Computerized assessment of vessel morphological changes during treatment of glioblastoma multiforme: report of a case imaged serially by MRA over four years

Computational Fractal-Based Analysis of MR Susceptibility-Weighted Imaging (SWI) in Neuro-Oncology and Neurotraumatology

Susceptibility-weighted imaging (SWI) is a magnetic resonance imaging (MRI) technique able to depict the magnetic susceptibility produced by different substances, such as deoxyhemoglobin, calcium, and iron. The main application of SWI in clinical neuroimaging is detecting microbleedings and venous vasculature. Quantitative analyses of SWI have been developed over the last few years, aimed to offer new parameters, which could be used as neuroimaging biomarkers. Each technique has shown pros and cons, but no gold standard exists yet. The fractal dimension (FD) has been investigated as a novel potential objective parameter for monitoring intratumoral space-filling properties of SWI patterns. We showed that SWI patterns found in different tumors or different glioma grades can be represented by a gradient in the fractal dimension, thereby enabling each tumor to be assigned a specific SWI fingerprint. Such results were especially relevant in the differentiation of low-grade versus high-grade gliomas, as well as from high-grade gliomas versus lymphomas.Therefore, FD has been suggested as a potential image biomarker to analyze intrinsic neoplastic architecture in order to improve the differential diagnosis within clinical neuroimaging, determine appropriate therapy, and improve outcome in patients.These promising preliminary findings could be extended into the field of neurotraumatology, by means of the application of computational fractal-based analysis for the qualitative and quantitative imaging of microbleedings in traumatic brain injury patients. In consideration of some evidences showing that SWI signals are correlated with trauma clinical severity, FD might offer some objective prognostic biomarkers.In conclusion, fractal-based morphometrics of SWI could be further investigated to be used in a complementary way with other techniques, in order to form a holistic understanding of the temporal evolution of brain tumors and follow-up response to treatment, with several further applications in other fields, such as neurotraumatology and cerebrovascular neurosurgery as well.

Non-invasive transcranial volumetric ultrasound localization microscopy of the rat brain with continuous, high volume-rate acquisition

Rationale: Structure and function of the microvasculature provides critical information about disease state, can be used to identify local regions of pathology, and has been shown to be an indicator of response to therapy. Improved methods of assessing the microvasculature with non-invasive imaging modalities such as ultrasound will have an impact in biomedical theranostics. Ultrasound localization microscopy (ULM) is a new technology which allows processing of ultrasound data for visualization of microvasculature at a resolution better than allowed by acoustic diffraction with traditional ultrasound systems. Previous application of this modality in brain imaging has required the use of invasive procedures, such as a craniotomy, skull-thinning, or scalp removal, all of which are not feasible for the purpose of longitudinal studies. Methods: The impact of ultrasound localization microscopy is expanded using a 1024 channel matrix array ultrasonic transducer, four synchronized programmable ultrasound systems with customized high-performance hardware and software, and high-performance GPUs for processing. The potential of the imaging hardware and processing approaches are demonstrated in-vivo. Results: Our unique implementation allows asynchronous acquisition and data transfer for uninterrupted data collection at an ultra-high fixed frame rate. Using these methods, the vasculature was imaged using 100,000 volumes continuously at a volume acquisition rate of 500 volumes per second. With ULM, we achieved a resolution of 31 µm, which is a resolution improvement on conventional ultrasound imaging by nearly a factor of ten, in 3-D. This was accomplished while imaging through the intact skull with no scalp removal, which demonstrates the utility of this method for longitudinal studies. Conclusions: The results demonstrate new capabilities to rapidly image and analyze complex vascular networks in 3-D volume space for structural and functional imaging in disease assessment, targeted therapeutic delivery, monitoring response to therapy, and other theranostic applications.

Novel Radiomic Measurements of Tumor-Associated Vasculature Morphology on Clinical Imaging as a Biomarker of Treatment Response in Multiple Cancers

PURPOSE

The tumor-associated vasculature (TAV) differs from healthy blood vessels by its convolutedness, leakiness, and chaotic architecture, and these attributes facilitate the creation of a treatment-resistant tumor microenvironment. Measurable differences in these attributes might also help stratify patients by likely benefit of systemic therapy (e.g., chemotherapy). In this work, we present a new category of computational image-based biomarkers called quantitative tumor-associated vasculature (QuanTAV) features, and demonstrate their ability to predict response and survival across multiple cancer types, imaging modalities, and treatment regimens involving chemotherapy.

