Correlation of MR perfusion imaging and vessel tortuosity parameters in assessment of intracranial neoplasms

High-Quality Ultrafast Power Doppler Imaging Based on Spatial Angular Coherence Factor

The morphological and hemodynamic changes of microvessels are demonstrated to be related to the diseased conditions in tissues. Ultrafast power Doppler imaging (uPDI) is a novel modality with a significantly increased Doppler sensitivity, benefiting from the ultrahigh frame rate plane-wave imaging (PWI) and advanced clutter filtering. However, unfocused plane-wave transmission often leads to a low imaging quality, which degrades the subsequent microvascular visualization in power Doppler imaging. Coherence factor (CF)-based adaptive beamformers have been widely studied in conventional B-mode imaging. In this study, we propose a spatial and angular coherence factor (SACF) beamformer for improved uPDI (SACF-uPDI) by calculating the spatial CF across apertures and the angular CF across transmit angles, respectively. To identify the superiority of SACF-uPDI, simulations, in vivo contrast-enhanced rat kidney, and in vivo contrast-free human neonatal brain studies were conducted. Results demonstrate that SACF-uPDI can effectively enhance contrast and resolution and suppress background noise simultaneously, compared with conventional uPDI methods based on delay-and-sum (DAS) (DAS-uPDI) and CF (CF-uPDI). In the simulations, SACF-uPDI can improve the lateral and axial resolutions compared with those of DAS-uPDI, from 176 to [Formula: see text] of lateral resolution, and from 111 to [Formula: see text] of axial resolution. In the in vivo contrast-enhanced experiments, SACF achieves 15.14- and 5.6-dB higher contrast-to-noise ratio (CNR), 15.25- and 3.68-dB lower noise power, and 240- and 15- [Formula: see text] narrower full-width at half-maximum (FWHM) than DAS-uPDI and CF-uPDI, respectively. In the in vivo contrast-free experiments, SACF achieves 6.11- and 1.09-dB higher CNR, 11.93- and 4.01-dB lower noise power, and 528- and 160- [Formula: see text] narrower FWHM than DAS-uPDI and CF-uPDI, respectively. In conclusion, the proposed SACF-uPDI method can efficiently improve the microvascular imaging quality and has the potential to facilitate clinical applications.

Improved Ultrafast Power Doppler Imaging by Using Spatiotemporal Non-Local Means Filtering

The change of microvasculature is associated with the occurrence and development of many diseases. Ultrafast power Doppler imaging (uPDI) is an emerging technology for the visualization of microvessels due to the development of ultrafast plane wave (PW) imaging and advanced clutter filters. However, the low signal-to-noise ratio (SNR) caused by unfocused transmit of PW imaging deteriorates the subsequent imaging of microvasculature. Nonlocal means (NLM) filtering has been demonstrated to be effective in the denoising of both natural and medical images, including ultrasound power Doppler images. However, the feasibility and performance of applying an NLM filter on the ultrasound radio frequency (RF) data have not been investigated so far. In this study, we propose to apply an NLM filter on the spatiotemporal domain of clutter filtered blood flow RF data (St-NLM) to improve the quality of uPDI. Experiments were conducted to compare the proposed method with three different methods (under various similarity window sizes), including conventional uPDI without NLM filtering (Non-NLM), NLM filtering on the obtained power Doppler images (PD-NLM), and NLM filtering on the spatial domain of clutter filtered blood flow RF data (S-NLM). Phantom experiments, in vivo contrast-enhanced human spinal cord tumor experiments, and in vivo contrast-free human liver experiments were performed to demonstrate the superiority of the proposed St-NLM method over the other three methods. Qualitative and quantitative results show that the proposed St-NLM method can effectively suppress the background noise, improve the contrast between vessels and background, and preserve the details of small vessels at the same time. In the human liver study, the proposed St-NLM method achieves 31.05-, 24.49-, and 11.15-dB higher contrast-to-noise ratios (CNRs) and 36.86-, 36.86-, and 15.22-dB lower noise powers than Non-NLM, PD-NLM, and S-NLM, respectively. In the human spinal cord tumor, the full-width at half-maximums (FWHMs) of vessel cross Section are 76, 201, and [Formula: see text] for St-NLM, Non-NLM, and S-NLM, respectively. The proposed St-NLM method can enhance the microvascular visualization in uPDI and has the potential for the diagnosis of many microvessel-change-related diseases.

