Treatment Effect of Drug-Coated Balloons Is Durable to 3 Years in the Femoropopliteal Arteries: Long-Term Results of the IN.PACT SFA Randomized Trial

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Background—

Randomized controlled trials have reported favorable 1-year outcomes with drug-coated balloons (DCBs) for the treatment of symptomatic peripheral arterial disease when compared with standard percutaneous transluminal angioplasty (PTA). Evidence remains limited on the durability of the treatment effect with DCBs in the longer term.

Methods and Results—

IN.PACT SFA is a single-blind, randomized trial (Randomized Trial of IN.PACT Admiral Paclitaxel-Coated Percutaneous Transluminal Angioplasty [PTA] Balloon Catheter vs Standard PTA for the Treatment of Atherosclerotic Lesions in the Superficial Femoral Artery [SFA] and/or Proximal Popliteal Artery [PPA]) that enrolled 331 patients with symptomatic (Rutherford 2–4) femoropopliteal lesions up to 18 cm in length. Patients were randomized 2:1 to receive treatment with DCB or PTA. The 36-month assessments included primary patency, freedom from clinically driven target lesion revascularization, major adverse events, and functional outcomes. At 36 months, primary patency remained significantly higher among patients treated with DCB compared with PTA (69.5% versus 45.1%; log rank P<0.001). The rates of clinically driven target lesion revascularization were 15.2% and 31.1% (P=0.002) for the DCB and PTA groups, respectively. Functional outcomes were similarly improved between treatment groups even though subjects in the DCB group required significantly fewer reinterventions versus those in the PTA group (P<0.001 for target lesion revascularization, P=0.001 for target vessel revascularization). There were no device- or procedure-related deaths as adjudicated by an independent Clinical Events Committee.

Conclusions—

Three-year results demonstrate a durable and superior treatment effect among patients treated with DCB versus standard PTA, with significantly higher primary patency and lower clinically driven target lesion revascularization, resulting in similar functional improvements with reduced need for repeat interventions.

Clinical Trial Registration—

URL: http://www.clinicaltrials.gov. Unique identifiers: NCT01175850 for IN.PACT SFA phase I in the European Union and NCT01566461 for IN.PACT SFA phase II in the United States.

Acute and Midterm Outcomes of Antegrade vs Retrograde Crossing Strategies for Endovascular Treatment of Iliac Artery Chronic Total Occlusions

Purpose: To examine whether an antegrade or retrograde crossing strategy for treatment of iliac artery chronic total occlusions (CTOs) is associated with differences in procedural or midterm outcomes. Materials and Methods: A dual-center retrospective cohort study was conducted in 168 patients (mean age 66.4±10.6 years; 116 men) treated for CTOs in 110 common iliac arteries (CIA), 52 external iliac arteries (EIA), and 26 combined CIA/EIAs. Logistic regression models were developed to determine the association between crossing strategy and procedural complications, 1- and 3-year target lesion revascularization (TLR), and major adverse limb events (MALE). Results are presented as the odds ratio (OR) and 95% confidence interval (CI). Results: An initial antegrade strategy was more common for EIA CTOs (p<0.005), and an initial retrograde strategy was more often used in CIA (p<0.005) and combined CIA/EIA (p<0.005) CTOs. Crossover to an alternate approach was required in 27.6% of initial antegrade attempts and 9.6% of initial retrograde attempts. EIA CTOs were the most likely lesions to be treated successfully with the initial attempt (either strategy). In all, 123 (65.4%) lesions were successfully crossed with a final retrograde approach and 65 with a final antegrade approach. Overall target lesion success was high for both groups (95.1% vs 93.2%, p=0.456). Lesions treated with a final retrograde approach were shorter (75.3±34.9 vs 87.6±31.3 mm, p=0.005) and were more likely to be treated with a reentry device (34.2% vs 9.2%, p<0.001) and with balloon-expandable stents (39.2% vs 17.7%, p=0.005). The final antegrade approach was associated with a lower risk of target lesion complications (OR 0.07, 95% CI 0.01 to 0.81, p=0.034). The two crossing approaches were associated with similar estimates of 1- and 3-year TLR and MALE. Conclusion: A final antegrade approach was associated with lower rates for complications but the 2 approaches were similar in terms of lesion success, TLR, and MALE. The EIA CTOs were more likely to be treated with an antegrade approach and more likely to be crossed successfully with the initial approach irrespective of the crossing direction.

A Special Report on Changing Trends in Preventive Stroke/Cardiovascular Risk Assessment Via B-Mode Ultrasonography

PURPOSE OF REVIEW

Cardiovascular disease (CVD) and stroke risk assessment have been largely based on the success of traditional statistically derived risk calculators such as Pooled Cohort Risk Score or Framingham Risk Score. However, over the last decade, automated computational paradigms such as machine learning (ML) and deep learning (DL) techniques have penetrated into a variety of medical domains including CVD/stroke risk assessment. This review is mainly focused on the changing trends in CVD/stroke risk assessment and its stratification from statistical-based models to ML-based paradigms using non-invasive carotid ultrasonography.

RECENT FINDINGS

In this review, ML-based strategies are categorized into two types: non-image (or conventional ML-based) and image-based (or integrated ML-based). The success of conventional (non-image-based) ML-based algorithms lies in the different data-driven patterns or features which are used to train the ML systems. Typically these features are the patients' demographics, serum biomarkers, and multiple clinical parameters. The integrated (image-based) ML-based algorithms integrate the features derived from the ultrasound scans of the arterial walls (such as morphological measurements) with conventional risk factors in ML frameworks. Even though the review covers ML-based system designs for carotid and coronary ultrasonography, the main focus of the review is on CVD/stroke risk scores based on carotid ultrasound. There are two key conclusions from this review: (i) fusion of image-based features with conventional cardiovascular risk factors can lead to more accurate CVD/stroke risk stratification; (ii) the ability to handle multiple sources of information in big data framework using artificial intelligence-based paradigms (such as ML and DL) is likely to be the future in preventive CVD/stroke risk assessment.

Ranking of stroke and cardiovascular risk factors for an optimal risk calculator design: Logistic regression approach

PURPOSE

Conventional cardiovascular risk factors (CCVRFs) and carotid ultrasound image-based phenotypes (CUSIP) are independently associated with long-term risk of cardiovascular (CV) disease. In this study, 26 cardiovascular risk (CVR) factors which consisted of a combination of CCVRFs and CUSIP together were ranked. Further, an optimal risk calculator using AtheroEdge composite risk score (AECRS1.0) was designed and benchmarked against seven conventional CV risk (CVR) calculators.

METHODS

Two types of ranking were performed: (i) ranking of 26 CVR factors and (ii) ranking of eight types of 10-year risk calculators. In the first case, multivariate logistic regression was used to compute the odds ratio (OR) and in the second, receiver operating characteristic curves were used to evaluate the performance of eight types of CVR calculators using SPSS23.0 and MEDCALC12.0 with validation against STATA15.0.

RESULTS

The left and right common carotid arteries (CCA) of 202 Japanese patients were examined to obtain 404 ultrasound scans. CUSIP ranked in the top 50% of the 26 covariates. Intima-media thickness variability (IMTV) and IMTV_10yr were the most influential carotid phenotypes for left CCA (OR = 250, P < 0.0001 and OR = 207, P < 0.0001 respectively) and right CCA (OR = 1614, P < 0.0001 and OR = 626, P < 0.0001 respectively). However, for the mean CCA, AECRS1.0 and AECRS1.0_10yr reported the most highly significant OR among all the CVR factors (OR = 1.073, P < 0.0001 and OR = 1.104, P < 0.0001). AECRS1.0_10yr also reported highest area-under-the-curve (AUC = 0.904, P < 0.0001) compared to seven types of conventional calculators. Age and glycated haemoglobin reported highest OR (1.96, P < 0.0001 and 1.05, P = 0.012) among all other CCVRFs.

CONCLUSION

AECRS1.0_10yr demonstrated the best performance due to presence of CUSIP and ranked at the first place with highest AUC.

