Abnormal Vessel Tortuosity as a Marker of Treatment Response of Malignant Gliomas: Preliminary Report

Despite multiple advances in medical imaging, noninvasive monitoring of therapeutic efficacy for malignant gliomas remains problematic. An underutilized observation is that malignancy induces characteristic abnormalities of vessel shape. These characteristic shape abnormalities affect both capillaries and much larger vessels in the tumor vicinity, involve larger vessels prior to sprout formation, and are generally not present in hypervascular benign tumors. Vessel shape abnormalities associated with malignancy thus may appear independently of increase in vessel density. We hypothesize that an automated, computerized analysis of vessel shape as defined from high-resolution MRA can provide valuable information about tumor activity during the treatment of malignant gliomas. This report describes vessel shape properties in 10 malignant gliomas prior to treatment, in 2 patients in remission during treatment, and in 2 patients with recurrent disease. One subject was scanned multiple times. The method involves an automated, statistical analysis of vessel shape within a region of interest for each tumor, normalized by the values obtained from the vessels within the same region of interest of 34 healthy subjects. Results indicate that untreated tumors display statistically significant vessel tortuosity abnormalities. These abnormalities involve vessels not only within the tumor margins as defined from MR but also vessels in the surrounding tissue. The abnormalities resolve during effective treatment and recur with tumor recurrence. We conclude that vessel shape analysis could provide an important means of assessing tumor activity.

[1]  Glyn Johnson,et al.  Comparison of cerebral blood volume and vascular permeability from dynamic susceptibility contrast-enhanced perfusion MR imaging with glioma grade. , 2004, AJNR. American journal of neuroradiology.

[2]  J. Folkman,et al.  Incipient angiogenesis. , 2000, Journal of the National Cancer Institute.

[3]  Stephen R. Aylward,et al.  Symbolic description of intracerebral vessels segmented from magnetic resonance angiograms and evaluation by comparison with X-ray angiograms , 2001, Medical Image Anal..

[4]  Glyn Johnson,et al.  Glioma grading: sensitivity, specificity, and predictive values of perfusion MR imaging and proton MR spectroscopic imaging compared with conventional MR imaging. , 2003, AJNR. American journal of neuroradiology.

[5]  Guido Gerig,et al.  Automatic brain tumor segmentation by subject specific modification of atlas priors. , 2003, Academic radiology.

[6]  Dietmar W. Siemann Vascular targeting agents , 2002 .

[7]  B. Achinstein,et al.  Journal of the National Cancer Institute, Vol. 29, 1962: Action of bacterial polysaccharide on tumors. II. Damage of sarcoma 37 by serum of mice treated with Serratia marcescens polysaccharide, and induced tolerance. , 2009, Nutrition reviews.

[8]  Stephen R. Aylward,et al.  Tissue-Based Affine Registration of Brain Images to form a Vascular Density Atlas , 2003, MICCAI.

[9]  K. Muller,et al.  Symbolic Description of Intracerebral Vessels Segmented from MRA and Evaluation by Comparison with X-Ray Angiograms , 2000 .

[10]  W. E. Gye,et al.  CANCER RESEARCH , 1923, British medical journal.

[11]  Julien Jomier,et al.  Vascular Atlas Formation Using a Vessel-to-Image Affine Registration Method , 2003, MICCAI.

[12]  R. Anderson,et al.  Surgical Pathology of the Nervous System and Its Coverings , 1977 .

[13]  Julien Jomier,et al.  Registration and Analysis of Vascular Images , 2003, International Journal of Computer Vision.

[14]  Rakesh K. Jain,et al.  Normalizing tumor vasculature with anti-angiogenic therapy: A new paradigm for combination therapy , 2001, Nature Medicine.

[15]  Stephen R. Aylward,et al.  Initialization, noise, singularities, and scale in height ridge traversal for tubular object centerline extraction , 2002, IEEE Transactions on Medical Imaging.

[16]  M. Westphal,et al.  Local control of gliomas: the next best step--a good step? , 1999, Frontiers of radiation therapy and oncology.

[17]  Stephen R. Aylward,et al.  Analyzing attributes of vessel populations , 2005, Medical Image Anal..

[18]  Carl-Fredrik Westin,et al.  A method for the analysis of the geometrical relationship between white matter pathology and the vascular architecture of the brain , 2004, NeuroImage.

[19]  B. Scheithauer,et al.  Surgical Pathology of the Nervous System and its Coverings , 1976 .

[20]  C. H. Park,et al.  Vascular structure of glioblastomas. , 1969, The American journal of roentgenology, radium therapy, and nuclear medicine.

[21]  Roland Hustinx,et al.  Imaging gliomas with positron emission tomography and single-photon emission computed tomography. , 2003, Seminars in nuclear medicine.

[22]  J. Murray,et al.  Virtual and real brain tumors: using mathematical modeling to quantify glioma growth and invasion , 2003, Journal of the Neurological Sciences.

[23]  Guido Gerig,et al.  Vascular Attributes and Malignant Brain Tumors , 2003, MICCAI.

[24]  E. Sabo,et al.  Microscopic analysis and significance of vascular architectural complexity in renal cell carcinoma. , 2001, Clinical cancer research : an official journal of the American Association for Cancer Research.

[25]  Haiying Liu,et al.  A Generic Framework for Non-rigid Registration Based on Non-uniform Multi-level Free-Form Deformations , 2001, MICCAI.

[26]  Guido Gerig,et al.  Robust Estimation for Brain Tumor Segmentation , 2003, MICCAI.

[27]  L. Xue,et al.  Paclitaxel (Taxol): an inhibitor of angiogenesis in a highly vascularized transgenic breast cancer. , 1999, Cancer biotherapy & radiopharmaceuticals.

[28]  Julien Jomier,et al.  Rigid and Deformable Vasculature-to-Image Registration: A Hierarchical Approach , 2004, MICCAI.

[29]  Guido Gerig,et al.  Determining Malignancy of Brain Tumors by Analysis of Vessel Shape , 2004, MICCAI.

[30]  S. Pizer,et al.  Measuring tortuosity of the intracerebral vasculature from MRA images , 2003, IEEE Transactions on Medical Imaging.

[31]  J W Baish,et al.  Fractals and cancer. , 2000, Cancer research.

[32]  Marc Dellian,et al.  Acid production in glycolysis-impaired tumors provides new insights into tumor metabolism. , 2002, Clinical cancer research : an official journal of the American Association for Cancer Research.

[33]  M. Dewhirst,et al.  Initial stages of tumor cell-induced angiogenesis: evaluation via skin window chambers in rodent models. , 2000, Journal of the National Cancer Institute.