Segmentation and Quantitative Analysis of Photoacoustic Imaging: A Review

Photoacoustic imaging is an emerging biomedical imaging technique that combines optical contrast and ultrasound resolution to create unprecedented light absorption contrast in deep tissue. Thanks to its fusional imaging advantages, photoacoustic imaging can provide multiple structural and functional insights into biological tissues such as blood vasculatures and tumors and monitor the kinetic movements of hemoglobin and lipids. To better visualize and analyze the regions of interest, segmentation and quantitative analyses were used to extract several biological factors, such as the intensity level changes, diameter, and tortuosity of the tissues. Over the past 10 years, classical segmentation methods and advances in deep learning approaches have been utilized in research investigations. In this review, we provide a comprehensive review of segmentation and quantitative methods that have been developed to process photoacoustic imaging in preclinical and clinical experiments. We focus on the parametric reliability of quantitative analysis for semantic and instance-level segmentation. We also introduce the similarities and alternatives of deep learning models in qualitative measurements using classical segmentation methods for photoacoustic imaging.

Quantitative Biomarkers for Cancer Detection Using Contrast-Free Ultrasound High-Definition Microvessel Imaging: Fractal Dimension, Murray's Deviation, Bifurcation Angle & Spatial Vascularity Pattern

A growing body of evidence indicates that there is a strong correlation between microvascular morphological features and malignant tumors. Therefore, quantification of these features might allow more accurate differentiation of benign and malignant tumors. The main objective of this research project is to improve the quantification of microvascular networks depicted in contrast-free ultrasound microvessel images. To achieve this goal, a new series of quantitative microvessel morphological parameters are introduced for differentiation of breast masses using contrast-free ultrasound-based high-definition microvessel imaging (HDMI). Using HDMI, we quantified and analyzed four new parameters: 1) microvessel fractal dimension (mvFD), a marker of tumor microvascular complexity; 2) Murray's deviation (MD), the diameter mismatch, defined as the deviation from Murray's law; 3) bifurcation angle (BA), abnormally decreased angle; and 4) spatial vascular pattern (SVP), indicating tumor vascular distribution pattern, either intratumoral or peritumoral. The new biomarkers have been tested on 60 patients with breast masses. Validation of the feature's extraction algorithm was performed using a synthetic data set. All the proposed parameters had the power to discriminate the breast lesion malignancy (p < 0.05), displaying BA as the most sensitive test, with a sensitivity of 90.6%, and mvFD as the most specific test, with a specificity of 92%. The results of all four new biomarkers showed an AUC = 0.889, sensitivity of 80% and specificity of 91.4% In conclusion, the added value of the proposed quantitative morphological parameters, as new biomarkers of angiogenesis within breast masses, paves the way for more accurate breast cancer detection with higher specificity.

Quantification of Morphological Features in Non-Contrast-Enhanced Ultrasound Microvasculature Imaging

There are significant differences in microvascular morphological features in diseased tissues, such as cancerous lesions, compared to noncancerous tissue. Quantification of microvessel morphological features could play an important role in disease diagnosis and tumor classification. However, analyzing microvessel morphology in ultrasound Doppler is a challenging task due to limitations associated with this technique. Our main objective is to provide methods for quantifying morphological features of microvasculature obtained by ultrasound Doppler imaging. To achieve this goal, we propose multiple image enhancement techniques and appropriate morphological feature extraction methods that enable quantitative analysis of microvasculature structures. Vessel segments obtained by the skeletonization of the regularized microvasculature images are further analyzed to satisfy other constraints, such as vessel segment diameter and length. Measurements of some morphological metrics, such as tortuosity, depend on preserving large vessel trunks. To address this issue, additional filtering methods are proposed. These methods are tested on in vivo images of breast lesion and thyroid nodule microvasculature, and the outcomes are discussed. Initial results show that using vessel morphological features allows for differentiation between malignant and benign breast lesions (p-value < 0.005) and thyroid nodules (p-value < 0.01). This paper provides a tool for the quantification of microvasculature images obtained by non-contrast ultrasound imaging, which may serve as potential biomarkers for the diagnosis of some diseases.