Nonlinear model for the carotid artery disease 10-year risk prediction by fusing conventional cardiovascular factors to carotid ultrasound image phenotypes: A Japanese diabetes cohort study

MOTIVATION

This study presents a novel nonlinear model which can predict 10-year carotid ultrasound image-based phenotypes by fusing nine traditional cardiovascular risk factors (ethnicity, gender, age, artery type, body mass index, hemoglobin A1c, hypertension, low-density lipoprotein, and smoking) with five types of carotid automated image phenotypes (three types of carotid intima-media thickness (IMT), wall variability, and total plaque area).

METHODOLOGY

Two-step process was adapted: First, five baseline carotid image-based phenotypes were automatically measured using AtheroEdge^™ (AtheroPoint^™ , CA, USA) system by two operators (novice and experienced) and an expert. Second, based on the annual progression rates of cIMT due to nine traditional cardiovascular risk factors, a novel nonlinear model was adapted for 10-year predictions of carotid phenotypes.

RESULTS

Institute review board (IRB) approved 204 Japanese patients' left/right common carotid artery (407 ultrasound scans) was collected with a mean age of 69 ± 11 years. Age and hemoglobin were reported to have a high influence on the 10-year carotid phenotypes. Mean correlation coefficient (CC) between 10-year carotid image-based phenotype and age was improved by 39.35% in males and 25.38% in females. The area under the curves for the 10-year measurements of five phenotypes IMT_ave10yr , IMT_max10yr , IMT_min10yr , IMTV_10yr , and TPA_10yr were 0.96, 0.94, 0.90, 1.0, and 1.0. Inter-operator variability between two operators showed significant CC (P < 0.0001).

CONCLUSIONS

A nonlinear model was developed and validated by fusing nine conventional CV risk factors with current carotid image-based phenotypes for predicting the 10-year carotid ultrasound image-based phenotypes which may be used risk assessment.

Performance evaluation of 10-year ultrasound image-based stroke/cardiovascular (CV) risk calculator by comparing against ten conventional CV risk calculators: A diabetic study

MOTIVATION

AtheroEdge Composite Risk Score (AECRS1.0_10yr) is an integrated stroke/cardiovascular risk calculator that was recently developed and computes the 10-year risk of carotid image phenotypes by integrating conventional cardiovascular risk factors (CCVRFs). It is therefore important to understand how closely AECRS1.0_10yr is associated with the ten other currently available conventional cardiovascular risk calculators (CCVRCs).

METHODS

The Institutional Review Board of Toho University approved the examination of the left/right common carotid arteries of 202 Japanese patients. Step 1 consists of measurement of AECRS1.0_10yr, given current image phenotypes and CCVRFs. Step 2 consists of computing the risk score using ten different CCVRCs given CCVR factors: QRISK3, Framingham Risk Score (FRS), United Kingdom Prospective Diabetes Study (UKPDS) 56, UKPDS60, Reynolds Risk Score (RRS), Pooled cohort Risk Score (PCRS or ASCVD), Systematic Coronary Risk Evaluation (SCORE), Prospective Cardiovascular Munster Study (PROCAM) calculator, NIPPON, and World Health Organization (WHO) risk. Step 3 consists of computing the closeness factor between AECRS1.0_10yr and ten CCVRCs using cumulative ranking index derived using eight different statistically derived metrics.

RESULTS

AECRS1.0_10yr reported the highest area-under-the-curve (0.927;P < 0.001) among all the risk calculators. The top three CCVRCs closest to AECRS1.0_10yr were QRISK3, FRS, and UKPDS60 with cumulative ranking scores of 2.1, 3.0, and 3.8, respectively.

CONCLUSION

AECRS1.0_10yr produced the largest AUC due to the integration of image-based phenotypes with CCVR factors, and ranked at first place with the highest AUC. Cumulative ranking of ten CCVRCs demonstrated that QRISK3 was the closest calculator to AECRS1.0_10yr, which is also consistent with the industry trend.

State-of-the-art review on deep learning in medical imaging

Deep learning (DL) is affecting each and every sphere of public and private lives and becoming a tool for daily use. The power of DL lies in the fact that it tries to imitate the activities of neurons in the neocortex of human brain where the thought process takes place. Therefore, like the brain, it tries to learn and recognize patterns in the form of digital images. This power is built on the depth of many layers of computing neurons backed by high power processors and graphics processing units (GPUs) easily available today. In the current scenario, we have provided detailed survey of various types of DL systems available today, and specifically, we have concentrated our efforts on current applications of DL in medical imaging. We have also focused our efforts on explaining the readers the rapid transition of technology from machine learning to DL and have tried our best in reasoning this paradigm shift. Further, a detailed analysis of complexities involved in this shift and possible benefits accrued by the users and developers.

Deep learning fully convolution network for lumen characterization in diabetic patients using carotid ultrasound: a tool for stroke risk

Manual ultrasound (US)-based methods are adapted for lumen diameter (LD) measurement to estimate the risk of stroke but they are tedious, error prone, and subjective causing variability. We propose an automated deep learning (DL)-based system for lumen detection. The system consists of a combination of two DL systems: encoder and decoder for lumen segmentation. The encoder employs a 13-layer convolution neural network model (CNN) for rich feature extraction. The decoder employs three up-sample layers of fully convolution network (FCN) for lumen segmentation. Three sets of manual tracings were used during the training paradigm leading to the design of three DL systems. Cross-validation protocol was implemented for all three DL systems. Using the polyline distance metric, the precision of merit for three DL systems over 407 US scans was 99.61%, 97.75%, and 99.89%, respectively. The Jaccard index and Dice similarity of DL lumen segmented region against three ground truth (GT) regions were 0.94, 0.94, and 0.93 and 0.97, 0.97, and 0.97, respectively. The corresponding AUC for three DL systems was 0.95, 0.91, and 0.93. The experimental results demonstrated superior performance of proposed deep learning system over conventional methods in literature. Graphical abstract ᅟ.

State-of-the-art review on automated lumen and adventitial border delineation and its measurements in carotid ultrasound

BACKGROUND AND OBJECTIVE

Accurate, reliable, efficient, and precise measurements of the lumen geometry of the common carotid artery (CCA) are important for (a) managing the progression/regression of atherosclerotic build-up and (b) the risk of stroke. The image-based degree of stenosis in the carotid artery and the plaque burden can be predicted using the automated carotid lumen diameter (LD)/inter-adventitial diameter (IAD) measurements from B-mode ultrasound images. The objective of this review is to present the state-of-the-art methods and systems for the measurement of LD/IAD in CCA based on automated or semi-automated strategies. Further, the performance of these systems is compared based on various metrics for its measurements.

METHODS

The automated algorithms proposed for the segmentation of carotid lumen are broadly classified into two different categories as: region-based and boundary-based. These techniques are discussed in detail specifying their pros and cons. Further, we discuss the challenges encountered in the segmentation process along with its quantitative assessment. Lastly, we present stenosis quantification and risk stratification strategies.

RESULTS

Even though, we have found more boundary-based approaches compared to region-based approaches in the literature, however, the region-based strategy yield more satisfactory performance. Novel risk stratification strategies are presented. On a patient database containing 203 patients, 9 patients are identified as high risk patients, whereas 27 patients are identified as medium risk patients.

CONCLUSIONS

We have presented different techniques for the lumen segmentation of the common carotid artery from B-mode ultrasound images and measurement of lumen diameter and inter-adventitial diameter. We believe that the issue regarding boundary-based techniques can be compensated by taking regional statistics embedded with boundary-based information.

Echolucency-based phenotype in carotid atherosclerosis disease for risk stratification of diabetes patients

AIM

The study investigated the association of carotid ultrasound echolucent plaque-based biomarker with HbA1c, measured as age-adjusted grayscale median (AAGSM) as a function of chronological age, total plaque area, and conventional grayscale median (GSM_conv).

METHODS

Two stages were developed: (a) automated measurement of carotid parameters such as total plaque area (TPA); (b) computing the AAGSM as a function of GSM_conv, age, and TPA. Intra-operator (novice and experienced) analysis was conducted.

