Cynthia L. Lean

Magnetic resonance spectroscopy detects biochemical changes in the brain associated with chronic low back pain: a preliminary report

Magnetic resonance (MR) spectroscopy is a noninvasive technique that can be used to detect and measure the concentration of metabolites and neurotransmitters in the brain and other organs. We used in vivo 1H MR spectroscopy in subjects with low back pain compared with control subjects to detect alterations in biochemistry in three brain regions associated with pain processing. A pattern recognition approach was used to determine whether it was possible to discriminate accurately subjects with low back pain from control subjects based on MR spectroscopy. MR spectra were obtained from the prefrontal cortex, anterior cingulate cortex, and thalamus of 32 subjects with low back pain and 33 control subjects without pain. Spectra were analyzed and compared between groups using a pattern recognition method (Statistical Classification Strategy). Using this approach, it was possible to discriminate between subjects with low back pain and control subjects with accuracies of 100%, 99%, and 97% using spectra obtained from the anterior cingulate cortex, thalamus, and prefrontal cortex, respectively. These results demonstrate that MR spectroscopy, in combination with an appropriate pattern recognition approach, is able to detect brain biochemical changes associated with chronic pain with a high degree of accuracy.

Accurate diagnosis and prognosis of human cancers by proton MRS and a three-stage classification strategy

Publisher Summary Magnetic resonance spectroscopy (MRS) of human biopsy specimens has the potential to become the new gold standard for pathological and, in some organs, clinical characterization of human cancers. MRS can detect small populations of abnormal cells with high accuracy, and identify and subcategorize preinvasive states. In addition, MRS detects changes to cellular chemistry in human tissues prior to these changes being apparent under the light microscope and, hence, discernable by various methods. The development of a classifier for breast biopsy that determines both pathology and nodal involvement is a paradigm shift in the management of breast disease. It remains to be seen if such prognostic information is available in spectra from other organs such as prostate and oesophagus. This new methodology is of clinical importance in identifying the extent of abnormality in preinvasive states, particularly in patients with a predisposition to cancer. The three-stage statistical classification strategy (SCS)-based methodology, which is the focus of this chapter, has been specifically developed for this purpose. The method provides accurate and reliable classification of large amounts of biomedical spectral data, while ensuring that the complete content of the spectrum is considered, spectral identity is retained, and a degree of confidence in a given diagnosis is provided. Furthermore, the use of SCS allows the MRS method to be automated, a step which must precede the routine use of this technology by clinicians.

Determination of Grade and Receptor Status from the Primary Breast Lesion by Magnetic Resonance Spectroscopy

Magnetic resonance spectra (MRS) from fine needle aspiration biopsies (FNAB) from primary breast lesions were analysed using a pattern recognition method, Statistical Classification Strategy, to assess tumor grade and oestrogen receptor (ER) and progesterone receptor (PgR) status. Grade 1 and 2 breast cancers were separated from grade 3 cancers with a sensitivity and specificity of 96% and 95%, respectively. The ER status was predicted with a sensitivity of 91% and a specificity of 90%, and the PgR status with a sensitivity of 91% and a specificity of 86%. These classifiers provide rapid and reliable, computerized information and may offer an objective method for determining these prognostic indicators simultaneously with the diagnosis of primary pathology and lymph node involvement.

The Use of Proton MR in Cancer Pathology

Publisher Summary This chapter describes the use of proton MR in cancer pathology. Water-based MRI is, at present, independently unable to identify the pathology of human tumors. The literature and work in this domain indicate that by studying carefully controlled model systems and excised human tissues, 1 H MRS can extract chemical information relating directly to the pathology. In addition, by tailoring data acquisition and processing parameters to report specifically on those molecules of known diagnostic relevance, 1 H MRS can diagnose invasive cancer in many organs ex vivo and some in vivo . 1 H MRS has the potential to provide an independent modality that can (1) report on the presence of invasive or preinvasive neoplastic cells in biopsy specimens, (2) detect the microfoci of metastatic cells missed by routine histopathology, and (3) provide a precise diagnosis to aid in the decision on treatment and subsequent patient management. Cancer can be diagnosed by 1 H MRS if the pathological criteria are linked to specific chemical changes ascertained from intact cells and tissues. This concept was demonstrated by the cervix program where CSI ( ex vivo ) not only defined the pathology of the tissue but also provided a spatial map of the diseased areas.