Background Removal and Vessel Filtering of Noncontrast Ultrasound Images of Microvasculature

OBJECTIVE

Recent advances in ultrasound Doppler imaging have made it possible to visualize small vessels with diameters near the imaging resolution limits using spatiotemporal singular value thresholding of long ensembles of ultrasound data. However, vessel images derived based on this method present severe intensity variations and additional background noise that limits visibility and subsequent processing such as centerline extraction and morphological analysis. The goal of this paper is to devise a method to enhance vessel-background separation directly on the power Doppler images by exploiting blood echo-noise independence.

METHOD

We present a two-step algorithm to mitigate these adverse effects when using singular value thresholding for obtaining gross vasculature images. Our method comprises a morphological-based filtering for removing global and local background signals and a multiscale Hessian-based vessel enhancement filtering to further improve the vascular structures. We applied our method for in vivo imaging of the microvasculature of kidney in one healthy subject, liver in five healthy subjects, thyroid nodules in five patients, and breast tumors in five patients.

RESULTS

Singular value thresholding, top-hat filtering, and Hessian-based vessel enhancement filtering each provided an average peak-to-side level gain of 1.11, 18.55, and 2.26 dB, respectively, resulting in an overall gain of 21.92 dB when compared to the conventional power Doppler imaging using infinite impulse response filtering.

CONCLUSION

Singular value thresholding combined with morphological and Hessian-based vessel enhancement filtering provides a powerful tool for visualization of the deep-seated small vessels using long ultrasound echo ensembles without requiring any type of contrast enhancing agents.

SIGNIFICANCE

This method provides a fast and cost-effective modality for in vivo assessment of the microvasculature suitable for both clinical and preclinical applications.

Three-dimensional Hessian matrix-based quantitative vascular imaging of rat iris with optical-resolution photoacoustic microscopy in vivo

For the diagnosis and evaluation of ophthalmic diseases, imaging and quantitative characterization of vasculature in the iris are very important. The recently developed photoacoustic imaging, which is ultrasensitive in imaging endogenous hemoglobin molecules, provides a highly efficient label-free method for imaging blood vasculature in the iris. However, the development of advanced vascular quantification algorithms is still needed to enable accurate characterization of the underlying vasculature. We have developed a vascular information quantification algorithm by adopting a three-dimensional (3-D) Hessian matrix and applied for processing iris vasculature images obtained with a custom-built optical-resolution photoacoustic imaging system (OR-PAM). For the first time, we demonstrate in vivo 3-D vascular structures of a rat iris with a the label-free imaging method and also accurately extract quantitative vascular information, such as vessel diameter, vascular density, and vascular tortuosity. Our results indicate that the developed algorithm is capable of quantifying the vasculature in the 3-D photoacoustic images of the iris in-vivo, thus enhancing the diagnostic capability of the OR-PAM system for vascular-related ophthalmic diseases in vivo.

Imaging Surrogates of Infiltration Obtained Via Multiparametric Imaging Pattern Analysis Predict Subsequent Location of Recurrence of Glioblastoma

BACKGROUND

Glioblastoma is an aggressive and highly infiltrative brain cancer. Standard surgical resection is guided by enhancement on postcontrast T1-weighted (T1) magnetic resonance imaging, which is insufficient for delineating surrounding infiltrating tumor.

OBJECTIVE

To develop imaging biomarkers that delineate areas of tumor infiltration and predict early recurrence in peritumoral tissue. Such markers would enable intensive, yet targeted, surgery and radiotherapy, thereby potentially delaying recurrence and prolonging survival.

METHODS

Preoperative multiparametric magnetic resonance images (T1, T1-gadolinium, T2-weighted, T2-weighted fluid-attenuated inversion recovery, diffusion tensor imaging, and dynamic susceptibility contrast-enhanced magnetic resonance images) from 31 patients were combined using machine learning methods, thereby creating predictive spatial maps of infiltrated peritumoral tissue. Cross-validation was used in the retrospective cohort to achieve generalizable biomarkers. Subsequently, the imaging signatures learned from the retrospective study were used in a replication cohort of 34 new patients. Spatial maps representing the likelihood of tumor infiltration and future early recurrence were compared with regions of recurrence on postresection follow-up studies with pathology confirmation.