RESULTS

IRB approved, 204 patients' left/right CCA (408 images) ultrasound scans were collected: mean age: 69 ± 11 years; mean HbA1c: 6.12 ± 1.47%. A moderate inverse correlation was observed between AAGSM and HbA1c (CC of -0.13, P = 0.01), compared to GSM (CC of -0.06, P = 0.24). The RCCA and LCCA showed CC of -0.18, P < 0.01 and -0.08; P < 0.24. Female and males showed CC of -0.29, P < 0.01 and -0.10, P = 0.09. Using the threshold for AAGSM and HbA1c as: low-risk (AAGSM > 100; HbA1c < 5.7%), moderate-risk (40 < AAGSM < 100; 5.7% < HbA1c < 6.5%) and high-risk (AAGSM < 40; HbA1c > 6.5%), the area under the curve showed a better performance of AAGSM over GSM_conv. A paired t-test between operators and expert (P < 0.0001); inter-operator CC of 0.85 (P < 0.0001).

CONCLUSIONS

Echolucent plaque in patients with diabetes can be more accurately characterized for risk stratification using AAGSM compared to GSM_conv.

Morphologic TPA (mTPA) and composite risk score for moderate carotid atherosclerotic plaque is strongly associated with HbA1c in diabetes cohort

BACKGROUND

This study examines the association between six types of carotid artery disease image-based phenotypes and HbA1c in diabetes patients. Six phenotypes (intima-media thickness measurements (cIMT (ave.), cIMT (max.), cIMT (min.)), bidirectional wall variability (cIMTV), morphology-based total plaque area (mTPA), and composite risk score (CRS)) were measured in an automated setting using AtheroEdge™ (AtheroPoint, CA, USA).

METHOD

Consecutive 199 patients (157 M, age: 68.96 ± 10.98 years), L/R common carotid artery (CCA; 398 US scans) who underwent a carotid ultrasound (L/R) were retrospectively analyzed using AtheroEdge™ system. Two operators (novice and experienced) manually calibrated all the US scans using AtheroEdge™. Logistic regression (LR) and Odds ratio (OR) was computed and phenotypes were ranked.

RESULTS

The baseline results showed 150 low-risk patients (HbA1c < 6.50 mg/dl) and 49 high-risk patients (HbA1c ≥ 6.50 mg/dl). The fasting blood sugar (FBS) was highly associated with HbA1c (P < 0.001). Except for cIMTV, all phenotypes showed an OR > 1.0 (P < 0.001) for left common carotid artery (LCCA), right carotid artery (RCCA), and mean of left and right common carotid artery (MCCA). After adjusting the FBS, the OR for mTPA showed a higher risk for LCCA, RCCA, and MCCA. The coefficient of correlation (CC) between phenotypes and HbA1c were strong and inter-CC between cIMT and mTPA/CRS was above 0.9 (P < 0.001). The statistical tests showed that phenotypes were significantly associated with diabetes (P-value<0.0001).

CONCLUSIONS

All phenotypes using AtheroEdge™, except cIMTV, showed a strong association with HbA1c. mTPA and CRS were equally strong phenotypes as cIMT. The CRS phenotype showed the strongest relationship to HbA1c.

A Survey on Coronary Atherosclerotic Plaque Tissue Characterization in Intravascular Optical Coherence Tomography

PURPOSE OF REVIEW

Atherosclerotic plaque deposition within the coronary vessel wall leads to arterial stenosis and severe catastrophic events over time. Identification of these atherosclerotic plaque components is essential to pre-estimate the risk of cardiovascular disease (CVD) and stratify them as a high or low risk. The characterization and quantification of coronary plaque components are not only vital but also a challenging task which can be possible using high-resolution imaging techniques.

RECENT FINDING

Atherosclerotic plaque components such as thin cap fibroatheroma (TCFA), fibrous cap, macrophage infiltration, large necrotic core, and thrombus are the microstructural plaque components that can be detected with only high-resolution imaging modalities such as intravascular ultrasound (IVUS) and optical coherence tomography (OCT). Light-based OCT provides better visualization of plaque tissue layers of coronary vessel walls as compared to IVUS. Three dominant paradigms have been identified to characterize atherosclerotic plaque components based on optical attenuation coefficients, machine learning algorithms, and deep learning techniques. This review (condensation of 126 papers after downloading 150 articles) presents a detailed comparison among various methodologies utilized for plaque tissue characterization, classification, and arterial measurements in OCT. Furthermore, this review presents the different ways to predict and stratify the risk associated with the CVD based on plaque characterization and measurements in OCT. Moreover, this review discovers three different paradigms for plaque characterization and their pros and cons. Among all of the techniques, a combination of machine learning and deep learning techniques is a best possible solution that provides improved OCT-based risk stratification.

Ultrasound-Based Automated Carotid Lumen Diameter/Stenosis Measurement and its Validation System

Objective

Degree of carotid stenosis is an important predictor to assess risk of stroke. Systolic velocity-based methods for lumen diameter and stenosis measurement are subjective. Image-based methods face a challenge because of low gradients in media and intima walls.

Methods

This article presents AtheroEdge™ 2.0, a two-stage process for automated carotid lumen diameter measurement that combats the above challenges. Stage one uses spectral analysis based on the hypothesis that far-wall adventitia is brightest. Stage two uses lumen pixel region identification based on the assumption that blood flow has constant density. Using global and local processing, lumen boundaries are detected. This clinical system outputs lumen diameter along with stenosis severity index (SSI).

Results

Our database consists of institutional review board–approved 202 patients (males/females: 155/47) left and right common carotid artery images (404 images, Toshiba scanner). Two trained neuro radiologists performed manual lumen border tracings using ImgTracer™ software. The coefficient of correlation between automated and two manual readings was 0.91 and 0.92. Dice similarity and Jaccard index were 95.82%, 95.72% and 92.10%, 91.92%, respectively. The mean diameter error between automated and two manual readings was 0.27 ± 0.26 and 0.26 ± 0.28 mm, respectively. Precision of merit was 98.05% and 99.03% with respect to two readings. SSI showed 97% accuracy.

Conclusions

The image-based automated carotid lumen diameter and stenosis measurement system is fast, accurate, and reliable.

Long-term outcomes after re-entry device use for recanalization of common iliac artery chronic total occlusions

OBJECTIVE

To examine the impact of re-entry device (RED) use on 1- and 5-year outcomes after endovascular treatment of common iliac artery (CIA) chronic total Occlusions (CTOs).

BACKGROUND

There are not enough data regarding the long-term safety and efficacy of RED.

METHODS

We performed a two-center retrospective study of 115 patients (140 lesions) undergoing CIA CTO endovascular intervention between 2006 and 2016. Baseline characteristics and long-term outcomes were described. A Cox proportional hazard model was developed to determine if REDs were associated with target lesion revascularization (TLR) or major adverse limb events (MALE) after 1 and 5 years.

RESULTS

Among 140 lesions, 43 (31%) required use of a RED. The mean age was 63.9 years and the majority (n = 80) of patients were male. An antegrade crossing approach and treatment of restenotic lesions were less common in the RED group (10% vs. 29%, P < .05 and 0% vs. 21%, P < .05, respectively). There were no significant differences in Rutherford class, pre-procedure ABI, or patient presentation. The procedural complication rates were similar between the two groups. The 1- and 5-year TLR rates for lesions treated with re-entry device vs. standard approaches were 11% vs. 9%; P = 0.8 and 29% vs. 29%; P = 0.9 respectively. The 1 and 5-year MALE rates for lesions treated with re-entry device were 5% vs. 6%; P = 0.8 and 11% vs. 11%; P = 0.9 respectively.

CONCLUSIONS

This retrospective analysis found that recanalization of CIA occlusions using a RED is safe and is associated with long-term clinical outcomes similar to that of standard crossing techniques.

Aspirin and clopidogrel high on-treatment platelet reactivity and genetic predictors in peripheral arterial disease

OBJECTIVES

Our aims were to examine the prevalence and genetic predictors of aspirin and clopidogrel high on-treatment platelet reactivity (HoTPR), and associated adverse cardiovascular outcomes in patients with peripheral arterial disease (PAD).

BACKGROUND

The association of aspirin and clopidogrel HoTPR with outcomes in PAD remains unclear.

