Biomedical subjects

Melissa A Burns

Publications and source records attributed to Melissa A Burns.

3 recordsLinked to original sources

PubMed2005

Metabolic characterization of human prostate cancer with tissue magnetic resonance spectroscopy.

Diagnostic advancements for prostate cancer have so greatly increased early detections that hope abounds for improved patient outcomes. However, histopathology, which guides treatment, often subcategorizes aggressiveness insufficiently among moderately differentiated Gleason score (6 and 7) tumors (>70% of new cases). Here, we test the diagnostic capability of prostate metabolite profiles measured with intact tissue magnetic resonance spectroscopy and the sensitivity of local prostate metabolites in predicting prostate cancer status. Prostate tissue samples (n = 199) obtained from 82 prostate cancer patients after prostatectomy were analyzed with high-resolution magic angle spinning proton magnetic resonance spectroscopy, and afterwards with quantitative pathology. Metabolite profiles obtained from principal component analysis of magnetic resonance spectroscopy were correlated with pathologic quantitative findings by using linear regression analysis and evaluated against patient pathologic statuses by using ANOVA. Paired t tests show that tissue metabolite profiles can differentiate malignant from benign samples obtained from the same patient (P < 0.005) and correlate with patient serum prostate-specific antigen levels (P < 0.006). Furthermore, metabolite profiles obtained from histologically benign tissue samples of Gleason score 6 and 7 prostates can delineate a subset of less aggressive tumors (P < 0.008) and predict tumor perineural invasion within the subset (P < 0.03). These results indicate that magnetic resonance spectroscopy metabolite profiles of biopsy tissues may help direct treatment plans by assessing prostate cancer pathologic stage and aggressiveness, which at present can be histopathologically determined only after prostatectomy.

Humans↗

PubMed2005

Reduction of spinning sidebands in proton NMR of human prostate tissue with slow high-resolution magic angle spinning.

High-resolution magic angle spinning (HRMAS) NMR spectroscopy has proven useful for analyzing intact tissue and permitting correlations to be made between tissue metabolites and disease pathologies. Extending these studies to slow-spinning methodologies helps protect tissue pathological structures from HRMAS centrifuging damage and may permit the study of larger objects. Spinning sidebands (SSBs), which are produced by slow spinning, must be suppressed to prevent the complication of metabolic spectral regions. In this study human prostate tissues, as well as gel samples of a metabolite mixture solution, were measured with continuous-wave (CW) water presaturation on a 14.1T spectrometer, with HRMAS spinning rates of 250, 300, 350, 600, and 700 Hz, and 3.0 kHz. Editing the spectra by means of a simple minimum function (Min(A, B, ..., N) for N spectra acquired at different but close spinning rates) produced SSB-free spectra. Statistically significant linear correlations were observed for metabolite concentrations quantified from the Min(A, B, ..., N)-edited spectra generated at low spinning rates, with concentrations measured from the 3 kHz spectra, and also with quantitative pathology. These results indicate the empirical utility of this scheme for analyzing intact tissue, which also may be used as an adjunct tool in pathology for diagnosing disease.

Algorithms↗

PubMed2004

Quantitative pathology in tissue MR spectroscopy based human prostate metabolomics.

At present, the clinical utility of metabolomic profiles of human prostate tissue relies on the establishment of correlations between metabolite data and clinical measurements, particularly pathological findings. Because metabolomics is a quantitative study, its clinical value can be rigorously investigated by determining its association with other quantitative measures. The human visual assessment of prostate tissue, however, introduces both inter- and intra-observer biases that may limit the reliability of its quantitations, and therefore, the strength of its correlations with metabolomic profiles. The aim of this study was to develop a simple, feasible protocol for the computer-aided image analysis (CAIA) of prostate pathology slides in order to achieve quantitative pathology from tissue samples, following metabolomic measurement with high-resolution magic angle spinning (HRMAS) magnetic resonance spectroscopy (MRS). Thirty-eight samples from 29 prostatectomy cases were studied with HRMAS MRS. After spectroscopy analysis, samples were serial-sectioned, stained and visually assessed by pathologists. Cross-sections from these samples were then measured with the CAIA protocol. Results showed a two-fold difference between human visual assessments of the area percentages of tissue pathologies and CAIA area percentages obtained for the same features. Linear correlations were found between both metabolites indicative of normal epithelium and those indicative of prostate cancer, and the CAIA quantitative results. CAIA based quantitative pathology is more reliable than human visual assessment in establishing correlations useful for disease diagnosis between prostate pathology and metabolite concentrations.

Epithelium↗