed Tomography (PET/CT) quantitative imaging (QI) biomarker development applied to head and neck cancer (HNC) treatment response assessment, using the Digital Imaging and Communications in Medicine (DICOM(®)) international standard and free open-source software. Methods. Quantitative analysis of PET/CT imaging data collected on patients undergoing treatment for HNC was conducted. Processing steps included Standardized Uptake Value (SUV) normalization of the images, segmentation of the tumor using manual and semi-automatic approaches, automatic segmentation of the reference regions, and extraction of the volumetric segmentation-based measurements. Suitable components of the DICOM standard were identified to model the various types of data produced by the analysis. A developer toolkit of conversion routines and an Application Programming Interface (API) were contributed and applied to create a standards-based representation of the data. Results. DICOM Real World Value Mapping, Segmentation and Structured Reporting objects were utilized for standards-compliant representation of the PET/CT QI analysis results and relevant clinical data. A number of correction proposals to the standard were developed. The open-source DICOM toolkit (DCMTK) was improved to simplify the task of DICOM encoding by introducing new API abstractions. Conversion and visualization tools utilizing this toolkit were developed. The encoded objects were validated for consistency and interoperability. The resulting dataset was deposited in the QIN-HEADNECK collection of The Cancer Imaging Archive (TCIA). Supporting tools for data analysis and DICOM conversion were made available as free open-source software. Discussion. We presented a detailed investigation of the development and application of the DICOM model, as well as the supporting open-source tools and toolkits, to accommodate representation of the research data in QI biomarker development. We demonstrated that the DICOM standard can be used to represent the types of data relevant in HNC QI biomarker development, and encode their complex relationships. The resulting annotated objects are amenable to data mining applications, and are interoperable with a variety of systems that support the DICOM standard.

Automated Segmentability Index for Layer Segmentation of Macular SD-OCT Images.

PURPOSE: To automatically identify which spectral-domain optical coherence tomography (SD-OCT) scans will provide reliable automated layer segmentations for more accurate layer thickness analyses in population studies. METHODS: Six hundred ninety macular SD-OCT image volumes (6.0 × 6.0 × 2.3 mm3) were obtained from one eyes of 690 subjects (74.6 ± 9.7 [mean ± SD] years, 37.8% of males) randomly selected from the population-based Rotterdam Study. The dataset consisted of 420 OCT volumes with successful automated retinal nerve fiber layer (RNFL) segmentations obtained from our previously reported graph-based segmentation method and 270 volumes with failed segmentations. To evaluate the reliability of the layer segmentations, we have developed a new metric, segmentability index SI, which is obtained from a random forest regressor based on 12 features using OCT voxel intensities, edge-based costs, and on-surface costs. The SI was compared with well-known quality indices, quality index (QI), and maximum tissue contrast index (mTCI), using receiver operating characteristic (ROC) analysis. RESULTS: The 95% confidence interval (CI) and the area under the curve (AUC) for the QI are 0.621 to 0.805 with AUC 0.713, for the mTCI 0.673 to 0.838 with AUC 0.756, and for the SI 0.784 to 0.920 with AUC 0.852. The SI AUC is significantly larger than either the QI or mTCI AUC (P < 0.01). CONCLUSIONS: The segmentability index SI is well suited to identify SD-OCT scans for which successful automated intraretinal layer segmentations can be expected. TRANSLATIONAL RELEVANCE: Interpreting the quantification of SD-OCT images requires the underlying segmentation to be reliable, but standard SD-OCT quality metrics do not predict which segmentations are reliable and which are not. The segmentability index SI presented in this study does allow reliable segmentations to be identified, which is important for more accurate layer thickness analyses in research and population studies.