METHODS

This is a prospective cohort study of patients with angiographically documented PAD involving carotid and lower extremity arteries. Aspirin and clopidogrel HoTPR (using the VerifyNow Assay) and associated genetic predictors were compared to clinical outcomes. The primary end-point was a composite of major adverse cardiovascular events: all-cause mortality, myocardial infarction, stroke, target vessel revascularization (TVR) and limb-loss in patients who underwent extremity intervention.

RESULTS

The study was stopped prematurely due to slow patient enrolment. Of 195 patients enrolled, the primary analysis was performed in 154 patients taking both drugs. Aspirin HoTPR was present in 31 (20%) and clopidogrel HoTPR in 76 (49%) patients. There was a trend toward more primary composite outcome events with PRU ≥ 235 (52% freedom-from-event rate vs. 70% for PRU < 235; P = 0.09). TVR was higher in those with PRU ≥ 235 (20 vs. 6%, unadjusted P = 0.02). There was no association between aspirin HoTPR and combined outcomes. Single nucleotide polymorphisms in serum paraoxonase/arylesterase 1 (PON1) gene was associated with aspirin HoTPR (P = 0.005) while SNP in phospholipase A2, group III (PLA2G3) gene was associated with clopidogrel HoTPR (P = 0.002).

CONCLUSION

Clopidogrel HoTPR was significantly associated with TVR, while aspirin HoTPR was not associated with adverse clinical outcomes in patients with PAD.

Intra- and inter-operator reproducibility of automated cloud-based carotid lumen diameter ultrasound measurement

BACKGROUND

Common carotid artery lumen diameter (LD) ultrasound measurement systems are either manual or semi-automated and lack reproducibility and variability studies. This pilot study presents an automated and cloud-based LD measurements software system (AtheroCloud) and evaluates its: (i) intra/inter-operator reproducibility and (ii) intra/inter-observer variability.

METHODS

100 patients (83M, mean age: 68±11years), IRB approved, consisted of L/R CCA artery (200 ultrasound images), acquired using a 7.5-MHz linear transducer. The intra/inter-operator reproducibility was verified using three operator's readings. Near-wall and far carotid wall borders were manually traced by two observers for intra/inter-observer variability analysis.

RESULTS

The mean coefficient of correlation (CC) for intra- and inter-operator reproducibility between all the three automated reading pairs were: 0.99 (P<0.0001) and 0.97 (P<0.0001), respectively. The mean CC for intra- and inter-observer variability between both the manual reading pairs were 0.98 (P<0.0001) and 0.98 (P<0.0001), respectively. The Figure-of-Merit between the mean of the three automated readings against the four manuals were 98.32%, 99.50%, 98.94% and 98.49%, respectively.

CONCLUSIONS

The AtheroCloud LD measurement system showed high intra/inter-operator reproducibility hence can be adapted for vascular screening mode or pharmaceutical clinical trial mode.

Novel Nitinol Stent for Lesions up to 24 cm in the Superficial Femoral and Proximal Popliteal Arteries: 24-Month Results From the TIGRIS Randomized Trial

PURPOSE

To evaluate the safety and effectiveness of the TIGRIS stent for lesions up to 24 cm in the superficial femoral and proximal popliteal arteries (SFA/PPA).

METHODS

This prospective, multicenter, randomized study enrolled 274 subjects at 36 sites in the United States and Europe. Subjects were randomly assigned in a 3:1 ratio to treatment with the TIGRIS stent (n=197; mean age 66.7±9.28 years; 141 men) or LifeStent (n=70; mean age 67.9±8.87 years; 49 men). The primary safety endpoint was 30-day freedom from major adverse events (MAE). The primary efficacy endpoint was primary patency at 12 months. Secondary endpoints included target lesion revascularization (TLR) and stent fracture. Clinical success and quality of life were also assessed.

RESULTS

Mean lesion length (107.6 vs 117.9 mm, p=0.29), procedure success (99.5% vs 97.1%, p=0.17), and freedom from MAE (99.5% vs 100%, p>0.99) were similar for the TIGRIS and control groups, respectively. Likewise, there was no difference in primary patency at 12 months (60.6% vs 63.2%, p=0.73) or 24 months (56.3% vs 50.2%, p=0.60) or in TLR at the same time points (76.6% vs 80.6%, p=0.49; 70.5% vs 67.2%, p=0.85). There were no differences in the changes in Rutherford category or the ankle/brachial index through 24 months. The rate of stent fracture was lower for TIGRIS compared with LifeStent (0% vs 32.7%, p<0.001).

CONCLUSION

The TIGRIS stent and LifeStent were similarly effective for the treatment of lesions in the SFA and PPA. The high flexibility and zero fracture rate associated with the TIGRIS stent make this device favorable for use in high-flexion arteries.

Laser Atherectomy Combined With Drug-Coated Balloon Angioplasty Is Associated With Improved 1-Year Outcomes for Treatment of Femoropopliteal In-Stent Restenosis

Purpose: To examine whether laser atherectomy combined with drug-coated balloons (laser + DCB) can improve the outcomes of femoropopliteal (FP) in-stent restenosis (ISR). Methods: A dual-center retrospective study was conducted of 112 consecutive patients (mean age 70.3±10.6 years; 86 men) with Tosaka class II (n=29; diffuse stenosis) or III (n=83; occlusion) FP-ISR lesions. Sixty-two patients (mean age 68.5±10 years; 51 men) underwent laser + DCB while the other 50 patients (mean age 72.5±10.8 years; 35 men) had laser atherectomy plus balloon angioplasty (laser + BA). Critical limb ischemia was the indication in 33% of the interventions. The average lesion length was 247 mm. A Cox regression hazard model was developed to examine the association between laser + DCB vs laser + BA; the results are presented as the hazard ratio (HR) and 95% confidence interval (CI). One-year target lesion revascularization (TLR) and reocclusion were estimated using the Kaplan-Meier method. Results: Overall procedure success was 98% and was similar between groups. Bailout stenting was less often required in the laser + DCB group (31.7% vs 58%, p=0.006). The combination of laser + DCB was associated with improved 12-month estimates for freedom from TLR (72.5% vs 50.5%, p=0.043) and freedom from reocclusion (86.7% vs 56.9%, p=0.003). Among patients with Tosaka III FP-ISR, combination therapy with laser + DCB was also associated with increased freedom from reocclusion (87.1% vs 57.1%, p=0. 028). On multivariable analysis, treatment with laser + DCB was associated with a significantly reduced risk of reocclusion (HR 0.08, 95% CI 0.17 to 0.38; p=0.002). Conclusion: When used for treatment of complex FP-ISR lesions, DCB angioplasty combined with laser atherectomy is associated with significantly reduced 1-year TLR and reocclusion rates.

Wall-based measurement features provides an improved IVUS coronary artery risk assessment when fused with plaque texture-based features during machine learning paradigm

BACKGROUND

Planning of percutaneous interventional procedures involves a pre-screening and risk stratification of the coronary artery disease. Current screening tools use stand-alone plaque texture-based features and therefore lack the ability to stratify the risk.

METHOD

This IRB approved study presents a novel strategy for coronary artery disease risk stratification using an amalgamation of IVUS plaque texture-based and wall-based measurement features. Due to common genetic plaque makeup, carotid plaque burden was chosen as a gold standard for risk labels during training-phase of machine learning (ML) paradigm. Cross-validation protocol was adopted to compute the accuracy of the ML framework. A set of 59 plaque texture-based features was padded with six wall-based measurement features to show the improvement in stratification accuracy. The ML system was executed using principle component analysis-based framework for dimensionality reduction and uses support vector machine classifier for training and testing-phases.

RESULTS

The ML system produced a stratification accuracy of 91.28%, demonstrating an improvement of 5.69% when wall-based measurement features were combined with plaque texture-based features. The fused system showed an improvement in mean sensitivity, specificity, positive predictive value, and area under the curve by: 6.39%, 4.59%, 3.31% and 5.48%, respectively when compared to the stand-alone system. While meeting the stability criteria of 5%, the ML system also showed a high average feature retaining power and mean reliability of 89.32% and 98.24%, respectively.

CONCLUSIONS

The ML system showed an improvement in risk stratification accuracy when the wall-based measurement features were fused with the plaque texture-based features.

