A Method for Tumor Characterization from Nuclear Magnetic Resonance Spectroscopic Data Using Wavelets
Purpose
The aim of this research is to study the potential of a wavelet-based method for the analysis of nuclear magnetic Resonance Spectroscopic (MRS) signals obtained from patients with tumors.
The Problem of Tumor Characterization Using Current Methodology
There are two basic questions which must be answered once a tumor is found:
- Is the tumor benign or malignant?
- Can it be categorized?
Clearly, an accurate and timely answer to these questions is crucial. If the tumor is on the surface of the human body, its diagnosis is easier.
However, for interior tumors the situation is more difficult. The first step is to detect the tumor via X-ray, CAT or MRI examination. If the tumors are large, and have distinct geometrical boundaries, then the trained radiologist can draw some conclusions. However, if the tumors are small and not clearly visible, and are subject to psychophysical perception interpretations, a sure diagnosis is difficult. Furthermore, no biochemical analysis is possible from such examinations.
Unfortunately, in almost all cases, the patient goes through the procedure of biopsy. Biopsy is an invasive surgical technique, which will provide the most reliable biochemical composition of the tumor. There are two kinds of biopsies. The first one is a biopsy involving surgery and the second is known as needle aspiration. Both kinds will create trauma and bleeding. Note that bleeding, in the case of a malignant tumor can be risky in the sense that it may propagate cancerous cells in other parts of the body, and could also favor the creation of blood clots. In the case of the surgical biopsy the samples are usually large and provide adequate data for an accurate biochemical analysis, but this is not true in the case of needle aspiration. In the needle aspiration case the samples are usually small and in many cases inadequate for an accurate and reliable diagnosis. Furthermore, due to the tumor’s location, the degrees of freedom of getting the desired sample are limited. Therefore, the need for a better method is clear.
Basics of Magnetic Resonance Spectroscopy 1
MRS has been used by chemists for many years for the analysis of chemical compounds.
A chemical compound consists of molecules, and molecules are composite systems of atoms. An atom consists of a small nucleus and a cloud of electrons. The nucleus is made up from two types of subatomic particles, the protons (p), and the neutrons (n). According to quantum mechanics these subatomic particles are intrinsically spinning. When a number of these particles (p, n) are grouped together to form nucleus, their respective spins will add and the nucleus will have a net nuclear spin. The net nuclear spin is zero for all the nuclei except those with an odd number of protons and an even number of neutrons (and vice versa). These are the nuclei of importance to nuclear magnetic resonance (NMR). As the nuclei spin, their charges circulate and generate a magnetic field. Such magnetic nuclei, which have north and south magnetic poles, have no preferred orientation in space. But if we put them in a uniform static magnetic field, Η they tend to line up with the field (favorable state). The next thing we do is to change the orientation of the nuclei (perturb the nuclei) in the field (turn them over to make them point the other way). To achieve this (less favorable) state we have to apply energy into the system. This energy can be obtained from the application of a precisely tuned pulsed radio frequency (RF) field which is generated from a radio transmitter by changing its frequency. This field is orthogonal to the static field H. When the RF of the transmitter becomes equal to the frequency of the spinning nucleus then we achieve resonance and the RF at which resonance occurs is known as resonance or Larmor frequency ω. The equation
ω= –γΗ
is the key equation in NM / MRS, where Η is the magnetic field strength ,and γ is the gyromagnetic ratio (which is associated with each nuclei).
In MRS experiments, it has been observed that high resolution spectral analysis requires relatively low molecular weight compounds(otherwise the spectra become too complex), very pure homogeneous samples, and extremely homogeneous magnetic fields of high strengths (4 Tesla or more).
In MRS studies of humans we wish to determine accurately, the chemical composition of a specific region in the human body containing the tumor under study In general, these regions are tissues comprised of very complex molecules, are highly non-homogeneous, and contain high levels of water and fat as well as small amounts of metabolites (which have been reported to be useful in tumor characterization). Furthermore, the high intensity signals from water and fats severely interfere with the observation of the weak signals from low molecular weight metabolites.
For example, the tissue -water signals is typically four orders of magnitude more intense than that of the metabolites, making it difficult to observe the weak metabolite signals in the present of the intense water signal.
Clearly, the above imposed limitations by the biological systems require strong magnetic fields (i.e. 3 Tesla or more).
1 A bit simpler description of the proposed process : When MRS is used the patient is placed inside an homogeneous magnetic field. This field causes the spins of protons to align in a specific direction, designated the longitudinal direction. A short RF pulse transverse to this field is then used to synchronize the precession of these proton spins. When this pulse ends, the spins revert back to their original state, emitting radio signals in the process. The exact signal a proton emits depends on the specific chemical environment of the proton; nuclei in different environments emit radio signals at different frequencies. These signals are combined to form a free induction decay which is then analyzed through FFT. By examining the spectra in frequency space, it is possible to determine the concentrations of certain chemicals and metabolites in a given sample. This makes spectroscopy an extremely powerful diagnostic tool. Furthermore, because the fields used function at radio frequency, magnetic spectroscopy examinations are also extremely safe.
Proposition
In this study, the analysis of FID signals is done using a powerful mathematical tool known as WAVELETS. Wavelets will provide high resolution spectra containing not only the chemical markers obtained from the currently used Fourier analysis, but also a host of other potential chemical markers that need to be identified. These new markers could be useful for diagnosis purposes and for the evaluation of medical treatments as well. However, such study can be clinically useful only if proper tumor calibration is done first.
Note: From 1995 until now, Dr. Nick Panagiotacopulos (Dr. P.) has developed a software system which is doing exactly what we discussed earlier. Initially, the purpose of the system was to analyze FID signals related to cancer, but the system can be used also for the analysis of other medical signals such as electromyograms, electrocardiograms, encephalograms, and cases involving Parkinson, Alzheimer’s and dementia. For example, measure dopamine levels in the brain.