EXPERIMENTAL DESIGN

We isolated tumor vasculature and extracted mathematical measurements of twistedness and organization from routine pretreatment radiology (CT or contrast-enhanced MRI) of a total of 558 patients, who received one of four first-line chemotherapy-based therapeutic intervention strategies for breast (n = 371) or non-small cell lung cancer (NSCLC, n = 187).

RESULTS

Across four chemotherapy-based treatment strategies, classifiers of QuanTAV measurements significantly (P < 0.05) predicted response in held out testing cohorts alone (AUC = 0.63-0.71) and increased AUC by 0.06-0.12 when added to models of significant clinical variables alone. Similarly, we derived QuanTAV risk scores that were prognostic of recurrence-free survival in treatment cohorts who received surgery following chemotherapy for breast cancer [P = 0.0022; HR = 1.25; 95% confidence interval (CI), 1.08-1.44; concordance index (C-index) = 0.66] and chemoradiation for NSCLC (P = 0.039; HR = 1.28; 95% CI, 1.01-1.62; C-index = 0.66). From vessel-based risk scores, we further derived categorical QuanTAV high/low risk groups that were independently prognostic among all treatment groups, including patients with NSCLC who received chemotherapy only (P = 0.034; HR = 2.29; 95% CI, 1.07-4.94; C-index = 0.62). QuanTAV response and risk scores were independent of clinicopathologic risk factors and matched or exceeded models of clinical variables including posttreatment response.

CONCLUSIONS

Across these domains, we observed an association of vascular morphology on CT and MRI-as captured by metrics of vessel curvature, torsion, and organizational heterogeneity-and treatment outcome. Our findings suggest the potential of shape and structure of the TAV in developing prognostic and predictive biomarkers for multiple cancers and different treatment strategies.

Characterization of an Array-Based Dual-Frequency Transducer for Superharmonic Contrast Imaging

Superharmonic imaging with dual-frequency imaging systems uses conventional low-frequency ultrasound transducers on transmit, and high-frequency transducers on receive to detect higher order harmonic signals from microbubble contrast agents, enabling high-contrast imaging while suppressing clutter from background tissues. Current dual-frequency imaging systems for superharmonic imaging have been used for visualizing tumor microvasculature, with single-element transducers for each of the low- and high-frequency components. However, the useful field of view is limited by the fixed focus of single-element transducers, while image frame rates are limited by the mechanical translation of the transducers. In this article, we introduce an array-based dual-frequency transducer, with low-frequency and high-frequency arrays integrated within the probe head, to overcome the limitations of single-channel dual-frequency probes. The purpose of this study is to evaluate the line-by-line high-frequency imaging and superharmonic imaging capabilities of the array-based dual-frequency probe for acoustic angiography applications in vitro and in vivo. We report center frequencies of 1.86 MHz and 20.3 MHz with -6 dB bandwidths of 1.2 MHz (1.2-2.4 MHz) and 14.5 MHz (13.3-27.8 MHz) for the low- and high-frequency arrays, respectively. With the proposed beamforming schemes, excitation pressure was found to range from 336 to 458 kPa at its azimuthal foci. This was sufficient to induce nonlinear scattering from microbubble contrast agents. Specifically, in vitro contrast channel phantom imaging and in vivo xenograft mouse tumor imaging by this probe with superharmonic imaging showed contrast-to-tissue ratio improvements of 17.7 and 16.2 dB, respectively, compared to line-by-line micro-ultrasound B-mode imaging.

Vascular amounts and dispersion of caliber-classified vessels as key parameters to quantitate 3D micro-angioarchitectures in multiple myeloma experimental tumors

Blood vessel micro-angioarchitecture plays a pivotal role in tumor progression, metastatic dissemination and response to therapy. Thus, methods able to quantify microvascular trees and their anomalies may allow a better comprehension of the neovascularization process and evaluation of vascular-targeted therapies in cancer. To this aim, the development of a restricted set of indexes able to describe the arrangement of a microvascular tree is eagerly required. We addressed this goal through 3D analysis of the functional microvascular network in sulfo-biotin-stained human multiple myeloma KMS-11 xenografts in NOD/SCID mice. Using image analysis, we show that amounts, spatial dispersion and spatial relationships of adjacent classes of caliber-filtered microvessels provide a near-linear graphical “fingerprint” of tumor micro-angioarchitecture. Position, slope and axial projections of this graphical outcome reflect biological features and summarize the properties of tumor micro-angioarchitecture. Notably, treatment of KMS-11 xenografts with anti-angiogenic drugs affected position and slope of the specific curves without degrading their near-linear properties. The possibility offered by this procedure to describe and quantify the 3D features of the tumor micro-angioarchitecture paves the way to the analysis of the microvascular tree in human tumor specimens at different stages of tumor progression and after pharmacologic interventions, with possible diagnostic and prognostic implications.