Web-based accurate measurements of carotid lumen diameter and stenosis severity: An ultrasound-based clinical tool for stroke risk assessment during multicenter clinical trials

BACKGROUND

This pilot study presents a completely automated, novel, smart, cloud-based, point-of-care system for (a) carotid lumen diameter (LD); (b) stenosis severity index (SSI) and (c) total lumen area (TLA) measurement using B-mode ultrasound. The proposed system was (i) validated against manual reading taken by the Neurologist and (ii) benchmarked against the commercially available system.

METHOD

One hundred patients (73 M/27 F, mean age: 68 ± 11 years), institutional review board approved, written informed consent, consisted of left/right common carotid artery (200 ultrasound scans) were acquired using a 7.5-MHz linear transducer.

RESULTS

The measured mean LD for left and right carotids were (in mm): (i) for proposed system (6.49 ± 1.77, 6.66 ± 1.70); and (ii) for manual (6.29 ± 1.79, 6.45 ± 1.63), respectively and coefficient of correlation between cloud-based automated against manual were 0.98 (P < 0.0001) and 0.99 (P < 0.0001), respectively. The corresponding TLA error, Precision-of-Merit, and Figure-of-Merit when measured against the manual were: 4.56 ± 3.54%, 96.18 ± 3.21%, and 96.85%, respectively. The AUC for the receiving operating characteristics for the cloud-based system was: 1.0. Four statistical tests such as: Two-tailed z-test, Mann-Whitney test, Kolmogorov-Smirnov (KS) and one-way ANOVA were performed to demonstrate consistency and reliability.

CONCLUSIONS

The proposed system is reliable, accurate, fast, completely automated, anytime-anywhere solution for multi-center clinical trials and routine vascular screening.

A Review on Atherosclerotic Biology, Wall Stiffness, Physics of Elasticity, and Its Ultrasound-Based Measurement

Functional and structural changes in the common carotid artery are biomarkers for cardiovascular risk. Current methods for measuring functional changes include pulse wave velocity, compliance, distensibility, strain, stress, stiffness, and elasticity derived from arterial waveforms. The review is focused on the ultrasound-based carotid artery elasticity and stiffness measurements covering the physics of elasticity and linking it to biological evolution of arterial stiffness. The paper also presents evolution of plaque with a focus on the pathophysiologic cascade leading to arterial hardening. Using the concept of strain, and image-based elasticity, the paper then reviews the lumen diameter and carotid intima-media thickness measurements in combined temporal and spatial domains. Finally, the review presents the factors which influence the understanding of atherosclerotic disease formation and cardiovascular risk including arterial stiffness, tissue morphological characteristics, and image-based elasticity measurement.

High-Intensity Statin Therapy Is Associated With Improved Survival in Patients With Peripheral Artery Disease

Background

The relative benefit of higher statin dosing in patients with peripheral artery disease has not been reported previously. We compared the effectiveness of low‐ or moderate‐intensity (LMI) versus high‐intensity (HI) statin dose on clinical outcomes in patients with peripheral artery disease.

Methods and Results

We reviewed patients with symptomatic peripheral artery disease who underwent peripheral angiography and/or endovascular intervention from 2006 to 2013 who were not taking other lipid‐lowering medications. HI statin use was defined as atorvastatin 40–80 mg or rosuvastatin 20–40 mg. Baseline demographics, procedural data, and outcomes were retrospectively analyzed. Among 909 patients, 629 (69%) were prescribed statins, and 124 (13.6%) were treated with HI statin therapy. Mean low‐density lipoprotein level was similar in patients on LMI versus HI (80±30 versus 87±44 mg/dL, P=0.14). Demographics including age (68±12 versus 67±10 years, P=0.25), smoking history (76% versus 80%, P=0.42), diabetes mellitus (54% versus 48%, P=0.17), and hypertension (88% versus 89%, P=0.78) were similar between groups (LMI versus HI). There was a higher prevalence of coronary artery disease (56% versus 75%, P=0.0001) among patients on HI statin (versus LMI). After propensity weighting, HI statin therapy was associated with improved survival (hazard ratio for mortality: 0.52; 95% confidence interval, 0.33–0.81; P=0.004) and decreased major adverse cardiovascular events (hazard ratio: 0.58; 95% confidence interval 0.37–0.92, P=0.02).

Conclusions

In patients with peripheral artery disease who were referred for peripheral angiography or endovascular intervention, HI statin therapy was associated with improved survival and fewer major adverse cardiovascular events compared with LMI statin therapy.

Long-term outcomes in patients with critical limb ischemia and heart failure with preserved or reduced ejection fraction

The impact of heart failure (HF) on long-term survival in patients with critical limb ischemia (CLI) has not been well described. Outcomes stratified by left ventricular ejection fraction (EF) are also unknown. A single center retrospective chart review was performed for patients who underwent treatment for CLI from 2006 to 2013. Baseline demographics, procedural data and outcomes were analyzed. HF diagnosis was based on appropriate signs and symptoms as well as results of non-invasive testing. Among 381 CLI patients, 120 (31%) had a history of HF and 261 (69%) had no history of heart failure (no-HF). Within the HF group, 74 (62%) had HF with preserved ejection fraction (HFpEF) and 46 (38%) had HF with reduced ejection fraction (HFrEF). The average EF for those with no-HF, HFpEF and HFrEF were 59±13% vs 56±9% vs 30±9%, respectively. The likelihood of having concomitant coronary artery disease (CAD) was lowest in the no-HF group (43%), higher in the HFpEF group (70%) and highest in the HFrEF group (83%) ( p=0.001). Five-year survival was on average twofold higher in the no-HF group (43%) compared to both the HFpEF (19%, p=0.001) and HFrEF groups (24%, p=0.001). Long-term survival rates did not differ between the two HF groups ( p=0.50). There was no difference in 5-year freedom from major amputation or freedom from major adverse limb events between the no-HF, HFpEF and HFrEF groups, respectively. Overall, the combination of CLI and HF is associated with poor 5-year survival, independent of the degree of left ventricular systolic dysfunction.

Relationship between Automated Coronary Calcium Volumes and a Set of Manual Coronary Lumen Volume, Vessel Volume and Atheroma Volume in Japanese Diabetic Cohort

INTRODUCTION

A high degree of correlation exists between Coronary Artery Diseases (CAD) and calcification of the vessel wall. For Percutaneous Coronary Interventional (PCI) planning, it is essential to have an exact understanding of the extent to which calcium volume is correlated to the lumen, vessel, and atheroma volume regions in the coronary artery, which is unclear in recent studies.

AIM

Four automated Coronary Calcium Volume (aCCV) measurement methods {threshold, Fuzzy c-Means (FCM), K-means, and Hidden Markov Random Field (HMRF)} and its correlation with three manual (experts) coronary parameters namely: Coronary Vessel Volume (mCVV), Coronary Lumen Volume (mCLV), and Coronary Atheroma Volume (mCAV), was determined in a Japanese diabetic cohort.

MATERIALS AND METHODS

Intravascular Ultrasound (IVUS) image dataset from 19 patients (around 40,090 frames) was collected using 40 MHz IVUS catheter (Atlantis^® SR Pro, Boston Scientific^®, pullback speed of 0.5 mm/sec). The methodology consisted of automatically computing the calcium volume in the entire IVUS coronary videos using FCM, K-means, and HMRF based pixel classification and comparing it against the previously published threshold-based method. The Coefficient of Correlation (CC) was then established between the four aCCV and three manually (experts) coronary parameters: mCVV, mCLV, and mCAV computed using iMAP software Boston Scientific^®. Statistical tests (Two-tailed paired Student t-test, Wilcoxon signed rank test, Mann-Whitney test, Chi-square test, and Kolmogorov-Smirnov KS-test) were performed to demonstrate consistency, reliability, and accuracy of the proposed work.

RESULTS

Correlation coefficient of: (a) automated threshold-based volume; (b) automated FCM based volume; (c) automated K-means based volume; and (d) automated HMRF based volume and corresponding three manually (expert's) coronary parameters (mCLV, mCVV, mCAV) were: (0.51, 0.40, 0.48), (0.52, 0.38, 0.49), (0.56, 0.45, 0.52), and (0.57, 0.42, 0.56), respectively. The CC between age and haemoglobin was 0.50.

