Quantitative Analysis of Diffusion Weighted MR Images of Intracerebral Haemorrhage by Signal Intensity Gradient Technique

Supriya S. Shanbhag; Gururaj R. Udupi; K. Mothiram Patil; Krishnaswamy Ranganath

doi:doi:10.11648/j.ijmi.20130101.13

| Peer-Reviewed

Quantitative Analysis of Diffusion Weighted MR Images of Intracerebral Haemorrhage by Signal Intensity Gradient Technique

Supriya S. Shanbhag, Gururaj R. Udupi, K. Mothiram Patil, Krishnaswamy Ranganath

Published in International Journal of Medical Imaging (Volume 1, Issue 1)

Received: 28 July 2013 Published: 20 August 2013

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

Abstract

Intracerebral Haemorrhage (ICH) is an important public health problem leading to high rates of death and disability in adults. Early and reliable identification of the stage of ICH is vital when choosing the proper treatment and estimating patient’s diagnosis and outcome. Diffusion Weighted - Magnetic Resonance Imaging (DW-MRI) presents a variation in the image signal intensity characteristics relative to the different stages of ICH and thus an increased understanding of the progression of the signal intensity variations on Diffusion Weighted (DW) images, subsequent to the onset of ICH, is valuable. In the present paper an effort was made to quantify the variations in the signal intensity characteristics on DW images, at evolving stages of ICH, for 32 subjects, by means of Signal Intensity Gradient (SIG) imaging metric. The relative increase in the SIG values (RSIG) for the subjects with ICH was in the range of (3.83 – 35.67) times compared to their corresponding SIG values on the contralateral normal side. The observed RSIG values were elevated in Stage 1 (Hyperacute: <1 day) and further progressively decreased in Stage 2 (Acute: 1 - 7 days) and Stage 3 (Late subacute: 7 - 14 days), and eventually reached their minimum in Stage 4 (Chronic: >14 days) of ICH. Also a negative correlation (r = − 0.97) was observed between the RSIG values and the evolving stages of ICH. Therefore, the progression of the RSIG values could be supportive in understanding the developmental stages of ICH, and further be helpful in predicting the ICH stage and providing treatment at the appropriate time.

Published in	International Journal of Medical Imaging (Volume 1, Issue 1)
DOI	10.11648/j.ijmi.20130101.13
Page(s)	12-18
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2013. Published by Science Publishing Group

Keywords

Diffusion Weighted Images, Intracerebral Haemorrhage, Magnetic Resonance Imaging, Signal Intensity Gradient