RESULTS

This technique produced predictions of early recurrence with a mean area under the curve of 0.84, sensitivity of 91%, specificity of 93%, and odds ratio estimates of 9.29 (99% confidence interval: 8.95-9.65) for tissue predicted to be heavily infiltrated in the replication study. Regions of tumor recurrence were found to have subtle, yet fairly distinctive multiparametric imaging signatures when analyzed quantitatively by pattern analysis and machine learning.

CONCLUSION

Visually imperceptible imaging patterns discovered via multiparametric pattern analysis methods were found to estimate the extent of infiltration and location of future tumor recurrence, paving the way for improved targeted treatment.

Non-invasive MR assessment of macroscopic and microscopic vascular abnormalities in the rectal tumour-surrounding mesorectum

OBJECTIVES

To evaluate the MRI macroscopic and microscopic parameters of mesorectal vasculature in rectal cancer patients.

METHODS

Thirteen patients with rectal adenocarcinoma underwent a dynamic contrast-enhanced MRI at 1.5 T using a blood pool agent at the primary staging. Mesorectal macrovascular features, i.e., the number of vascular branches, average diameter and length, were assessed from baseline-subtracted post-contrast images by two independent readers. Mesorectal microvascular function was investigated by means of area under the enhancement-time curve (AUC). Histopathology served as reference standard of the tumour response to CRT.

RESULTS

The average vessel branching in the mesorectum around the tumour and normal rectal wall was 8.2 ± 3.8 and 1.7 ± 1.3, respectively (reader1: p = 0.001, reader2: p = 0.002). Similarly, the tumour-surrounding mesorectum displayed circa tenfold elevated AUC (p = 0.01). Interestingly, patients with primary node involvement had a twofold higher number of macrovascular branches compared to those with healthy nodes (reader1: p = 0.005 and reader2: p = 0.03). A similar difference was observed between good and poor responders to CRT, whose tumour-surrounding mesorectum displayed 10.7 ± 3.4 and 5.6 ± 1.5 vessels, respectively (reader1/reader2: p = 0.02).

CONCLUSIONS

We showed at baseline MRI of rectal tumours a significantly enhanced macrovascular structure and microvascular function in rectal tumour-surrounding mesorectum, and the association of primary mesorectal macrovascular parameters with node involvement and therapy response.

KEY POINTS

• Vascular MRI reveals macrovascular and microvascular abnormalities in the rectal tumour-surrounding mesorectum. • Formation of highly vascular stroma precedes the actual tumour invasion. • High macrovascular parameters are associated with node involvement. • Mesorectal vascular network differs for good and poor responders.

Survival analysis in patients with newly diagnosed primary glioblastoma multiforme using pre- and post-treatment peritumoral perfusion imaging parameters

The objective of this study was to evaluate if peritumoral (PT) perfusion parameters obtained from dynamic susceptibility weighted contrast enhanced perfusion MRI can predict overall survival (OS) and progression free survival (PFS) in patients with newly diagnosed glioblastoma multiforme (GBM). Twenty-eight newly diagnosed GBM patients, who were treated with resection followed by concurrent chemoradiation and adjuvant chemotherapy, were included in this study. Evaluated perfusion parameters were pre- and post-treatment PT relative cerebral blood volume (rCBV) and relative cerebral blood flow (rCBF). Proportional hazard analysis was used to assess the relationship OS, PFS and perfusion parameters. Kaplan-Meier survival estimates and log-rank test were used to characterize and compare the patient groups with high and low perfusion parameter values in terms of OS and PFS. Pretreatment PT rCBV and rCBF were not associated with OS and PFS whereas there was statistically significant association of both posttreatment PT rCBV and rCBF with OS and posttreatment rCBV with PFS (association of PFS and posttreatment rCBF was not statistically significant). Neither the Kaplan-Meier survival estimates nor the log-rank test demonstrated any differences in OS between high and low pretreatment PT rCBV values and rCBF values; however, high and low post-treatment PT rCBV and rCBF values did demonstrate statistically significant difference in OS and PFS. Our study found posttreatment, not pretreatment, PT perfusion parameters can be used to predict OS and PFS in patients with newly diagnosed GBM.