Quantitative vessel tortuosity: A potential CT imaging biomarker for distinguishing lung granulomas from adenocarcinomas

Adenocarcinomas and active granulomas can both have a spiculated appearance on computed tomography (CT) and both are often fluorodeoxyglucose (FDG) avid on positron emission tomography (PET) scan, making them difficult to distinguish. Consequently, patients with benign granulomas are often subjected to invasive surgical biopsies or resections. In this study, quantitative vessel tortuosity (QVT), a novel CT imaging biomarker to distinguish between benign granulomas and adenocarcinomas on routine non-contrast lung CT scans is introduced. Our study comprised of CT scans of 290 patients from two different institutions, one cohort for training (N = 145) and the other (N = 145) for independent validation. In conjunction with a machine learning classifier, the top informative and stable QVT features yielded an area under receiver operating characteristic curve (ROC AUC) of 0.85 in the independent validation set. On the same cohort, the corresponding AUCs for two human experts including a radiologist and a pulmonologist were found to be 0.61 and 0.60, respectively. QVT features also outperformed well known shape and textural radiomic features which had a maximum AUC of 0.73 (p-value = 0.002), as well as features learned using a convolutional neural network AUC = 0.76 (p-value = 0.028). Our results suggest that QVT features could potentially serve as a non-invasive imaging biomarker to distinguish granulomas from adenocarcinomas on non-contrast CT scans.

Exercise Test Performance Reveals Evidence of the Cardiorespiratory Fitness Hypothesis

Positive physiologic and cognitive responses to aerobic exercise have resulted in a proposed cardiorespiratory (CR) fitness hypothesis in which fitness gains drive changes leading to cognitive benefit. The purpose of this study was to directly assess the CR fitness hypothesis. Using data from an aerobic exercise trial, we examined individuals who completed cardiopulmonary and cognitive testing at baseline and 26 weeks. Change in cognitive test performance was not related to CR fitness change (r2 = .06, p = .06). However, in the subset of individuals who gave excellent effort during exercise testing, change in cognitive test performance was related to CR fitness change (r2 = .33, p < .01). This was largely due to change in the cognitive domain of attention (r2 = .36, p < .01). The magnitude of change was not explained by duration of exercise. Our findings support further investigation of the CR fitness hypothesis and mechanisms by which physiologic adaptation may drive cognitive change.

3-D Ultrasound Localization Microscopy for Identifying Microvascular Morphology Features of Tumor Angiogenesis at a Resolution Beyond the Diffraction Limit of Conventional Ultrasound

Angiogenesis has been known as a hallmark of solid tumor cancers for decades, yet ultrasound has been limited in its ability to detect the microvascular changes associated with malignancy. Here, we demonstrate the potential of 'ultrasound localization microscopy' applied volumetrically in combination with quantitative analysis of microvascular morphology, as an approach to overcome this limitation. This pilot study demonstrates our ability to image complex microvascular patterns associated with tumor angiogenesis in-vivo at a resolution of tens of microns - substantially better than the diffraction limit of traditional clinical ultrasound, yet using an 8 MHz clinical ultrasound probe. Furthermore, it is observed that data from healthy and tumor-bearing tissue exhibit significant differences in microvascular pattern and density. Results suggests that with continued development of these novel technologies, ultrasound has the potential to detect biomarkers of cancer based on the microvascular 'fingerprint' of malignant angiogenesis rather than through imaging of blood flow dynamics or the tumor mass itself.

Glioma vessel abnormality quantification using time-of-flight MR angiography

OBJECTIVES

To differentiate between abnormal tumor vessels and regular brain vasculature using new quantitative measures in time-of-flight (TOF) MR angiography (MRA) data.

MATERIALS AND METHODS

In this work time-of-flight (TOF) MR angiography data are acquired in 11 glioma patients to quantify vessel abnormality. Brain vessels are first segmented with a new algorithm, efficient monte-carlo image-analysis for the location of vascular entity (EMILOVE), and are then characterized in three brain regions: tumor, normal-appearing contralateral brain, and the total brain volume without the tumor. For characterization local vessel orientation angles and the dot product between local orientation vectors are calculated and averaged in the 3 regions. Additionally, correlation with histological and genetic markers is performed.

