Fractal Analysis of Elastographic Images for Automatic Detection of Diffuse Diseases of Salivary Glands: Preliminary Results

The geometry of some medical images of tissues, obtained by elastography and ultrasonography, is characterized in terms of complexity parameters such as the fractal dimension (FD). It is well known that in any image there are very subtle details that are not easily detectable by the human eye. However, in many cases like medical imaging diagnosis, these details are very important since they might contain some hidden information about the possible existence of certain pathological lesions like tissue degeneration, inflammation, or tumors. Therefore, an automatic method of analysis could be an expedient tool for physicians to give a faultless diagnosis. The fractal analysis is of great importance in relation to a quantitative evaluation of “real-time” elastography, a procedure considered to be operator dependent in the current clinical practice. Mathematical analysis reveals significant discrepancies among normal and pathological image patterns. The main objective of our work is to demonstrate the clinical utility of this procedure on an ultrasound image corresponding to a submandibular diffuse pathology.

[1]  F. Pansera Fractals and cancer. , 1994, Medical hypotheses.

[2]  M F Neurath,et al.  An abdominal and thyroid status with Acoustic Radiation Force Impulse Elastometry--a feasibility study: Acoustic Radiation Force Impulse Elastometry of human organs. , 2011, European journal of radiology.

[3]  Roger W Nightingale,et al.  An Integrated Indenter-ARFI Imaging System for Tissue Stiffness Quantification , 2008, Ultrasonic imaging.

[4]  Tudorel Ciurea,et al.  Hue histogram analysis of real-time elastography images for noninvasive assessment of liver fibrosis. , 2007, AJR. American journal of roentgenology.

[5]  G. Nunnari,et al.  Acoustic Radial Force Impulse as an effective tool for a prompt and reliable diagnosis of hepatocellular carcinoma - preliminary data. , 2012, European review for medical and pharmacological sciences.

[6]  R. Nelson,et al.  Acoustic radiation force impulse imaging of the abdomen: demonstration of feasibility and utility. , 2005, Ultrasound in medicine & biology.

[7]  Konradin Metze,et al.  Robust variables in texture analysis. , 2010, Pathology.

[8]  Richard F. Voss,et al.  LONG-RANGE FRACTAL CORRELATIONS IN DNA INTRONS AND EXONS , 1994 .

[9]  Igor Pantic,et al.  Changes in fractal dimension and lacunarity as early markers of UV-induced apoptosis. , 2012, Journal of theoretical biology.

[10]  V. Anh,et al.  Fractals in DNA Sequence Analysis , 2002 .

[11]  J. Lindebjerg,et al.  Ultrasound elastography in patients with rectal cancer treated with chemoradiation. , 2013, European journal of radiology.

[12]  Ming Li Fractal Time Series—A Tutorial Review , 2010 .

[13]  Panagiotis Samaras,et al.  Real-time elastography for noninvasive assessment of liver fibrosis in chronic viral hepatitis. , 2007, AJR. American journal of roentgenology.

[14]  Shigehiko Kanaya,et al.  Statistical Analysis of Genomic Information , 2000 .

[15]  Hongtu Zhu,et al.  ARFI imaging for noninvasive material characterization of atherosclerosis. Part II: toward in vivo characterization. , 2009, Ultrasound in medicine & biology.

[16]  Douglas Dumont,et al.  ARFI imaging for noninvasive material characterization of atherosclerosis. , 2006, Ultrasound in medicine & biology.

[17]  R. Voss,et al.  Evolution of long-range fractal correlations and 1/f noise in DNA base sequences. , 1992, Physical review letters.

[18]  Radu Dobrescu,et al.  Morphometrical differences between resectable and non-resectable pancreatic cancer: a fractal analysis. , 2011, Hepato-gastroenterology.

[19]  H. Stanley,et al.  Analysis of DNA sequences using methods of statistical physics , 1998 .

[20]  D. Sornette,et al.  The US Stock Market Leads the Federal Funds Rate and Treasury Bond Yields , 2011, PloS one.

[21]  Yongmin Kim,et al.  Efficacy of thyroid ultrasound elastography in differential diagnosis of small thyroid nodules. , 2013, European journal of radiology.

[22]  C. A. Chatzidimitriou-Dreismann,et al.  Long-range correlations in DNA , 1993, Nature.

[23]  Ming Li,et al.  Quantitatively investigating the locally weak stationarity of modified multifractional Gaussian noise , 2012 .

[24]  Gaetano Pierro,et al.  Sequence Complexity of Chromosome 3 in Caenorhabditis elegans , 2012, Adv. Bioinformatics.

[25]  Fabio Grizzi,et al.  Impact of Real-Time Elastography versus Systematic Prostate Biopsy Method on Cancer Detection Rate in Men with a Serum Prostate-Specific Antigen between 2.5 and 10 ng/mL , 2013, ISRN oncology.

[26]  Carlo Cattani,et al.  Fractals and Hidden Symmetries in DNA , 2010 .

[27]  Le-Hang Guo,et al.  Virtual Touch Tissue Quantification of Acoustic Radiation Force Impulse: A New Ultrasound Elastic Imaging in the Diagnosis of Thyroid Nodules , 2012, PloS one.

[28]  Radu Badea,et al.  Performance of a new elastographic method (ARFI technology) compared to unidimensional transient elastography in the noninvasive assessment of chronic hepatitis C. Preliminary results. , 2009, Journal of gastrointestinal and liver diseases : JGLD.

[29]  Alessandro Giuliani,et al.  Metabolism and cell shape in cancer: a fractal analysis. , 2011, The international journal of biochemistry & cell biology.

[30]  Pranab Dey,et al.  Fractal dimension of chromatin texture of squamous intraepithelial lesions of cervix , 2012, Diagnostic cytopathology.

[31]  S S Cross,et al.  FRACTALS IN PATHOLOGY , 1997, The Journal of pathology.

[32]  Benoit B. Mandelbrot,et al.  Fractal Geometry of Nature , 1984 .

[33]  Konradin Metze,et al.  Fractal dimension of chromatin is an independent prognostic factor for survival in melanoma , 2010, BMC Cancer.

[34]  Konradin Metze,et al.  Fractal Characteristics of May-Grünwald-Giemsa Stained Chromatin Are Independent Prognostic Factors for Survival in Multiple Myeloma , 2011, PloS one.

[35]  Gregg Trahey,et al.  Acoustic radiation force impulse imaging: in vivo demonstration of clinical feasibility. , 2002, Ultrasound in medicine & biology.

[36]  André Ricardo Backes,et al.  Segmentação de Texturas por Análise de Complexidade , 2006 .