Intraobserver and interobserver variability in the quality assessment of cervical smears

Department of Pathology, University of Nijmegen, the Netherlands.
Acta cytologica (Impact Factor: 1.56). 01/1989; 33(2):215-8.
Source: PubMed


Intraobserver and interobserver variability in assessing the quality of cervical smears, as measured by the presence or absence of endocervical columnar cells and squamous metaplastic cells, was evaluated. In total, 180 cervical smears representing the most important cytologic diagnoses were anonymously rescreened twice by 19 observers with an interval of six months. An absence of endocervical columnar cells was proven to correlate with a high percentage of false-negative diagnoses. Intraobserver agreement on the presence or absence of endocervical columnar cells was 85.7% between the two screenings. A predictive value of 57.7% was found for a negative scoring (absence of these cells) while the predictive value of a positive scoring (presence of endocervical cells) was 87.3%. Of the observer scorings, 83.9% concurred with the final diagnosis; there was no significant correlation between that concurrence and the number of years of experience in cytopathology of the observer. For squamous and squamous metaplastic cells in the cervical smear the predictive value of a negative scoring (absence) was only 20.6%. Compared to the final diagnosis, 69.5% of these scorings matched. A significant and relatively high correlation with the experience of the observer was found for the scoring for the presence of metaplastic cells. Even though the predictive values of these quality scorings were relatively low a significantly higher risk for false diagnoses was established when negative scorings were given. It is therefore advisable to have smears with negative scorings for endocervical columnar cells and squamous metaplastic cells always rescreened by another observer.

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    ABSTRACT: Histopathologic evaluation of surgical specimens is a well established technique for disease identification, and has remained relatively unchanged since its clinical introduction. Although it is essential for clinical investigation, histopathologic identification of tissues remains a time consuming and subjective technique, with unsatisfactory levels of inter- and intra-observer discrepancy. A novel approach for histological recognition is to use Fourier Transform Infrared (FT-IR) micro-spectroscopy. This non-destructive optical technique can provide a rapid measurement of sample biochemistry and identify variations that occur between healthy and diseased tissues. The advantage of this method is that it is objective and provides reproducible diagnosis, independent of fatigue, experience and inter-observer variability. We report a method for analysing excised lymph nodes that is based on spectral pathology. In spectral pathology, an unstained (fixed or snap frozen) tissue section is interrogated by a beam of infrared light that samples pixels of 25 mum x 25 mum in size. This beam is rastered over the sample, and up to 100,000 complete infrared spectra are acquired for a given tissue sample. These spectra are subsequently analysed by a diagnostic computer algorithm that is trained by correlating spectral and histopathological features. We illustrate the ability of infrared micro-spectral imaging, coupled with completely unsupervised methods of multivariate statistical analysis, to accurately reproduce the histological architecture of axillary lymph nodes. By correlating spectral and histopathological features, a diagnostic algorithm was trained that allowed both accurate and rapid classification of benign and malignant tissues composed within different lymph nodes. This approach was successfully applied to both deparaffinised and frozen tissues and indicates that both intra-operative and more conventional surgical specimens can be diagnosed by this technique. This paper provides strong evidence that automated diagnosis by means of infrared micro-spectral imaging is possible. Recent investigations within the author's laboratory upon lymph nodes have also revealed that cancers from different primary tumours provide distinctly different spectral signatures. Thus poorly differentiated and hard-to-determine cases of metastatic invasion, such as micrometastases, may additionally be identified by this technique. Finally, we differentiate benign and malignant tissues composed within axillary lymph nodes by completely automated methods of spectral analysis.
    BMC Clinical Pathology 02/2008; 8(1):8. DOI:10.1186/1472-6890-8-8
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    • "of which histological evaluation and morphologic grading are the most important. However, these methods are based on subjective evaluations which often result in considerable inter-and intra-observer variation [52] [62] [63] [107]. Therefore, image analysis methods have been developed in an attempt to obtain more objective diagnosis. "
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    Acta cytologica 51(6). · 1.56 Impact Factor
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