RESULTS

Both the local vessel orientation angles and the dot product show a statistically significant difference (p < 0.005) between tumor vessels and normal brain vasculature. Furthermore, the connection to both histology and the gene expression of the tumor can be found-here, the measures were compared to the proliferation marker Ki-67 [MIB] and genome-wide expression analysis. The results in a subgroup indicate that the dot product measure may be correlated with activated genetic pathways.

CONCLUSION

It is possible to define a measure of vessel abnormality based on local vessel orientation angles which can differentiate between normal brain vasculature and glioblastoma vessels.

The implementation of acoustic angiography for microvascular and angiogenesis imaging

Recently, it has been demonstrated that through the use of contrast agents and multi-frequency transducer technology, high resolution and high signal to noise ultrasound images can be obtained which illustrate microvascular structure in unprecedented detail for an ultrasound modality. The enabling technology is ultrasound transducers which are fabricated with elements which can excite microbubble contrast agents near resonance and detect their broadband harmonics at a much higher bandwidth (several times the fundamental frequency). The resulting images contain very little background from tissue scattering and thus provide high contrast, and can have a resolution on the order of 130 microns with an appropriate high frequency receiving element. Because microbubbles are strictly an intravascular agent, this approach enables visualization of microvascular morphology with unique clarity, providing insight into angiogenesis associated with tumor development.

Ultrasound imaging of breast tumor perfusion and neovascular morphology

A novel image processing strategy is detailed for simultaneous measurement of tumor perfusion and neovascular morphology parameters from a sequence of dynamic contrast-enhanced ultrasound (DCE-US) images. After normalization and tumor segmentation, a global time-intensity curve describing contrast agent flow was analyzed to derive surrogate measures of tumor perfusion (i.e., peak intensity, time-to-peak intensity, area under the curve, wash-in rate, wash-out rate). A maximum intensity image was generated from these same segmented image sequences, and each vascular component was skeletonized via a thinning algorithm. This skeletonized data set and collection of vessel segments were then investigated to extract parameters related to the neovascular network and physical architecture (i.e., vessel-to-tissue ratio, number of bifurcations, vessel count, average vessel length and tortuosity). An efficient computation of local perfusion parameters was also introduced and operated by averaging time-intensity curve data over each individual neovascular segment. Each skeletonized neovascular segment was then color-coded by these local measures to produce a parametric map detailing spatial properties of tumor perfusion. Longitudinal DCE-US image data sets were collected in six patients diagnosed with invasive breast cancer using a Philips iU22 ultrasound system equipped with a L9-3 transducer and Definity contrast agent. Patients were imaged using US before and after contrast agent dosing at baseline and again at weeks 6, 12, 18 and 24 after treatment started. Preliminary clinical results suggested that breast tumor response to neoadjuvant chemotherapy may be associated with temporal and spatial changes in DCE-US-derived parametric measures of tumor perfusion. Moreover, changes in neovascular morphology parametric measures may also help identify any breast tumor response (or lack thereof) to systemic treatment. Breast cancer management from early detection to therapeutic monitoring is currently undergoing profound changes. Novel imaging techniques that are sensitive to the unique biological conditions of each individual tumor represent valuable tools in the pursuit of personalized medicine.

Quantification of Microvascular Tortuosity during Tumor Evolution Using Acoustic Angiography

The recent design of ultra-broadband, multifrequency ultrasound transducers has enabled high-sensitivity, high-resolution contrast imaging, with very efficient suppression of tissue background using a technique called acoustic angiography. Here we perform the first application of acoustic angiography to evolving tumors in mice predisposed to develop mammary carcinoma, with the intent of visualizing and quantifying angiogenesis progression associated with tumor growth. Metrics compared include vascular density and two measures of vessel tortuosity quantified from segmentations of vessels traversing and surrounding 24 tumors and abdominal vessels from control mice. Quantitative morphologic analysis of tumor vessels revealed significantly increased vascular tortuosity abnormalities associated with tumor growth, with the distance metric elevated approximately 14% and the sum of angles metric increased 60% in tumor vessels versus controls. Future applications of this imaging approach may provide clinicians with a new tool in tumor detection, differentiation or evaluation, though with limited depth of penetration using the current configuration.