References

[1]	C. Counsell, S. Boonyakarnkul, M. Dennis, P. Sandercock, J. Bamford, J. Burn, C. Warlow, "Primary intracerebral haemorrhage in the Oxfordshire community stroke project," Cerebrovascular Diseases, vol. 5, no. 1, pp. 26-34, 1995.
[2]	A. I. Qureshi, Y. M. Mohammad, A. M. Yahia, J. I. Suarez, A. M. Siddiqui, J. F. Kirmani, M. F. Suri, J. Kolb, O. O. Zaidat, "A prospective multicenter study to evaluate the feasibility and safety of aggressive antihypertensive treatment in patients with acute intracerebral hemorrhage," Journal of Intensive Care Medicine, vol. 20, no. 1, pp. 34-42, Jan.-Feb. 2005.
[3]	J. P. Broderick, H. P. Adams Jr, W. Barsan, W. Feinberg, E. Feldmann, J. Grotta, C. Kase, D. Krieger, M. Mayberg, B. Tilley, J. M. Zabramski, M. Zuccarello, " Guidelines for the management of spontaneous intracerebral hemorrhage. A statement for healthcare professionals from a special writing group of the stroke council. American Heart Association," Stroke, vol. 30, no. 4, pp. 905-915, Apr. 1999.
[4]	C. S. Kidwell, J. L. Saver, J. P. Villablanca, G. Duckwiler, A. Fredieu, K. Gough, M. C. Leary, S. Starkman, Y. P. Gobin, R. Jahan, P. Vespa, D. S. Liebeskind, J. R. Alger, F. Vinuela, "Magnetic resonance imaging detection of microbleeds before thrombolysis: an emerging application," Stroke, vol. 33, no. 1, pp. 95-98, Jan. 2002.
[5]	N. Nighoghossian, M. Hermier, P. Adeleine, K. Blanc-Lasserre, L. Derex, J. Honnorat, F. Philippeau, J.F. Dugor, J. C. Froment, P. Trouillas, "Old microbleeds are a potential risk factor for cerebral bleeding after ischemic stroke : a gradient-echo T2*-weighted brain MRI study," Stroke, vol. 33, no. 3, pp. 735-742, Mar. 2002.
[6]	R. von Kummer, "MRI: The new gold standard for detecting brain hemorrhage?," Stroke, vol. 33, no. 7, pp. 1748-1749, Jul. 2002.
[7]	B. K. Kang, D. G. Na, J. W. Ryoo, H. S. Byun, H. G. Roh, Y. S. Pyeun, "Diffusion-weighted MR imaging of intracerebral haemorrhage," Korean Journal of Radiology, vol. 2, no. 4, pp. 183-191, Oct.-Dec. 2001.
[8]	J. M. Gomori, R. I. Grossman, H. I. Goldberg, R. A. Zimmerman, L. T. Bilaniuk, "Intracranial hematomas: imaging by high-field MR," Radiology, vol. 157, no. 1, pp. 87-93, Oct. 1985.
[9]	W. G. Bradley, "MR appearance of hemorrhage in the brain," Radiology, vol. 189, no. 1, pp. 15-26, Oct. 1993.
[10]	S. W. Atlas, P. DuBois, M. B. Singer, D. Lu, "Diffusion measurements in intracranial hematomas: implications for MR imaging of acute stroke," American Journal of Neuroradiology, vol. 21, no. 7, pp. 1190-1194, Aug. 2000.
[11]	T. Ebisu, C. Tanaka, M. Umeda, M. Kitamura, M. Fukunaga, I. Aoki, H. Sato, T. Higuchi, S. Naruse, Y. Horikawa, S. Ueda, "Hemorrhagic and nonhemorrhagic stroke: diagnosis with diffusion-weighted and T2-weighted echo-planar MR imaging," Radiology, vol. 203, no. 3, pp. 823-828, Jun. 1997.
[12]	P. D. Schellinger, O. Jansen, J. B. Fiebach, W. Hacke, K. Sartor, "A standardized MRI stroke protocol: comparison with CT in hyperacute intracerebral hemorrhage," Stroke, vol. 30, no. 4, pp. 765-768, Apr. 1999.
[13]	S. Felber, A. Auer, C. Wolf, M. Schocke, S. Golaszewski, B. Amort, D. zurNedden, "MRI characteristics of spontaneous intracerebral hemorrhage," Radiologe, vol. 39, no. 10, pp. 838-846, Oct. 1999.