CONCLUSION

Automated coronary volume measurement using HMRF method is more accurate compared to threshold, FCM, and K-means-based method, since it is more strongly correlated with three expert's readings.

Extracranial internal carotid artery calcium volume measurement using computer tomography

BACKGROUND

The extent of calcium volume in the carotid arteries of contrast-based computer tomography (CT) is a valuable indicator of stroke risk. This study presents an automated, simple and fast calcium volume computation system. Since the high contrast agent can sometimes obscure the presence of calcium in the CT slices, it is therefore necessary to identify these slices before the corrected volume can be estimated.

METHODS

The system typically consists of segmenting the calcium region from the CT scan into slices based on Hounsfield Unit-based threshold, and subsequently computing the summation of the calcium areas in each slice. However, when the carotid volume has intermittently higher concentration of contrast agent, a dependable approach is adapted to correct the calcium region using the neighboring slices, thereby estimating the correct volume. Furthermore, mitigation is provided following the regulatory constraints by changing the system to semi-automated criteria as a fall back solution. We evaluate the automated and semi-automated techniques using completely manual calcium volumes computed based on the manual tracings by the neuroradiologist.

RESULTS

A total of 64 patients with calcified plaque in the internal carotid artery were analyzed. Using the above algorithm, our automated and semi-automated system yields correlation coefficients (CC) of 0.89 and 0.96 against first manual readings and 0.90 and 0.96 against second manual readings, respectively. Using the t-test, there was no significant difference between the automated and semi-automated methods against manual. The intra-observer reliability was excellent with CC 0.98.

CONCLUSIONS

Compared to automated method, the semi-automated method for calcium volume is acceptable and closer to manual strategy for calcium volume. Further work evaluating and confirming the performance of our semi-automated protocol is now warranted.

Plaque Tissue Morphology-Based Stroke Risk Stratification Using Carotid Ultrasound: A Polling-Based PCA Learning Paradigm

Severe atherosclerosis disease in carotid arteries causes stenosis which in turn leads to stroke. Machine learning systems have been previously developed for plaque wall risk assessment using morphology-based characterization. The fundamental assumption in such systems is the extraction of the grayscale features of the plaque region. Even though these systems have the ability to perform risk stratification, they lack the ability to achieve higher performance due their inability to select and retain dominant features. This paper introduces a polling-based principal component analysis (PCA) strategy embedded in the machine learning framework to select and retain dominant features, resulting in superior performance. This leads to more stability and reliability. The automated system uses offline image data along with the ground truth labels to generate the parameters, which are then used to transform the online grayscale features to predict the risk of stroke. A set of sixteen grayscale plaque features is computed. Utilizing the cross-validation protocol (K = 10), and the PCA cutoff of 0.995, the machine learning system is able to achieve an accuracy of 98.55 and 98.83%corresponding to the carotidfar wall and near wall plaques, respectively. The corresponding reliability of the system was 94.56 and 95.63%, respectively. The automated system was validated against the manual risk assessment system and the precision of merit for same cross-validation settings and PCA cutoffs are 98.28 and 93.92%for the far and the near wall, respectively.PCA-embedded morphology-based plaque characterization shows a powerful strategy for risk assessment and can be adapted in clinical settings.

Midterm Outcomes After Infrapopliteal Interventions in Patients With Critical Limb Ischemia Based on the TASC II Classification of Below-the-Knee Arteries

Purpose: To analyze the relationship between the new TransAtlantic Inter-Society Consensus (TASC II) infrapopliteal classification and limb outcomes among patients with critical limb ischemia (CLI). Methods: A single-center retrospective study was performed on 166 consecutive CLI patients (mean age 71 years; 113 men) undergoing endovascular treatment of 244 infrapopliteal lesions from 2006 to 2013. Patient, procedural, angiographic, and limb outcomes were compared for the new TASC A/B vs C/D classification for infrapopliteal lesions. Binary restenosis was determined by a peak systolic velocity ratio >2.0 by duplex ultrasound on follow-up at 1, 3, 6, and 12 months. Results: Seventy-two (43.4%) patients had TASC A/B lesions, while 94 (56.6%) had TASC C/D patterns of infrapopliteal disease. Baseline demographics and tissue loss (93% vs 94%, p=0.59) were similar between the groups. TASC A/B lesions were shorter (53±35 vs 170±83 mm, p<0.001), less severely stenosed (77%±24% vs 93%±14%, p<0.001), had a larger target vessel diameter (2.9±0.5 vs 2.6±0.5 mm, p<0.001), and were less frequently chronic total occlusions (24% vs 64%, p<0.001) compared with the TASC C/D group. Three-year freedom from both amputation (85% vs 67%, p=0.02) and major adverse limb events (79% vs 61%, p=0.02) were significantly higher in the TASC A/B group. Technical success rates (95% vs 80%, p<0.001) and 1-year primary patency (58% vs 51%, p=0.04) were higher in the A/B group. Overall 3-year survival was similar between the groups (96% A/B vs 88% C/D, p=0.2). Conclusion: TASC C/D infrapopliteal lesions are associated with higher amputation and major adverse limb events rates and lower primary patency compared with TASC A/B infrapopliteal lesions. Further studies are needed to assess the association between TASC C/D infrapopliteal lesions and clinical outcomes in patients with CLI.

Automated segmental-IMT measurement in thin/thick plaque with bulb presence in carotid ultrasound from multiple scanners: Stroke risk assessment

BACKGROUND AND OBJECTIVES

Standardization of the carotid IMT requires a reference marker in ultrasound scans. It has been shown previously that manual reference marker and manually created carotid segments are used for measuring IMT in these segments. Manual methods are tedious, time consuming, subjective, and prone to errors. Bulb edge can be considered as a reference marker for measurements of the cIMT. However, bulb edge can be difficult to locate in ultrasound scans due to: (a) low signal to noise ratio in the bulb region as compared to common carotid artery region; (b) uncertainty of bulb location in craniocaudal direction; and (c) variability in carotid bulb shape and size. This paper presents an automated system (a class of AtheroEdge™ system from AtheroPoint™, Roseville, CA, USA) for locating the bulb edge as a reference marker and further develop segmental-IMT (sIMT) which measures IMT in 10mm segments (namely: s1, s2 and s3) proximal to the bulb edge.

METHODS

The patented methodology uses an integrated approach which combines carotid geometry and pixel-classification paradigms. The system first finds the bulb edge and then measures the sIMT proximal to the bulb edge. The system also estimates IMT in bulb region (bIMT). The 649 image database consists of varying plaque (light, moderate to heavy), image resolutions, shapes, sizes and ethnicity.

RESULTS

Our results show that the IMT contributions in different carotid segments are as follows: bulb-IMT 34%, s1-IMT 29.46%, s2-IMT 11.48%, and s3-IMT 12.75%, respectively. We compare our automated results against reader's tracings demonstrating the following performance: mean lumen-intima error: 0.01235 ± 0.01224mm, mean media-adventitia error: 0.020933 ± 0.01539mm and mean IMT error: 0.01063 ± 0.0031mm. Our system's Precision of Merit is: 98.23%, coefficient of correlation between automated and Reader's IMT is: 0.998 (p-value < 0.0001). These numbers are improved compared to previous publications by Suri's group which is automated multi-resolution conventional cIMT.

CONCLUSIONS

Our fully automated bulb detection system reports 92.67% precision against ideal bulb edge locations as marked by the reader in the bulb transition zone.

Non-compressible ABIs are associated with an increased risk of major amputation and major adverse cardiovascular events in patients with critical limb ischemia

Ankle-brachial indices (ABIs) are important for the assessment of disease burden among patients with peripheral artery disease. Although low values have been associated with adverse clinical outcomes, the association between non-compressible ABI (ncABI) and clinical outcome has not been evaluated among patients with critical limb ischemia (CLI). The present study sought to compare the clinical characteristics, angiographic findings and clinical outcomes of those with compressible (cABI) and ncABI among patients with CLI. Consecutive patients undergoing endovascular evaluation for CLI between 2006 and 2013 were included in a single center cohort. Major adverse cardiovascular events (MACE) were then compared between the two groups. Among 284 patients with CLI, 68 (24%) had ncABIs. These patients were more likely to have coronary artery disease ( p=0.003), diabetes ( p<0.001), end-stage renal disease ( p<0.001) and tissue loss ( p=0.01) when compared to patients with cABI. Rates of infrapopliteal disease were similar between the two groups ( p=0.10), though patients with ncABI had lower rates of iliac ( p=0.004) or femoropopliteal stenosis ( p=0.003). Infrapopliteal vessels had smaller diameters ( p=0.01) with longer lesions ( p=0.05) among patients with ncABIs. After 3 years of follow-up, ncABIs were associated with increased rates of mortality (HR 1.75, 95% CI: 1.12-2.78), MACE (HR 2.04, 95% CI: 1.35-3.03) and major amputation (HR 1.96, 95% CI: 1.11-3.45) when compared to patients with cABIs. In conclusion, ncABIs are associated with higher rates of mortality and adverse events among those undergoing endovascular therapy for CLI.