Two-Dimensional Proton Magnetic Resonance Spectroscopy for Tissue Characterization of Thyroid Neoplasms

Abstract. We have previously demonstrated that one dimensional (1D) proton ( 1 H) magnetic resonance spectroscopy (MRS) can distinguish normal thyroid tissue from thyroid carcinoma using a spectral ratio of peak intensity at 1.7 ppm/0.9 ppm. Two dimensional (2D) 1 H-MRS allows identification of specific molecules that have overlapping peaks in the 1D-MR spectrum. Specimens from 93 consecutive thyroid nodules were examined using 2D 1 H-MRS on a Bruker AM-360 wide-bore spectrometer. There was a progressive increase in lipid cross peaks assigned to di-/triglycerides when comparing colloid/hyperplastic nodules to follicular adenoma, and adenoma to carcinoma. A specific cross peak attributable to cholesterol/cholesteryl esters was commonly seen in carcinomas. In contrast, two unassigned cross peaks unique to the thyroid were more prevalent in benign lesions. There was an overall increase in cross peaks attributable to cell surface fucosylation in carcinoma when compared to benign lesions, although the fucose spectral pattern was not specific for cancer. On this basis, a spectral ratio of peak intensity at 2.05 ppm/0.9 ppm more clearly distinguished benign follicular adenoma from carcinoma. 2D 1 H-MRS thus identifies chemical changes that allow more specific tissue characterization of thyroid neoplasms.

Cancer pathology in the year 2000

The last one hundred and fifty years has produced the mature and sophisticated discipline of histopathology, yet still leaves the diagnosis of human cancer, by the best available technique, as more art than science. Proton magnetic resonance spectroscopy (1H MRS) ex vivo identifies the chemical markers of established pathobiological disorders within excised biopsies and fine needle aspirates, in particular, those associated with the development and progression of malignant disease. Alterations to cellular chemistry monitored by 1H MRS allows distinction between invasive and pre-invasive lesions of the uterine cervix, and separate truly benign follicular neoplasms from follicular carcinomas on analysis of fine needle aspirates containing as few as 10(6) cells. 1H chemical shift imaging (CSI) determines the spatial location of these chemical changes and provides insight into the chemistry of neoplastic transformation. It is our hypothesis that, by the year 2000, CSI will aid image guided biopsy techniques and that correlation of biopsy histology with in vivo localised 1H MRS data will: (a) lead to improved assessment of the extent of malignant disease and (b) establish the sensitivity and specificity of in vivo 1H MRS for the simultaneous determination of the size, location and neoplastic potential of a tumour mass.

Melanoma metastases in regional lymph nodes are accurately detected by proton magnetic resonance spectroscopy of fine-needle aspirate biopsy samples.

BackgroundNonsurgical assessment of sentinel nodes (SNs) would offer advantages over surgical SN excision by reducing morbidity and costs. Proton magnetic resonance spectroscopy (MRS) of fine-needle aspirate biopsy (FNAB) specimens identifies melanoma lymph node metastases. This study was undertaken to determine the accuracy of the MRS method and thereby establish a basis for the future development of a nonsurgical technique for assessing SNs.MethodsFNAB samples were obtained from 118 biopsy specimens from 77 patients during SN biopsy and regional lymphadenectomy. The specimens were histologically evaluated and correlated with MRS data. Histopathologic analysis established that 56 specimens contained metastatic melanoma and that 62 specimens were benign. A linear discriminant analysis–based classifier was developed for benign tissues and metastases.ResultsThe presence of metastatic melanoma in lymph nodes was predicted with a sensitivity of 92.9%, a specificity of 90.3%, and an accuracy of 91.5% in a primary data set. In a second data set that used FNAB samples separate from the original tissue samples, melanoma metastases were predicted with a sensitivity of 87.5%, a specificity of 90.3%, and an accuracy of 89.1%, thus supporting the reproducibility of the method.ConclusionsProton MRS of FNAB samples may provide a robust and accurate diagnosis of metastatic disease in the regional lymph nodes of melanoma patients. These data indicate the potential for SN staging of melanoma without surgical biopsy and histopathological evaluation.