[14]	M. Wiesmann, T. E. Mayer, I. Yousry, G. F. Hamann, H. Bruckmann, "Detection of hyperacute parenchymal hemorrhage of the brain using echo-planar T2*-weighted and diffusion-weighted MRI," European Radiology, vol. 11, no. 5, pp. 849-853, 2001.
[15]	J. R. Carhuapoma, P. Y. Wang, N. J. Beauchamp, P. M. Keyl, D. F. Hanley, P. B. Barker, "Diffusion-weighted MRI and proton MR spectroscopic imaging in the study of secondary neuronal injury after intracerebral hemorrhage," Stroke, vol. 31, no. 3, pp. 726-732, Mar. 2000.
[16]	S. Attia, G. Mohamed, El Khatib, M. Bilal, H. Nassar, "Spontaneous intracerebral hematoma in young people: clinical and radiological magnetic resonance imaging features by diffusion-weighted images," Egyptian Journal of Neurology, Psychiatry and Neurosurgery, vol. 44, no. 2, Jul. 2007.
[17]	T. Hideichi, K. Masahito, S. Sadao, S. Fumiko, M. Ban, "Cerebral haemorrhage. Serial study using diffusion-weighted MRI," Japanese Journal of Stroke, vol. 21, no. 2, pp. 245-252, 1999.
[18]	S. Silvera, C. Oppenheim, E. Touzé, D. Ducreux, P. Page, V. Domigo, J. L. Mas, F. X. Roux, D. Frédy, J. F. Meder, "Spontaneous intracerebral hematoma on diffusion-weighted images: influence of T2-shine through and T2-blackout effects," American Journal of Neuroradiology, vol. 26, no. 2, pp. 236-241, Feb. 2005.
[19]	T. W. Stadnik, P. Demaerel, R. R. Luypaert, C. Chaskis, K. L. Van Rompaey, A. Michotte, M. J. Osteaux, "Imaging tutorial: differential diagnosis of bright lesions on diffusion-weighted MR images," Radiographic, vol. 23, no. 1, Jan. 2003.
[20]	J. A. Maldjian, J. Listerud, G. Moonis, F. Siddiqi, "Computing diffusion rates in T2-dark hematomas and areas of low T2 signal," American Journal of Neuroradiology, vol. 22, no. 1, pp. 112-118, Jan. 2001.
[21]	I. Linfante, R. H. Llinas, L. R. Caplan, S. Warach, "MRI features of intracerebral hemorrhage within 2 hours from symptom onset," Stroke, vol. 30, no. 11, pp. 2263-2267, Nov. 1999.
[22]	J. A. Chalela, C. S. Kidwell, L. M. Nentwich, M. Luby, J. A. Butman, A. M. Demchuk, M. D. Hill, N. Patronas, L. Latour, S. Warach, "Magnetic resonance imaging and computed tomography in emergency assessment of patients with suspected acute stroke: a prospective comparison," The Lancet, vol. 369, no. 9558, pp. 293-298, Jan. 2007.
[23]	D. Chien, R. B. Buxton, K. K. Kwong, T. J. Brady, B. R. Rosen, "MR diffusion imaging of the human brain," Journal of Computer Assisted Tomography, vol. 14, no. 4, pp. 514-520, Jul.1990.
[24]	J. W. van der Veen, P. van Gelderen, J. H. Creyghton, W. M. Bovee, "Diffusion in red blood cell suspensions: separation of the intracellular and extracellular NMR sodium signal," Magnetic Resonance in Medicine, vol. 29, no. 4, pp. 571-574, Apr. 1993.
[25]	R. C. Gonzalez and P. Wintz, Image transforms in ‘Digital Image Processing’. 2nd edition, Addison-Wesley, U.S.A, 1987.
[26]	K. G. Prabhu, K. M. Patil, S. Srinivasan, "Diabetic feet at risk: a new method of analysis of walking foot pressure images at different levels of neuropathy for early detection of plantar ulcers," Medical and Biological Engineering and Computing, vol. 39, no. 3, pp. 288-293, 2001.
[27]	K. C. Sudeep, J. A. Majumdar, "Novel architecture for real time implementation of edge detectors on FPGA," International Journal of Computer Science Issues, vol. 8, no. 1, pp. 193-202, Jan. 2011.
[28]	S. C. Gupta, V. K. Kapoor, Fundamentals of mathematical statistics. 11th edition, Sultan Chand and Sons, New Delhi, India, 1982.