Multi-parametric quantitative microvascular imaging with optical-resolution photoacoustic microscopy in vivo

Many diseases involve either the formation of new blood vessels (e.g., tumor angiogenesis) or the damage of existing ones (e.g., diabetic retinopathy) at the microcirculation level. Optical-resolution photoacoustic microscopy (OR-PAM), capable of imaging microvessels in 3D in vivo down to individual capillaries using endogenous contrast, has the potential to reveal microvascular information critical to the diagnosis and staging of microcirculation-related diseases. In this study, we have developed a dedicated microvascular quantification (MQ) algorithm for OR-PAM to automatically quantify multiple microvascular morphological parameters in parallel, including the vessel diameter distribution, the microvessel density, the vascular tortuosity, and the fractal dimension. The algorithm has been tested on in vivo OR-PAM images of a healthy mouse, demonstrating high accuracy for microvascular segmentation and quantification. The developed MQ algorithm for OR-PAM may greatly facilitate quantitative imaging of tumor angiogenesis and many other microcirculation related diseases in vivo.

Evolutionary etiology of high-grade astrocytomas

Glioblastoma (GBM), the most common brain malignancy, remains fatal with no effective treatment. Analyses of common aberrations in GBM suggest major regulatory pathways associated with disease etiology. However, 90% of GBMs are diagnosed at an advanced stage (primary GBMs), providing no access to early disease stages for assessing disease progression events. As such, both understanding of disease mechanisms and the development of biomarkers and therapeutics for effective disease management are limited. Here, we describe an adult-inducible astrocyte-specific system in genetically engineered mice that queries causation in disease evolution of regulatory networks perturbed in human GBM. Events yielding disease, both engineered and spontaneous, indicate ordered grade-specific perturbations that yield high-grade astrocytomas (anaplastic astrocytomas and GBMs). Impaired retinoblastoma protein RB tumor suppression yields grade II histopathology. Additional activation of v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS) network drives progression to grade III disease, and further inactivation of phosphatase and tensin homolog (PTEN) yields GBM. Spontaneous missense mutation of tumor suppressor Trp53 arises subsequent to KRAS activation, but before grade III progression. The stochastic appearance of mutations identical to those observed in humans, particularly the same spectrum of p53 amino acid changes, supports the validity of engineered lesions and the ensuing interpretations of etiology. Absence of isocitrate dehydrogenase 1 (IDH1) mutation, asymptomatic low grade disease, and rapid emergence of GBM combined with a mesenchymal transcriptome signature reflect characteristics of primary GBM and provide insight into causal relationships.

A two-stage model for in vivo assessment of brain tumor perfusion and abnormal vascular structure using arterial spin labeling

The ability to assess brain tumor perfusion and abnormalities in the vascular structure in vivo could provide significant benefits in terms of lesion diagnosis and assessment of treatment response. Arterial spin labeling (ASL) has emerged as an increasingly viable methodology for non-invasive assessment of perfusion. Although kinetic models have been developed to describe perfusion in healthy tissue, the dynamic behaviour of the ASL signal in the brain tumor environment has not been extensively studied. We show here that dynamic ASL data acquired in brain tumors displays an increased level of 'biphasic' behaviour, compared to that seen in healthy tissue. A new two-stage model is presented which more accurately describes this behaviour, and provides measurements of perfusion, pre-capillary blood volume fraction and transit time, and capillary bolus arrival time. These biomarkers offer a novel contrast in the tumor and surrounding tissue, and provide a means for measuring tumor perfusion and vascular structural abnormalities in a fully non-invasive manner.

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.

A phase II study of sagopilone (ZK 219477; ZK-EPO) in patients with breast cancer and brain metastases

Treatments for women with recurrent brain metastases from breast cancer are limited. In this phase II study,we administered sagopilone to patients with breast cancer and brain metastases. We observed modest activity with a central nervous system objective response rate of 13.3%; however, median PFS was disappointing. Further studies should focus on other agents to treat this challenging clinical problem.

BACKGROUND

Patients with progressive metastatic breast cancer to the central nervous system (CNS) have limited treatment options.

PATIENTS AND METHODS

We conducted a phase II study of sagopilone, an epothilone B analogue that crosses the blood-brain barrier, in patients with breast cancer brain metastases. Women were treated with 16 mg/m(2) or 22 mg/m(2) intravenously every 21 days. The primary endpoint was CNS objective response rate (ORR). Secondary endpoints included toxicity, progression-free survival (PFS), and overall survival (OS). Using modified, high-resolution magnetic resonance angiography (MRA), we also evaluated changes in vessel tortuosity with treatment.