Acoustic angiography: a new imaging modality for assessing microvasculature architecture

The purpose of this paper is to provide the biomedical imaging community with details of a new high resolution contrast imaging approach referred to as “acoustic angiography.” Through the use of dual-frequency ultrasound transducer technology, images acquired with this approach possess both high resolution and a high contrast-to-tissue ratio, which enables the visualization of microvascular architecture without significant contribution from background tissues. Additionally, volumetric vessel-tissue integration can be visualized by using b-mode overlays acquired with the same probe. We present a brief technical overview of how the images are acquired, followed by several examples of images of both healthy and diseased tissue volumes. 3D images from alternate modalities often used in preclinical imaging, contrast-enhanced micro-CT and photoacoustics, are also included to provide a perspective on how acoustic angiography has qualitatively similar capabilities to these other techniques. These preliminary images provide visually compelling evidence to suggest that acoustic angiography may serve as a powerful new tool in preclinical and future clinical imaging.

Current status and prospects for microbubbles in ultrasound theranostics

Encapsulated microbubbles have been developed over the past two decades to provide improvements both in imaging as well as new therapeutic applications. Microbubble contrast agents are used currently for clinical imaging where increased sensitivity to blood flow is required, such as echocardiography. These compressible spheres oscillate in an acoustic field, producing nonlinear responses which can be uniquely distinguished from surrounding tissue, resulting in substantial enhancements in imaging signal-to-noise ratio. Furthermore, with sufficient acoustic energy the oscillation of microbubbles can mediate localized biological effects in tissue including the enhancement of membrane permeability or increased thermal energy deposition. Structurally, microbubbles are comprised of two principal components--an encapsulating shell and an inner gas core. This configuration enables microbubbles to be loaded with drugs or genes for additional therapeutic effect. Application of sufficient ultrasound energy can release this payload, resulting in site-specific delivery. Extensive preclinical studies illustrate that combining microbubbles and ultrasound can result in enhanced drug delivery or gene expression at spatially selective sites. Thus, microbbubles can be used for imaging, for therapy, or for both simultaneously. In this sense, microbubbles combined with acoustics may be one of the most universal theranostic tools.

Current status and prospects for microbubbles in ultrasound theranostics

Encapsulated microbubbles have been developed over the past two decades to provide improvements both in imaging as well as new therapeutic applications. Microbubble contrast agents are used currently for clinical imaging where increased sensitivity to blood flow is required, such as echocardiography. These compressible spheres oscillate in an acoustic field, producing nonlinear responses which can be uniquely distinguished from surrounding tissue, resulting in substantial enhancements in imaging signal-to-noise ratio. Furthermore, with sufficient acoustic energy the oscillation of microbubbles can mediate localized biological effects in tissue including the enhancement of membrane permeability or increased thermal energy deposition. Structurally, microbubbles are comprised of two principal components--an encapsulating shell and an inner gas core. This configuration enables microbubbles to be loaded with drugs or genes for additional therapeutic effect. Application of sufficient ultrasound energy can release this payload, resulting in site-specific delivery. Extensive preclinical studies illustrate that combining microbubbles and ultrasound can result in enhanced drug delivery or gene expression at spatially selective sites. Thus, microbbubles can be used for imaging, for therapy, or for both simultaneously. In this sense, microbubbles combined with acoustics may be one of the most universal theranostic tools.

Mapping microvasculature with acoustic angiography yields quantifiable differences between healthy and tumor-bearing tissue volumes in a rodent model

PURPOSE

To determine if the morphologies of microvessels could be extracted from contrast material-enhanced acoustic angiographic ultrasonographic (US) images and used as a quantitative basis for distinguishing healthy from diseased tissue.

MATERIALS AND METHODS

All studies were institutional animal care and use committee approved. Three-dimensional contrast-enhanced acoustic angiographic images were acquired in both healthy (n = 7) and tumor-bearing (n = 10) rats. High-spatial-resolution and high signal-to-noise acquisition was enabled by using a prototype dual-frequency US transducer (transmit at 4 MHz, receive at 30 MHz). A segmentation algorithm was utilized to extract microvessel structure from image data, and the distance metric (DM) and the sum of angles metric (SOAM), designed to distinguish different types of tortuosity, were applied to image data. The vessel populations extracted from tumor-bearing tissue volumes were compared against vessels extracted from tissue volumes in the same anatomic location within healthy control animals by using the two-sided Student t test.