Cite This Article

Plain Text BibTeX RIS

APA Style

Supriya S. Shanbhag, Gururaj R. Udupi, K. Mothiram Patil, Krishnaswamy Ranganath. (2013). Quantitative Analysis of Diffusion Weighted MR Images of Intracerebral Haemorrhage by Signal Intensity Gradient Technique. International Journal of Medical Imaging, 1(1), 12-18. https://doi.org/10.11648/j.ijmi.20130101.13

Copy | Download

ACS Style

Supriya S. Shanbhag; Gururaj R. Udupi; K. Mothiram Patil; Krishnaswamy Ranganath. Quantitative Analysis of Diffusion Weighted MR Images of Intracerebral Haemorrhage by Signal Intensity Gradient Technique. Int. J. Med. Imaging 2013, 1(1), 12-18. doi: 10.11648/j.ijmi.20130101.13

Copy | Download

AMA Style

Supriya S. Shanbhag, Gururaj R. Udupi, K. Mothiram Patil, Krishnaswamy Ranganath. Quantitative Analysis of Diffusion Weighted MR Images of Intracerebral Haemorrhage by Signal Intensity Gradient Technique. Int J Med Imaging. 2013;1(1):12-18. doi: 10.11648/j.ijmi.20130101.13

Copy | Download

@article{10.11648/j.ijmi.20130101.13,
  author = {Supriya S. Shanbhag and Gururaj R. Udupi and K. Mothiram Patil and Krishnaswamy Ranganath},
  title = {Quantitative Analysis of Diffusion Weighted MR Images of Intracerebral Haemorrhage by Signal Intensity Gradient Technique},
  journal = {International Journal of Medical Imaging},
  volume = {1},
  number = {1},
  pages = {12-18},
  doi = {10.11648/j.ijmi.20130101.13},
  url = {https://doi.org/10.11648/j.ijmi.20130101.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijmi.20130101.13},
  abstract = {Intracerebral Haemorrhage (ICH) is an important public health problem leading to high rates of death and disability in adults. Early and reliable identification of the stage of ICH is vital when choosing the proper treatment and estimating patient’s diagnosis and outcome. Diffusion Weighted - Magnetic Resonance Imaging (DW-MRI) presents a variation in the image signal intensity characteristics relative to the different stages of ICH and thus an increased understanding of the progression of the signal intensity variations on Diffusion Weighted (DW) images, subsequent to the onset of ICH, is valuable. In the present paper an effort was made to quantify the variations in the signal intensity characteristics on DW images, at evolving stages of ICH, for 32 subjects, by means of Signal Intensity Gradient (SIG) imaging metric. The relative increase in the SIG values (RSIG) for the subjects with ICH was in the range of (3.83 – 35.67) times compared to their corresponding SIG values on the contralateral normal side. The observed RSIG values were elevated in Stage 1 (Hyperacute: 14 days) of ICH. Also a negative correlation (r = − 0.97) was observed between the RSIG values and the evolving stages of ICH. Therefore, the progression of the RSIG values could be supportive in understanding the developmental stages of ICH, and further be helpful in predicting the ICH stage and providing treatment at the appropriate time.},
 year = {2013}
}

Copy | Download

TY - JOUR
T1 - Quantitative Analysis of Diffusion Weighted MR Images of Intracerebral Haemorrhage by Signal Intensity Gradient Technique
AU - Supriya S. Shanbhag
AU - Gururaj R. Udupi
AU - K. Mothiram Patil
AU - Krishnaswamy Ranganath
Y1 - 2013/08/20
PY - 2013
N1 - https://doi.org/10.11648/j.ijmi.20130101.13
DO - 10.11648/j.ijmi.20130101.13
T2 - International Journal of Medical Imaging
JF - International Journal of Medical Imaging
JO - International Journal of Medical Imaging
SP - 12
EP - 18
PB - Science Publishing Group
SN - 2330-832X
UR - https://doi.org/10.11648/j.ijmi.20130101.13
AB - Intracerebral Haemorrhage (ICH) is an important public health problem leading to high rates of death and disability in adults. Early and reliable identification of the stage of ICH is vital when choosing the proper treatment and estimating patient’s diagnosis and outcome. Diffusion Weighted - Magnetic Resonance Imaging (DW-MRI) presents a variation in the image signal intensity characteristics relative to the different stages of ICH and thus an increased understanding of the progression of the signal intensity variations on Diffusion Weighted (DW) images, subsequent to the onset of ICH, is valuable. In the present paper an effort was made to quantify the variations in the signal intensity characteristics on DW images, at evolving stages of ICH, for 32 subjects, by means of Signal Intensity Gradient (SIG) imaging metric. The relative increase in the SIG values (RSIG) for the subjects with ICH was in the range of (3.83 – 35.67) times compared to their corresponding SIG values on the contralateral normal side. The observed RSIG values were elevated in Stage 1 (Hyperacute: 14 days) of ICH. Also a negative correlation (r = − 0.97) was observed between the RSIG values and the evolving stages of ICH. Therefore, the progression of the RSIG values could be supportive in understanding the developmental stages of ICH, and further be helpful in predicting the ICH stage and providing treatment at the appropriate time.
VL - 1
IS - 1
ER -