Stroke Risk Stratification and its Validation using Ultrasonic Echolucent Carotid Wall Plaque Morphology: A Machine Learning Paradigm

Stroke risk stratification based on grayscale morphology of the ultrasound carotid wall has recently been shown to have a promise in classification of high risk versus low risk plaque or symptomatic versus asymptomatic plaques. In previous studies, this stratification has been mainly based on analysis of the far wall of the carotid artery. Due to the multifocal nature of atherosclerotic disease, the plaque growth is not restricted to the far wall alone. This paper presents a new approach for stroke risk assessment by integrating assessment of both the near and far walls of the carotid artery using grayscale morphology of the plaque. Further, this paper presents a scientific validation system for stroke risk assessment. Both these innovations have never been presented before. The methodology consists of an automated segmentation system of the near wall and far wall regions in grayscale carotid B-mode ultrasound scans. Sixteen grayscale texture features are computed, and fed into the machine learning system. The training system utilizes the lumen diameter to create ground truth labels for the stratification of stroke risk. The cross-validation procedure is adapted in order to obtain the machine learning testing classification accuracy through the use of three sets of partition protocols: (5, 10, and Jack Knife). The mean classification accuracy over all the sets of partition protocols for the automated system in the far and near walls is 95.08% and 93.47%, respectively. The corresponding accuracies for the manual system are 94.06% and 92.02%, respectively. The precision of merit of the automated machine learning system when compared against manual risk assessment system are 98.05% and 97.53% for the far and near walls, respectively. The ROC of the risk assessment system for the far and near walls is close to 1.0 demonstrating high accuracy.

Five multiresolution-based calcium volume measurement techniques from coronary IVUS videos: A comparative approach

BACKGROUND AND OBJECTIVE

Fast intravascular ultrasound (IVUS) video processing is required for calcium volume computation during the planning phase of percutaneous coronary interventional (PCI) procedures. Nonlinear multiresolution techniques are generally applied to improve the processing time by down-sampling the video frames.

METHODS

This paper presents four different segmentation methods for calcium volume measurement, namely Threshold-based, Fuzzy c-Means (FCM), K-means, and Hidden Markov Random Field (HMRF) embedded with five different kinds of multiresolution techniques (bilinear, bicubic, wavelet, Lanczos, and Gaussian pyramid). This leads to 20 different kinds of combinations. IVUS image data sets consisting of 38,760 IVUS frames taken from 19 patients were collected using 40 MHz IVUS catheter (Atlantis® SR Pro, Boston Scientific®, pullback speed of 0.5 mm/sec.). The performance of these 20 systems is compared with and without multiresolution using the following metrics: (a) computational time; (b) calcium volume; (c) image quality degradation ratio; and (d) quality assessment ratio.

RESULTS

Among the four segmentation methods embedded with five kinds of multiresolution techniques, FCM segmentation combined with wavelet-based multiresolution gave the best performance. FCM and wavelet experienced the highest percentage mean improvement in computational time of 77.15% and 74.07%, respectively. Wavelet interpolation experiences the highest mean precision-of-merit (PoM) of 94.06 ± 3.64% and 81.34 ± 16.29% as compared to other multiresolution techniques for volume level and frame level respectively. Wavelet multiresolution technique also experiences the highest Jaccard Index and Dice Similarity of 0.7 and 0.8, respectively. Multiresolution is a nonlinear operation which introduces bias and thus degrades the image. The proposed system also provides a bias correction approach to enrich the system, giving a better mean calcium volume similarity for all the multiresolution-based segmentation methods. After including the bias correction, bicubic interpolation gives the largest increase in mean calcium volume similarity of 4.13% compared to the rest of the multiresolution techniques. The system is automated and can be adapted in clinical settings.

CONCLUSIONS

We demonstrated the time improvement in calcium volume computation without compromising the quality of IVUS image. Among the 20 different combinations of multiresolution with calcium volume segmentation methods, the FCM embedded with wavelet-based multiresolution gave the best performance.

Excimer Laser-Assisted Recanalization of Long, Chronic Superficial Femoral Artery Occlusions

Purpose:

To examine the safety and efficacy of excimer laser-assisted angioplasty (ELA) for recanalization of superficial femoral artery (SFA) occlusions.

Methods:

Data were analyzed from 318 consecutive patients (207 men; mean age 64.2 ± 10.7 years, range 33–91) who underwent ELA of 411 SFAs with chronic occlusions averaging 19.4 ± 6.0 cm in length. More than 75% of patients had severe claudication (category 3). Critical lower limb ischemia with rest pain or minor tissue loss was present in 6 and 15 patients, respectively. The mean ankle brachial index (ABI) before and after exercise was 0.62 ± 0.15 and 0.40 ± 0.18, respectively.

Results:

The initial attempt (crossover approach 89.7%, antegrade 6.6%, transpopliteal 3.6%) to cross the occlusion with an excimer laser catheter was successful in 342 (83.2%) of 411 limbs. A secondary attempt performed in 44 of 69 failed cases was successful in 30 limbs, increasing the technical success rate to 90.5% (372/411). Complications included acute reocclusion (4, 1.0%), perforation (9, 2.2%), and distal thrombosis/embolization (16, 3.9%). Postprocedurally, 219 (68.8%) patients were asymptomatic; mild (category 1) or moderate (category 2) claudication remained in 53 (16.6%) and 26 (8.2%) patients, respectively. The primary patency at 1 year was 33.6%. In the majority of patients, reocclusion was treatable on an outpatient basis. The 1-year assisted primary and secondary patency rates were 65.1% and 75.9%, respectively.

Conclusions:

Long SFA occlusions can be recanalized safely and successfully by ELA. However, to maintain patency and quality of life, intensive surveillance using objective testing followed by prompt repeat intervention are mandatory.

Limitations of Percutaneous Transluminal Angioplasty and Stenting for the Treatment of Disease of the Superficial Femoral and Popliteal Arteries

The long-term primary patency rates for percutaneous transluminal angioplasty (PTA) and stenting in treatment of disease of the superficial femoral and popliteal arteries have been disappointing. Three-year primary patency rates of ∼50% have been reported for PTA and first-generation stents. Early results with newer nitinol stents appear promising; however, long-term data are lacking. One- and 2-year primary patency rates of 76% to 97% and 60% to 84%, respectively, have been reported with nitinol stents. An emerging concern with nitinol stents is the frequency of stent fracture (≥25%) after interventions for long-segment disease. A recent study has shown that stent fractures are associated with in-stent restenosis and with significantly lower primary patency at 1 year.

The therapeutic success of PTA and stenting correlates with the complexity of the underlying disease. The best results are achieved when treating focal stenoses in patients with good distal runoff. Because endovascular interventions are preferred by patients, can be repeated, and preserve the option of bypass surgery, PTA and stenting are increasingly employed for diffuse and complex SFA disease. Clarifying the role of PTA and stenting in the treatment of complex SFA disease will require future studies that stratify results by both lesion anatomy and treatment indication.

Cryoplasty for the Treatment of Femoropopliteal Arterial Disease: Extended Follow-up Results

Purpose:

To report the findings from a multicenter study of patients treated with cryoplasty who were then followed for an average of >2 years post-treatment.