RESULTS

Metrics of microvascular tortuosity were significantly higher in the tumor population. The average DM of the tumor population (1.34 ± 0.40 [standard deviation]) was 23.76% higher than that of the control population (1.08 ± 0.08) (P < .0001), while the average SOAM (22.53 ± 7.82) was 50.73% higher than that of the control population (14.95 ± 4.83) (P < .0001). The DM and SOAM metrics for the control and tumor populations were significantly different when all vessels were pooled between the two animal populations. In addition, each animal in the tumor population had significantly different DM and SOAM metrics relative to the control population (P < .05 for all; P value ranges for DM, 3.89 × 10(-)(7) to 5.63 × 10(-)(3); and those for SOAM, 2.42 × 10(-)(12) to 1.57 × 10(-)(3)).

CONCLUSION

Vascular network quantification by using high-spatial-resolution acoustic angiographic images is feasible. Data suggest that the angiogenic processes associated with tumor development in the models studied result in higher instances of vessel tortuosity near the tumor site.

Vascular tortuosity: a mathematical modeling perspective

Although vascular tortuosity is a ubiquitous phenomenon, almost no mathematical models exist to describe its shape. Given that the shape of tortuous vessel curves seems fairly uniform across orders of magnitude of vessel size and across vast differences in anatomic substrata, it is hypothesized that the shape of tortuosity is not purely random but rather is governed by physical principles. We present a mathematical model of tortuosity based on optimality principles, and show how this model can potentially be used to distinguish physiologic tortuosity from abnormal tortuosity which may exist in disease states. Using the calculus of variations, a model of tortuosity has been developed which minimizes average curvature per unit length. The model is tested against curves in normal vessels and in diseased vessels in a case of Fabry's disease. It is found that the theoretical model provides a good fit for normal vessel tortuosity. This suggests that blood vessels obey optimality principles, and curve in such a way as to minimize average curvature. The model may also be able to distinguish physiologic tortuosity from abnormal tortuosity found in disease states.

Development of image-processing software for automatic segmentation of brain tumors in MR images

Most of the commercially available software for brain tumor segmentation have limited functionality and frequently lack the careful validation that is required for clinical studies. We have developed an image-analysis software package called ‘Prometheus,’ which performs neural system–based segmentation operations on MR images using pre-trained information. The software also has the capability to improve its segmentation performance by using the training module of the neural system. The aim of this article is to present the design and modules of this software. The segmentation module of Prometheus can be used primarily for image analysis in MR images. Prometheus was validated against manual segmentation by a radiologist and its mean sensitivity and specificity was found to be 85.71±4.89% and 93.2±2.87%, respectively. Similarly, the mean segmentation accuracy and mean correspondence ratio was found to be 92.35±3.37% and 0.78±0.046, respectively.

Algorithm-based method for detection of blood vessels in breast MRI for development of computer-aided diagnosis

PURPOSE

To develop a computer-based algorithm for detecting blood vessels that appear in breast dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI), and to evaluate the improvement in reducing the number of vascular pixels that are labeled by computer-aided diagnosis (CAD) systems as being suspicious of malignancy.

MATERIALS AND METHODS

The analysis was performed in 34 cases. The algorithm applied a filter bank based on wavelet transform and the Hessian matrix to detect linear structures as blood vessels on a two-dimensional maximum intensity projection (MIP). The vessels running perpendicular to the MIP plane were then detected based on the connectivity of enhanced pixels above a threshold. The nonvessel enhancements were determined and excluded based on their morphological properties, including those showing scattered small segment enhancements or nodular or planar clusters. The detected vessels were first converted to a vasculature skeleton by thinning and subsequently compared to the vascular track manually drawn by a radiologist.

RESULTS

When evaluating the performance of the algorithm in identifying vascular tissue, the correct-detection rate refers to pixels identified by both the algorithm and radiologist, while the incorrect-detection rate refers to pixels identified by only the algorithm, and the missed-detection rate refers to pixels identified only by the radiologist. From 34 analyzed cases the median correct-detection rate was 85.6% (mean 84.9% +/- 7.8%), the incorrect-detection rate was 13.1% (mean 15.1% +/- 7.8%), and the missed-detection rate was 19.2% (mean 21.3% +/- 12.8%). When detected vessels were excluded in the hot-spot color-coding of the CAD system, they could reduce the labeling of vascular vessels in 2.6%-68.6% of hot-spot pixels (mean 16.6% +/- 15.9%).

CONCLUSION

The computer algorithm-based method can detect most large vessels and provide an effective means in reducing the labeling of vascular pixels as suspicious on a DCE-MRI CAD system. This algorithm may improve the workflow of radiologists using CAD for image display, but will be particularly useful for development of automated CAD that gives diagnostic impression.