Copy | Download

Author Information

Supriya S. Shanbhag

Department of Electronics and Communication Engineering, Gogte Institute of Technology, Belgaum, Karnataka, India
Gururaj R. Udupi

Vishwanathrao Deshpande Rural Institute of Technology, Haliyal, Karnataka, India
K. Mothiram Patil

Retired, Indian Institute of Technology (Madras), Belgaum, Karnataka, India
Krishnaswamy Ranganath

RAGAVS Diagnostics and Research Center Pvt. Ltd., Bangalore, Karnataka, India

Download PDF

Sections

Plain Text BibTeX RIS

APA Style

Supriya S. Shanbhag, Gururaj R. Udupi, K. Mothiram Patil, Krishnaswamy Ranganath. (2013). Quantitative Analysis of Diffusion Weighted MR Images of Intracerebral Haemorrhage by Signal Intensity Gradient Technique. International Journal of Medical Imaging, 1(1), 12-18. https://doi.org/10.11648/j.ijmi.20130101.13

Copy | Download

ACS Style

Supriya S. Shanbhag; Gururaj R. Udupi; K. Mothiram Patil; Krishnaswamy Ranganath. Quantitative Analysis of Diffusion Weighted MR Images of Intracerebral Haemorrhage by Signal Intensity Gradient Technique. Int. J. Med. Imaging 2013, 1(1), 12-18. doi: 10.11648/j.ijmi.20130101.13

Copy | Download

AMA Style

Supriya S. Shanbhag, Gururaj R. Udupi, K. Mothiram Patil, Krishnaswamy Ranganath. Quantitative Analysis of Diffusion Weighted MR Images of Intracerebral Haemorrhage by Signal Intensity Gradient Technique. Int J Med Imaging. 2013;1(1):12-18. doi: 10.11648/j.ijmi.20130101.13

Copy | Download

@article{10.11648/j.ijmi.20130101.13,
  author = {Supriya S. Shanbhag and Gururaj R. Udupi and K. Mothiram Patil and Krishnaswamy Ranganath},
  title = {Quantitative Analysis of Diffusion Weighted MR Images of Intracerebral Haemorrhage by Signal Intensity Gradient Technique},
  journal = {International Journal of Medical Imaging},
  volume = {1},
  number = {1},
  pages = {12-18},
  doi = {10.11648/j.ijmi.20130101.13},
  url = {https://doi.org/10.11648/j.ijmi.20130101.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijmi.20130101.13},
  abstract = {Intracerebral Haemorrhage (ICH) is an important public health problem leading to high rates of death and disability in adults. Early and reliable identification of the stage of ICH is vital when choosing the proper treatment and estimating patient’s diagnosis and outcome. Diffusion Weighted - Magnetic Resonance Imaging (DW-MRI) presents a variation in the image signal intensity characteristics relative to the different stages of ICH and thus an increased understanding of the progression of the signal intensity variations on Diffusion Weighted (DW) images, subsequent to the onset of ICH, is valuable. In the present paper an effort was made to quantify the variations in the signal intensity characteristics on DW images, at evolving stages of ICH, for 32 subjects, by means of Signal Intensity Gradient (SIG) imaging metric. The relative increase in the SIG values (RSIG) for the subjects with ICH was in the range of (3.83 – 35.67) times compared to their corresponding SIG values on the contralateral normal side. The observed RSIG values were elevated in Stage 1 (Hyperacute: 14 days) of ICH. Also a negative correlation (r = − 0.97) was observed between the RSIG values and the evolving stages of ICH. Therefore, the progression of the RSIG values could be supportive in understanding the developmental stages of ICH, and further be helpful in predicting the ICH stage and providing treatment at the appropriate time.},
 year = {2013}
}

Copy | Download