RESULTS

Fifteen women were enrolled; all had progressive CNS disease despite whole-brain radiotherapy. Two patients achieved a partial response (ORR, 13.3%) and remained in the study for 6 cycles. Responses were not associated with normalization of tumor-associated vessels on correlative imaging studies. Median PFS and OS were 1.4 months and 5.3 months, respectively. The most common grade 3 toxicities were lymphopenia and fatigue. Enrollment was stopped prematurely because of limited observed activity and slow accrual.

CONCLUSIONS

Sagopilone was associated with modest CNS activity in patients with breast cancer; however median PFS was disappointing. Further studies should examine other potentially active agents and/or combinations for this challenging clinical problem.

Three-dimensional morphometry of the A1 segment of the anterior cerebral artery with neurosurgical relevance

BACKGROUND

Despite research in the anatomical sciences for the last 200 years, some structures of the human body remain controversial or incompletely described. One of these structures is the A1 segment of the anterior cerebral artery (ACA).

OBJECTIVE

To analyze the A1 segment of the ACA using novel stereoscopic methods because the 3-dimensional morphometry of the ACA is important to neurosurgeons.

METHODS

A digital-image computer-based system was used to analyze the A1 segment of 230 ACAs derived from computed tomography. Data analysis included the inner diameter, length, and volume and calculation of A1 symmetry, hypoplasia, and deviation, and tortuosity indexes.

RESULTS

Hypoplasia of the A1 segment was found in 0.87% and only on the right sides, whereas asymmetry was found in 42.6% and was more common in female patients. Right A1 segments tended to be longer in male patients, and this reached significance. Also of significance was the correlation of an increased length with age. Right A1 segments tended to have greater volumes, and this was significant in a comparison of male and female patients. Tortuosity indexes tended to be greater for left sides, but deviation indexes tended to be greater on the right sides.

CONCLUSION

Morphometric data of the A1 segment of the ACA as analyzed in the present study may be of utility to the neurosurgeon. Right A1 segments tend to be more tortuous, more deviated, longer, and narrower than left A1 segments.

Detailed 3D-morphometry of the anterior communicating artery: potential clinical and neurosurgical implications

PURPOSE

Although a site common for pathology and of great importance to the neurosurgeon, the three-dimensional (3D) morphometry of the anterior communicating artery (ACoA) has had incomplete descriptions in the literature.

METHODS

Using a novel 3D digital-image computer data analysis system, 115 patients underwent evaluation of their ACoA based on DICOM files derived from CT angiography. Measurements included the length, internal diameter, volume, deviation index (DI) and tortuosity index (TI).

RESULTS

Of 115 samples, 85 were visualized clearly enough for morphometric analysis. The mean internal diameter was 1.86 mm and this tended to be greater in males (P < 0.05). The mean length of the ACoA was 3.99 mm and the mean volume was 11.61 mm(3). The mean TI for the ACoA was 0.84 and the mean DI was 0.62 mm. A significant relationship between DI and length, DI and volume, and DI and TI were found. The significant correlation of diameter to volume, and length related to volume, DI and TI, as well as TI related to length, volume and DI were noticed. There were no relationship between any parameter and age.

CONCLUSIONS

A detailed knowledge of the 3D-morphometry of the ACoA demonstrates that in almost 50% of individuals the ACoA is straight in their course. Detailed data regarding arterial topography and trajectory as found in our study may be also of use in detecting early changes in this vessel due to pathology and may assist in the treatment of vascular lesions and planning of neurosurgical or interventional radiological procedures in the region including ACoA aneurysms.

Three-dimensional morphometry of the A2 segment of the anterior cerebral artery with neurosurgical relevance

