Bone involvement in chronic rhinosinusitis assessed by 99mTc-MDP bone SPECT.

To investigate the clinical significance of bone involvement in chronic rhinosinusitis, 99mTc-MDP bone single photon emission computed tomography (SPECT) was studied in 43 patients diagnosed as having chronic rhinosinusitis. Quantitative isotope uptake indices calculated on SPECT were compared between the patient and a control group, and between patients with a good postoperative outcome and those with a poor outcome. The patient group showed a significantly higher isotope uptake than the control group. The uptake of isotope in the ethmoid sinus areas in patients who had a poor postoperative outcome was significantly higher than those who had a good outcome. Our study suggests that patients with chronic rhinosinusitis have apparent bony involvement, and patients with more severe bone involvement may have a poorer treatment outcome.

Sinonasal tuberculosis associated with osteomyelitis of the ethmoid bone and cervical lymphadenopathy.

Sinonasal tuberculosis is a rare disease; its association with osteomyelitis of surrounding bone and cervical lymphadenopathy has been reported rarely. In this article, we report a case of sinonasal tuberculosis that was complicated by osteomyelitis of the ethmoid bone and cervical lymphadenopathy. Infection of the bone was demonstrated by biopsy and (99m)Tc-MDP bone single photon emission computed tomography (SPECT), and cervical lymphadenopathy was confirmed by histology. This case will be discussed with specific emphasis on the imaging characteristics.

Prospects for in vivo Raman spectroscopy.

Raman spectroscopy is a potentially important clinical tool for real-time diagnosis of disease and in situ evaluation of living tissue. The purpose of this article is to review the biological and physical basis of Raman spectroscopy of tissue, to assess the current status of the field and to explore future directions. The principles of Raman spectroscopy and the molecular level information it provides are explained. An overview of the evolution of Raman spectroscopic techniques in biology and medicine, from early investigations using visible laser excitation to present-day technology based on near-infrared laser excitation and charge-coupled device array detection, is presented. State-of-the-art Raman spectrometer systems for research laboratory and clinical settings are described. Modern methods of multivariate spectral analysis for extracting diagnostic, chemical and morphological information are reviewed. Several in-depth applications are presented to illustrate the methods of collecting, processing and analysing data, as well as the range of medical applications under study. Finally, the issues to be addressed in implementing Raman spectroscopy in various clinical applications, as well as some long-term directions for future study, are discussed.

Population genetics of the hypervariable locus D12S391 in Koreans.

The hypervariable short tandem repeat (STR) locus D12S391 was investigated in a Korean population and 34 fragments were sequenced to confirm the structure of alleles. From these sequenced fragments an allelic ladder containing 13 sequenced alleles was constructed. From 595 unrelated Koreans, 14 alleles were detected and one variant allele 19.3 was observed. The observed heterozygosity was 0.795 and no deviation from Hardy-Weinberg equilibrium was observed in the Korean population (p = 0.606). The allele frequency distribution in the Korean population was not similar to other racial or ethnic groups except for Egyptians, Yemenis, Japanese and Caucasoids from the Rhine area. No mutations were observed in the 702 meioses from 144 Korean families. This study demonstrates that the STR locus D12S391 is a useful tool for forensic identification and parentage testing.

Reagentless blood analysis by near-infrared Raman spectroscopy.

BACKGROUND: Raman spectroscopy has advantages over infrared absorption spectroscopy. Combined with a novel multivariate technique, hybrid linear analysis (HLA), low prediction error is expected. METHODS: A near-infrared (NIR) light source excited Raman signals, and a charge coupled device (CCD) camera was used to collect the signal. Samples were collected from 69 individuals for 7 weeks. The standard multivariate calibration technique, partial least squares (PLS) and HLA were both used to analyze the collected spectra. A Clarke error grid was used to evaluate the usefulness of the glucose measurement in serum. RESULTS: The root mean squared error of prediction (RMSEP) for glucose in serum obtained with PLS is 21 mg/dL, and the RMSEP obtained with HLA is 17 mg/dL. In whole blood, the PLS RMSEP for glucose was 79 mg/dL, and HLA predictions had an RMSEP of 63 mg/dL. CONCLUSIONS: The measurement technique was robust over the 7-week period. HLA was shown to generate a lower prediction error than PLS. The predictions by both PLS and HLA were clinically acceptable. The result with whole blood requires further improvement.

Multicomponent blood analysis by near-infrared Raman spectroscopy.

We demonstrate the use of Raman spectroscopy to measure the concentration of many important constituents (analytes) in serum and whole blood samples at physiological concentration in vitro across a multipatient data set. A near-infrared (830-nm) diode laser generates Raman spectra that contain superpositions of Raman signals from different analytes. Calibrations for glucose, cholesterol, urea, and other analytes are developed by use of partial least-squares cross validation. We predict six analytes in serum with significant accuracy in a 66-patient data set, using 60-s spectra. The calibrations are shown to be fairly robust against system drift over the span of seven weeks. In whole blood, a preliminary analysis yields accurate predictions of some of the same analytes and also hematocrit. The results hold promise for potential medical applications.

An enhanced algorithm for linear multivariate calibration.

We present a new method of linear multivariate calibration that can generate better prediction results than those obtained by partial least squares (PLS). This is accomplished by incorporating the spectrum of the desired species into the calibration procedure. The method combines the advantages of different standard methods and is therefore called hybrid linear analysis (HLA). In side-by-side tests using both simulated and experimental data, HLA produced lower prediction errors than PLS in all instances. We recommend HLA over PLS in situations where the spectrum of the desired species is available.