Methods:

Extended clinical follow-up was obtained for 70 patients (45 men; mean age 70.5±8.8 years) who originally received cryoplasty therapy to treat symptoms of intermittent claudication as part of a multicenter investigational device exemption (IDE) study. For all subjects, cryoplasty was used to treat stenoses or occlusions ≤10 cm in the femoropopliteal arteries. The original IDE study protocol enrolled 102 patients with a primary endpoint of target lesion patency at 9 months post-treatment. This collection of additional longer term follow-up data was initiated 2.5 years after the onset of study enrollment.

Results:

Extended clinical follow-up ranged from 11 to 41 months (mean 31). The clinical patency rate (freedom from target lesion revascularization) calculated by the Kaplan-Meier method was 83.2% after the original follow-up period of 300 days. After >3 years (1253 days), the clinical patency rate was well maintained at 75.0%.

Conclusions:

Long-term data indicate that cryoplasty is a durable therapy, with relatively low long-term restenosis rates compared to other endovascular treatment approaches.

Accurate cloud-based smart IMT measurement, its validation and stroke risk stratification in carotid ultrasound: A web-based point-of-care tool for multicenter clinical trial

This study presents AtheroCloud™ - a novel cloud-based smart carotid intima-media thickness (cIMT) measurement tool using B-mode ultrasound for stroke/cardiovascular risk assessment and its stratification. This is an anytime-anywhere clinical tool for routine screening and multi-center clinical trials. In this pilot study, the physician can upload ultrasound scans in one of the following formats (DICOM, JPEG, BMP, PNG, GIF or TIFF) directly into the proprietary cloud of AtheroPoint from the local server of the physician's office. They can then run the intelligent and automated AtheroCloud™ cIMT measurements in point-of-care settings in less than five seconds per image, while saving the vascular reports in the cloud. We statistically benchmark AtheroCloud™ cIMT readings against sonographer (a registered vascular technologist) readings and manual measurements derived from the tracings of the radiologist. One hundred patients (75 M/25 F, mean age: 68±11 years), IRB approved, Toho University, Japan, consisted of Left/Right common carotid artery (CCA) artery (200 ultrasound scans), (Toshiba, Tokyo, Japan) were collected using a 7.5MHz transducer. The measured cIMTs for L/R carotid were as follows (in mm): (i) AtheroCloud™ (0.87±0.20, 0.77±0.20); (ii) sonographer (0.97±0.26, 0.89±0.29) and (iii) manual (0.90±0.20, 0.79±0.20), respectively. The coefficient of correlation (CC) between sonographer and manual for L/R cIMT was 0.74 (P<0.0001) and 0.65 (P<0.0001), while, between AtheroCloud™ and manual was 0.96 (P<0.0001) and 0.97 (P<0.0001), respectively. We observed that 91.15% of the population in AtheroCloud™ had a mean cIMT error less than 0.11mm compared to sonographer's 68.31%. The area under curve for receiving operating characteristics was 0.99 for AtheroCloud™ against 0.81 for sonographer. Our Framingham Risk Score stratified the population into three bins as follows: 39% in low-risk, 70.66% in medium-risk and 10.66% in high-risk bins. Statistical tests were performed to demonstrate consistency, reliability and accuracy of the results. The proposed AtheroCloud™ system is completely reliable, automated, fast (3-5 seconds depending upon the image size having an internet speed of 180Mbps), accurate, and an intelligent, web-based clinical tool for multi-center clinical trials and routine telemedicine clinical care.

Numerical analysis of the effect of turbulence transition on the hemodynamic parameters in human coronary arteries

BACKGROUND

Local hemodynamics plays an important role in atherogenesis and the progression of coronary atherosclerosis disease (CAD). The primary biological effect due to blood turbulence is the change in wall shear stress (WSS) on the endothelial cell membrane, while the local oscillatory nature of the blood flow affects the physiological changes in the coronary artery. In coronary arteries, the blood flow Reynolds number ranges from few tens to several hundreds and hence it is generally assumed to be laminar while calculating the WSS calculations. However, the pulsatile blood flow through coronary arteries under stenotic condition could result in transition from laminar to turbulent flow condition.

METHODS

In the present work, the onset of turbulent transition during pulsatile flow through coronary arteries for varying degree of stenosis (i.e., 0%, 30%, 50% and 70%) is quantitatively analyzed by calculating the turbulent parameters distal to the stenosis. Also, the effect of turbulence transition on hemodynamic parameters such as WSS and oscillatory shear index (OSI) for varying degree of stenosis is quantified. The validated transitional shear stress transport (SST) k-ω model used in the present investigation is the best suited Reynolds averaged Navier-Stokes turbulence model to capture the turbulent transition. The arterial wall is assumed to be rigid and the dynamic curvature effect due to myocardial contraction on the blood flow has been neglected.

RESULTS

Our observations shows that for stenosis 50% and above, the WSSavg, WSSmax and OSI calculated using turbulence model deviates from laminar by more than 10% and the flow disturbances seems to significantly increase only after 70% stenosis. Our model shows reliability and completely validated.

CONCLUSIONS

Blood flow through stenosed coronary arteries seems to be turbulent in nature for area stenosis above 70% and the transition to turbulent flow begins from 50% stenosis.

PCA-based polling strategy in machine learning framework for coronary artery disease risk assessment in intravascular ultrasound: A link between carotid and coronary grayscale plaque morphology

BACKGROUND AND OBJECTIVE

Percutaneous coronary interventional procedures need advance planning prior to stenting or an endarterectomy. Cardiologists use intravascular ultrasound (IVUS) for screening, risk assessment and stratification of coronary artery disease (CAD). We hypothesize that plaque components are vulnerable to rupture due to plaque progression. Currently, there are no standard grayscale IVUS tools for risk assessment of plaque rupture. This paper presents a novel strategy for risk stratification based on plaque morphology embedded with principal component analysis (PCA) for plaque feature dimensionality reduction and dominant feature selection technique. The risk assessment utilizes 56 grayscale coronary features in a machine learning framework while linking information from carotid and coronary plaque burdens due to their common genetic makeup.

METHOD

This system consists of a machine learning paradigm which uses a support vector machine (SVM) combined with PCA for optimal and dominant coronary artery morphological feature extraction. Carotid artery proven intima-media thickness (cIMT) biomarker is adapted as a gold standard during the training phase of the machine learning system. For the performance evaluation, K-fold cross validation protocol is adapted with 20 trials per fold. For choosing the dominant features out of the 56 grayscale features, a polling strategy of PCA is adapted where the original value of the features is unaltered. Different protocols are designed for establishing the stability and reliability criteria of the coronary risk assessment system (cRAS).

RESULTS

Using the PCA-based machine learning paradigm and cross-validation protocol, a classification accuracy of 98.43% (AUC 0.98) with K=10 folds using an SVM radial basis function (RBF) kernel was achieved. A reliability index of 97.32% and machine learning stability criteria of 5% were met for the cRAS.

CONCLUSIONS

This is the first Computer aided design (CADx) system of its kind that is able to demonstrate the ability of coronary risk assessment and stratification while demonstrating a successful design of the machine learning system based on our assumptions.

Carotid inter-adventitial diameter is more strongly related to plaque score than lumen diameter: An automated tool for stroke analysis

PURPOSE

To compare the strength of correlation between automatically measured carotid lumen diameter (LD) and interadventitial diameter (IAD) with plaque score (PS).

METHODS

Retrospective study on a database of 404 common carotid artery B-mode sonographic images from 202 diabetic patients. LD and IAD were computed automatically using an advanced computerized edge detection method and compared with two distinct manual measurements. PS was computed by adding the maximal thickness in millimeters of plaques in segments taken from the internal carotid artery, bulb, and common carotid artery on both sides.

RESULTS

The coefficient of correlation was 0.19 (p < 0.007) between LD and PS, and 0.25 (p < 0.0006) between IAD and PS. After excluding 10 outliers, coefficient of correlation was 0.25 (p < 0.0001) between LD and PS, and 0.38 (p < 0.0001) between IAD and PS. The precision of merit of automated versus the two manual measurements was 96.6% and 97.2% for LD, and 97.7% and 98.1%, for IAD, respectively.

CONCLUSIONS

Our automated measurement system gave satisfying results in comparison with manual measurements. Carotid IAD was more strongly correlated to PS than carotid LD in this population sample of Japanese diabetic patients.