Diagnostic value of 8.5 t magnetic resonance spectroscopy of benign and malignant skin lesion biopsies

Proton magnetic resonance spectroscopy at 8.5 T ex vivo was used to investigate skin lesions for metabolic signatures to predict malignancy or indicate malignant potential. Magnetic resonance spectroscopy was performed on biopsy tissue obtained from 63 skin lesions and five melanoma metastases from 55 patients. Samples were grouped and compared according to five clinically significant distinctions: melanoma (n=38) or nonmelanoma (n=30), primary melanoma (n=33) or secondary melanoma (involved nodes and distant metastases, n=5), primary melanoma (n=33) or nevi (n=8), malignant (n=46) or nonmalignant (n=22), and melanocytic (n=46) or nonmelanocytic (n=22). In all comparisons, the average magnetic resonance spectrum of each class lay within 1 standard deviation of the average spectrum of the other class. There was a higher average choline metabolite signal intensity in melanoma-containing biopsies compared with nonmelanoma biopsies. Discriminant analysis based on the intensity of the choline resonance alone achieved 69% accuracy in separation of melanoma and nonmelanoma tissue. Inclusion of other metabolite resonances in the analysis did not increase discrimination accuracy. Tissue heterogeneity in conventionally collected full thickness skin biopsies and possible biochemical variance within individual tissue types limit classification accuracy using the methods and magnetic field strength that were earlier reported to provide accurate discrimination in other cancer types.

High Resolution Magic Angle Spinning (HRMAS) Proton MRS of Surgical Specimens

BPH Benign prostatic hyperplasis DCIS Ductal carcinoma in situ FNAB Fine needle aspiration biopsy GBM Glioblastoma multiforme HCA Hierarchical cluster analysis 1H MRS Proton magnetic resonance spectroscopy HPLC High pressure liquid chromatography (HR)MAS (High resolution) Magic angle spinning NAA N-acetyl aspartate PA Polyamines PC Phosphocholine PCA Principal component analysis PTC Phosphatidylcholine SCS Statistical classification strategy SSB Spinning side bands

Detection of melanoma lymph node metastases by proton magnetic resonance spectroscopy of fine-needle aspirates

Introduction Non-surgical sentinel node (SN) evaluation offers advantages over SN removal. Proton Magnetic Resonance Spectroscopy (MRS) of lymph node needle aspirates accurately identifies the presence of metabolites associated with melanoma micrometastases. Validation of this technique would reduce the morbidity and costs of SN evaluation. Methods Fine needle aspiration biopsies (FNAB) from 70 malignant and 42 benign nodes from patients undergoing node resection for metastatic melanoma were obtained. Proton MRS (8.5 T) was carried out using standard protocols (4). Four 5~tm sections from each node block (3mm thick) were stained with H&E (2 sections) and for S 100 protein and HMB45. MR spectra and histopathology were correlated using a statistical classification strategy (SCS) (3). Results Proton MRS of FNAB from benign and metastatic nodes are shown in Figure 1. Resonances include those from lipid (Lip), amino acids, lactate, creatine (Cre), phosphocreatine, choline (Chol) metabolites and inositol. An SCS-based classifier was generated for benign and metastatic nodes. In four random training sets, spectra from 47 metastatic and 28 benign nodes were subjected to SCS. Using five optimally discriminatory spectral regions, metastases was predicted with a sensitivity of 97.3%, a specificity of 90.2% and an accuracy of 94.7%. In independent validation sets (samples not in training sets), including 23 metastatic and 14 benign nodes, the presence of metastases was predicted with a sensitivity of 93.5%, a specificity of 87.5% and an accuracy of 91.2%. The crispness of the data (% samples with a class probability >75%) was ~88% for training and validation sets. These data indicate that SN staging of melanoma may be achieved without surgical biopsy and histopathology. Conclusions Pro- ton MRS of FNAB of lymph nodes provides robust, accurate diagnosis of metastatic disease in nodes from melanoma patients.