An optical detection method, Raman chemical imaging spectroscopy (RCIS), is reported, which combines Raman spectroscopy, fluorescence spectroscopy, and digital imaging. Using this method, trace levels of biothreat organisms are detected in the presence of complex environmental backgrounds without the use of amplification or enhancement techniques. RCIS is reliant upon the use of Raman signatures and automated recognition algorithms to perform species-level identification. The rationale and steps for constructing a pathogen Raman signature library are described, as well as the first reported Raman spectra from live, priority pathogens, including Bacillus anthracis, Yersinia pestis, Burkholderia mallei, Francisella tularensis, Brucella abortus, and ricin. Results from a government-managed blind trial evaluation of the signature library demonstrated excellent specificity under controlled laboratory conditions.

Study Type – Diagnostic (exploratory cohort)
Level of Evidence 2b OBJECTIVE To evaluate whether Raman molecular imaging (RMI, which combines digital imaging and analytical spectroscopy to evaluate the biochemical composition of interrogated material) can be used to identify biochemical differences in patients with Gleason 7 prostate cancer who progress to metastatic disease and die from prostate cancer. PATIENTS AND METHODS We identified 38 patients who had a radical prostatectomy for Gleason 7 adenocarcinoma of the prostate. Half progressed to metastatic disease and half had no evidence of disease after treatment. Patients were matched for preoperative prostate‐specific antigen level, surgical margin status, pathological stage, tumour volume, age at surgery, year of surgery and DNA ploidy. Sequential 5 µm sections were obtained from paraffin‐embedded tissue and one genitourinary pathologist selected areas of tumour for study. Principal component analysis was used to investigate the correlation between spectral response and clinical outcome. RESULTS The analysis was able to distinguish between those with progressive disease and those with no evidence of disease, most notably within the Gleason 3 regions when evaluating the epithelium and stroma as separate histological elements. A two‐sample t‐test gave P < 0.01 for both the Gleason 3 and 4 epithelium and stroma classes. CONCLUSIONS RMI is a novel technique that shows promise for identifying patients at risk of progression by visualizing molecular information not seen using other current methods. In Gleason 7 disease, RMI shows distinctive chemical differences in patients who progress to metastatic disease in both Gleason pattern 3 and 4 regions. This preliminary work lays the foundation for the further study of RMI for evaluating prostate tissue.