Dr. P. is donating this system to FKW, and he is inviting medical research groups from anywhere in the world, to collaborate with him in the tumor calibration aspects of the study and subsequently in the FID signal analysis.
Significance
The wavelet approach it can be (for certain cases) an alternative to biopsy, and is suitable for the biochemical analysis of tumors. Furthermore, the method is non-invasive (non-surgical) and therefore convenient, safe, fast, cheap and it will provide reliable (accurate, and reproducible) results.
References
ON THE APPLICATION OF WAVELETS TO MEDICAL SIGNAL ANALYSIS (EMG, and FID)
“Time-Frequency evaluation of surface EMG signals”.
Pope MH, Aleksiev A, Panagiotacopulos ND, Wilder DG, Friesen K, Stielau W.
Proceedings of the ISSLS (Second International Society for the Study of the Lumbar Spine), Burlington, Vermont, June 25-29, 1996.
“Detection of wire EMG activity in whiplash injuries using Wavelets”.
N. D. Panagiotacopulos, J.C. Lee, M.H. Pope, M.L.Magnusson, K. Friesen, and W. Stielau
IOWA Orthopedic Journal, 1997, Vol.17, pp. 134-148.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2378100/
“Fatigue identification from low back Surface EMG signals using Wavelets”,
N. D. Panagioacopulos, J. C. Lee, M. H. Pope, D. G. Wilder, K. Friesen, W. Stielau
8th Annual Meeting of the European Spine Society, September 13-15, 1997, in Kos, Greece.
http://www.chaseergo.com/research_08.html
“Evaluation of EMG signals from rehabilitated patients with low back pain using Wavelets”. Nick D. Panagiotacopulos, Jae S. Lee, Malcolm H. Pope, Ken Friesen
Journal of Electromyography and Kinesiology, Special Issue: Vol. 8, Issue 4,
August 1998, pages 269-278.
http://www.sciencedirect.com/science/article/pii/S1050641198000133
“Entropy based fatigue identification in spinal surface Electromyo-graphy signals using Wavelets”. N. D. Panagiotacopulos, J. C. Lee, K. Friesen, L. Wan
Advances in Intelligent Systems: Concepts, Tools and Applications,Chapter 43,
pages 487-498, 1999. Kluwer Academic Publishers.
http://link.springer.com/chapter/10.1007/978-94-011-4840-5_43
“A new method for the analysis of EMG signals from rehabilitated patients with low back pain using Wavelets”.
Nick D. Panagiotacopulos, J. S. Lee, Ken Friesen, M. H. Pope
Proceedings of the Japanese Spine Society and North American Spine Society.
Kamuela, Big Island, Hawaii, pp.147-148, July 2000.
https://www.spine.org/Documents/EducationEvents/SAS2000Proceedings.pdf
“Wavelets, Nuclear Magnetic Resonance Spectroscopy, and Head Traumas”.
Shic Frederick, Lin Alexander, Ross Brian D, Shelden CH, Panagiotacopulos Nick D., Lertsuntivit Sukit, Sanidge Lee Ann
Advances in Physics, Electronics, and Signal Processing Applications (a series of reference books and textbooks in Mathematics,Computer Science, and Engineering), World Scientific Press, pp.297-302, July 2000. .
http://www.wseas.us/e-library/conferences/athens2000/Papers2000/403.pdf
“Wavelets, Nuclear Magnetic Resonance Spectroscopy, and the chemical composition of tumors-some interesting results”.
Panagiotacopulos Nick D., Lertsuntivit Sukit, Sanidge Lee Ann, Shic Frederick, Lin Alexander, Ross Brian D, Shelden CH
Advances in Physics, Electronics, and Signal Processing Applications (a series of reference books and textbooks in Mathematics, Computer Science, and Engineering).World Scientific Press, pp.290-296, July 2000.
http://www.wseas.us/e-library/conferences/athens2000/Papers2000/402.pdf
“Evaluation of low back muscle surface EMG signals using Wavelets”.
M. H. Pope, A. Aleksiev, N. D. Panagiotacopulos, J. C. Lee, D. G. Wilder,
K. Friesen, W. Stielau, V. K. Goel
Clinical Biomechanics, October 2000, Volume 15, Issue 8, pp.567-573.
http://www.clinbiomech.com/article/S0268-0033(00)00024-3/abstract
“Definition of Neurochemical Patterns of Human Head Injury in Human MRS Using Wavelet Analysis”.
Frederick Shic, Alexander Lin, C H Shelden, Nick Panagiotacopulos, Brian Ross
Proc. Intl. Soc. Mag. Resonance. Med 9, July 2001 Glasgow, Scotland
“A Continuous Wavelet Transform treatment of Surface Electromyographic Signals obtained from Patients with Low Back Pain before and after rehabilitation”. N. D. Panagiotacopulos, M. L. Amos, D. G. Panayotakopoulos
IMAGE PROCESSING AND COMMUNICATIONS, INTELLIGENT SENSING, IMAGE PROCESSING AND APPLICATIONS, pp.113-120, Vol.8,No.2, 2002.
https://www.infona.pl/resource/bwmeta1.element.baztech-article-BAT2-0001-0283
“Wavelet Analysis of Low Back Surface EMG Signals Subject to Unexpected Load”.
M. H. Pope, N. D. Panagiotacopulos,w. Stielau, K. Friesen
JOURNAL OF MECHANICS AND BIOLOGY, WORLD SCIENTIFIC,
Vol. 4, No. 3, pp. 389-400, 2004.