Most prior morphometry data regarding the A2 segment of the anterior cerebral artery (ACA) have been based on cadaveric measurements. With newer imaging modalities, surgical techniques, and minimally invasive procedures, new standards for the anatomy of this vessel are necessary. A novel computer-based data system was used to analyze the three-dimensional (3D) morphometry of 230 A2 segments. In addition, tortuosity (TI) and deviation indices (DI) for this segment were calculated. The mean internal diameter of the A2 segment was 1.86 mm, and segments tended to be larger in men and on left sides. A2 segments were asymmetrical in 43%, and this was more common in women. Lengths tended to be greater on right sides and in men. Volumes were greater in men and increased with age, which was statistically significant. These gender differences were found to be statistically significant (P < 0.05), for both volume and diameter. TI was equal among sides, but DI was more often greater on right sides. The correlation coefficient ratio for length and DI was statistically significant. It is important to understand various 3D morphometrical differences particularly between genders. By constructing blood flow simulation models and during revascularization procedures, surgeons are able to gain a better understanding of each patient's vascular anatomy. These additional 3D data regarding the anatomy of the postcommunicating parts of the ACA may be useful to the neurosurgeon and interventional neuroradiologist. These data may assist with an earlier diagnosis of pathologies affecting the 3D morphology of the ACA.

Blood vessel morphologic changes depicted with MR angiography during treatment of brain metastases: a feasibility study

PURPOSE

To prospectively determine if magnetic resonance (MR) angiography can depict intracranial vascular morphologic changes during treatment of brain metastases from breast cancer and if serial quantitative vessel tortuosity measurements can be used to predict tumor treatment response sooner than traditional methods.

MATERIALS AND METHODS

Institutional review board approval and informed consent were obtained for this HIPAA-compliant study. Twenty-two women aged 31-61 years underwent brain MR angiography prior to and 2 months after initiation of lapatinib therapy for brain metastases from breast cancer. Vessels were extracted from MR angiograms with a computer program. Changes in vessel number, radius, and tortuosity were calculated mathematically, normalized with values obtained in 34 healthy control subjects (19 women, 15 men; age range, 19-72 years), and compared with subsequent assessments of tumor volume and clinical course.

RESULTS

All patients exhibited abnormal vessel tortuosity at baseline. Nineteen (86%) patients did not exhibit improvement in vessel tortuosity at 2-month follow-up, and all patients demonstrated tumor growth at 4-month follow-up. Vessel tortuosity measurements enabled us to correctly predict treatment failure 1-2 months earlier than did traditional methods. Three (14%) patients had quantitative improvement in vessel tortuosity at 2-month follow-up, with drop out of small abnormal vessels and straightening of large vessels. Each of the two patients for whom further follow-up data were available responded to treatment for more than 6 months.

CONCLUSION

Study results established the feasibility of using MR angiography to quantify vessel shape changes during therapy. Although further research is required, results suggest that changes in vessel tortuosity might enable early prediction of tumor treatment response.

The potential of ferumoxytol nanoparticle magnetic resonance imaging, perfusion, and angiography in central nervous system malignancy: a pilot study

OBJECTIVE

Ferumoxytol, an iron oxide nanoparticle that targets phagocytic cells, can be used in magnetic resonance imaging of malignant brain tumors and can be administered as a bolus, allowing dynamic imaging. Our objectives were to determine the optimum time of delayed contrast enhancement of ferumoxytol, and to compare ferumoxytol and gadolinium contrast agents for magnetic resonance angiography and perfusion.

METHODS

Twelve patients with malignant brain tumors underwent serial magnetic resonance imaging multiple times up to 72 hours after ferumoxytol injection at both 1.5 and 3-T. The enhancement time course was determined for ferumoxytol and compared with a baseline gadolinium scan. Perfusion, time-of-flight and dynamic magnetic resonance angiography and T1-weighted scans were compared for the two agents.

RESULTS

The lesions were detectable at all field strengths, even with an intraoperative 0.15-T magnet. Maximal ferumoxytol enhancement intensity was at 24 to 28 hours after administration, and the enhancing volume subsequently expanded with time into a non-gadolinium-enhancing, high T2-weighted signal region of tumor-infiltrated brain. Dynamic studies were assessed with both agents, indicating early vascular leak with gadolinium but not with ferumoxytol.

CONCLUSION

Our most important finding was that gadolinium leaks out of blood vessels early after injection, whereas ferumoxytol stays intravascular in the "early" phase, thereby increasing the accuracy of tumor perfusion assessment. As a magnetic resonance imaging contrast agent, ferumoxytol visualizes brain tumors at all field strengths evaluated, with delayed enhancement peaking at 24 to 28 hours after administration.

A review of micro- and macrovascular analyses in the assessment of tumor-associated vasculature as visualized by MR

There is currently no noninvasive, reliable method of assessing brain tumor malignancy or of monitoring tumor treatment response. Monitoring changes to tumor vasculature might provide an effective means of assessing both tumor aggressiveness and treatment efficacy. To date, most such research has concentrated upon tumor "microvascular" imaging, with permeability and/or perfusion imaging used to assess vessel changes at the subvoxel level. An alternative approach assesses tumor vasculature at the "macroscopic" level, calculating the numbers and shapes of the larger vessels discriminable by magnetic resonance angiography. This paper provides an overview of magnetic resonance (MR) vascular imaging at both the microscopic (dynamic MR perfusion and permeability) and macroscopic (MR angiographic) levels. The two approaches provide different, complementary information and together could provide important insights into cancer growth as well as new methods of assessing malignancy and tumor treatment response.

Tumor therapeutic response and vessel tortuosity: preliminary report in metastatic breast cancer

No current non-invasive method is capable of assessing the efficacy of brain tumor therapy early during treatment. We outline an approach that evaluates tumor activity via statistical analysis of vessel shape using vessels segmented from MRA. This report is the first to describe the changes in vessel shape that occur during treatment of metastatic brain tumors as assessed by sequential MRA. In this preliminary study of 16 patients undergoing treatment for metastatic breast cancer we conclude that vessel shape may predict tumor response several months in advance of traditional methods.

Malignancy-associated vessel tortuosity: a computer-assisted, MR angiographic study of choroid plexus carcinoma in genetically engineered mice

BACKGROUND AND PURPOSE

The ability to assess tumor malignancy and monitor treatment response noninvasively would be of value to both clinicians and animal investigators. This report describes the MR imaging characteristics of a genetically engineered mouse model of choroid plexus carcinoma (CPC) during tumor growth and progression to malignancy. We assess the ability of vessel tortuosity measurements, as calculated from high-resolution MR angiographic (MRA) images, to detect emerging CPC cancers.

METHODS

MR images of 9 healthy mice and of 20 CPC mice with precancerous choroid dysplasia or with cancer over a wide range of sizes were analyzed. Two vessel tortuosity measures and a measure of vessel attenuation (vessel count) were calculated from MRA images. Malignancy assessment was based upon a statistical analysis of vessel tortuosity, by using an equation derived from an earlier study of human brain tumor patients.

RESULTS

Choroid dysplasia was correctly judged nonmalignant. On the basis of vessel count, neoangiogenesis could not be detected until cancers were full-blown and had reached a volume of approximately 80 mm3. Vessel tortuosity measurements, however, correctly identified emerging malignancy in lesions larger than 0.3 mm3.

CONCLUSION

To the best of our knowledge, this report provides the first description of in vivo, MR imaging characteristics of genetically engineered CPC mice during the progression from dysplasia to cancer. Vessel tortuosity measurements offer promise of correctly defining even tiny tumors as malignant.

Vessel tortuosity and brain tumor malignancy: a blinded study

RATIONALE AND OBJECTIVES

Malignancy provokes regional changes to vessel shape. Characteristic vessel tortuosity abnormalities appear early during tumor development, affect initially healthy vessels, spread beyond the confines of tumor margins, and do not simply mirror tissue perfusion. The ability to detect and quantify tortuosity abnormalities on high-resolution magnetic resonance angiography (MRA) images offers a new approach to the noninvasive diagnosis of malignancy. This report evaluates a computerized, statistical method of analyzing the shapes of vessels extracted from MRA in diagnosing cancer.

MATERIALS AND METHODS

The regional vasculature of 34 healthy subjects was compared with the tumor-associated vasculature of 30 brain tumors before surgical resection. The operator performing the analysis was blinded to the diagnosis. Vessels were segmented from an MRA of each subject, a region of interest was defined in each tumor patient and was mapped to all healthy controls, and a statistical analysis of vessel shape measures was then performed over the region of interest. Many difficult cases were included, such as pinpoint, hemorrhagic, and irradiated tumors, as were hypervascular benign tumors. Tumors were identified as benign or malignant on the basis of histological evaluation.

RESULTS

A discriminant analysis performed at the study's conclusion successfully classified all but one of the 30 tumors as benign or malignant on the basis of vessel tortuosity.

CONCLUSIONS

Quantitative, statistical measures of vessel shape offer a new approach to the diagnosis and staging of disease. Although the methods developed under the current report must be tested against a new series of cases, initial results are promising.