For complex industrial processes with multiple operating conditions, the traditional multivariate process monitoring techniques such as principal component analysis (PCA) and partial least squares (PLS) are ill‐suited because the fundamental assumption that the operating data follow a unimodal Gaussian distribution usually becomes invalid. In this article, a novel multimode process monitoring approach based on finite Gaussian mixture model (FGMM) and Bayesian inference strategy is proposed. First, the process data are assumed to be from a number of different clusters, each of which corresponds to an operating mode and can be characterized by a Gaussian component. In the absence of a priori process knowledge, the Figueiredo–Jain (F–J) algorithm is then adopted to automatically optimize the number of Gaussian components and estimate their statistical distribution parameters. With the obtained FGMM, a Bayesian inference strategy is further utilized to compute the posterior probabilities of each monitored sample belonging to the multiple components and derive an integrated global probabilistic index for fault detection of multimode processes. The validity and effectiveness of the proposed monitoring approach are illustrated through three examples: (1) a simple multivariate linear system, (2) a simulated continuous stirred tank heater (CSTH) process, and (3) the Tennessee Eastman challenge problem. The comparison of monitoring results demonstrates that the proposed approach is superior to the conventional PCA method and can achieve accurate and early detection of various types of faults in multimode processes. © 2008 American Institute of Chemical Engineers AIChE J, 2008

Currently available clinico–pathologic criteria provide an imperfect assessment of outcome for patients with advanced epithelial ovarian cancer (EOC). Identification of prognostic factors related to tumor biology might improve this assessment. We investigated the prognostic significance of the melanoma cell adhesion molecule (M‐CAM) in EOC. Using the same antibody, M‐CAM expression was tested by Western blotting in protein extracts and by immunohistochemestry in tissue microarrays generated from 133 consecutively resected, well characterized EOC samples. Fisher test, Kaplan–Meier method and Cox proportional hazards analysis were used to relate M‐CAM expression to clinico–pathological variables and to time to progression (TTP) and overall survival (OS). In vitro biochemical analysis showed a progressively increased M‐CAM expression from normal to malignant cells. M‐CAM protein, detected immunohistochemically, was significantly associated with advanced tumor stage, serous and undifferentiated histotype, extent of residual disease and p53 accumulation. Presence or absence of M‐CAM significantly divided patients according to their TTP (median, 22 vs. 79 months, respectively; log‐rank p = 0.001) and OS (median, 42 vs. 131 months, respectively; log‐rank p = 0.0003). In the subgroup of advanced stage patients who achieved complete response after front‐line treatment, M‐CAM expression and absence of residual disease were significantly associated with shorter TTP (p = 0.003, HR 5.25, 95% Cl 1.79–15.41 and p = 0.011, HR 3.77, 95% Cl 1.36–10.49 respectively) at the multivariate level. In the same sub‐group of patients, M‐CAM expression remained the only parameter significantly associated with OS (p = 0.005, HR 3.35, 95% Cl 1.42–6.88). M‐CAM is a marker of early relapse and poorer outcome in EOC. In particular, M‐CAM expression identifies a subgroup of front‐line therapy‐responding patients who undergo dramatic relapses, thus helping to better select patients who might benefit from new/alternative therapeutic modalities. © 2006 Wiley‐Liss, Inc.

BackgroundKi67 labeling index (Ki67 LI), the percentage Ki67 immunoreactive cells, is a measure of tumor proliferation, with important clinical relevance in breast cancer, and it is extremely important to standardize its evaluation.AimTo test the efficacy of computer assisted image analysis (CAIA) applied to completely digitized slides and to assess its feasibility in routine practice and compare the results obtained using two different Ki67 monoclonal antibodies.Materials and methods315 consecutive breast cancer routinely immunostained for Ki-67 (223 with SP6 and 92 with MM1 antibodies previously examined by an experienced pathologist, have been re-evaluated using Aperio Scanscope Xs.ResultsMean human Ki67 LI values were 36%± 14.% and 28% ± 18% respectively for SP6 and MM1 antibodies; mean CAM Ki67 LI values were 31%± 19% and 22% ± 18% respectively for SP6 and MM1. Human and CAIA evaluation are statistically highly correlated (Pearson: 0.859, p<0.0001), although human LI are systematically higher. An interobserver variation study on CAIA performed on 84 cases showed that the correlation between the two evaluations was linear to an excellent degree.DiscussionOur study shows that a) CAIA can be easily adopted in routine practice, b) human and CAIA Ki67 LI are highly correlated, although human LI are systematically higher, c) Ki67 LI using different evaluation methods and different antibodies shows important differences in cut-off values.

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All cervical intraepithelial neoplasia (CIN) diagnoses identified during the New Technologies for Cervical Cancer trial (ISRCTN81678807) were blindly reviewed by 2 pathologists. Original diagnoses based on colposcopy-guided biopsies were compared with those made by the reviewers who had access to all clinical histologic samples (including postsurgical). Cases downgraded from CIN 2+ by the reviewers were considered indicative of unnecessary treatments. The analyses are presented according to the molecular (high-risk human papillomavirus [HPV]) and/or cytologic diagnosis used to refer the women for colposcopy. We reviewed 812 CIN 1 and 364 CIN 2 + diagnoses. The specificity of colposcopy-guided biopsy was 98% and the sensitivity, 84%. The probability of unnecessary treatment was 27% for women with atypical squamous cells of undetermined significance cytologic findings and 8% for women with low-grade squamous intraepithelial lesion or worse, 10% for HPV+ and positive cytologic findings, and 16% for HPV+ alone. The positive predictive value of the first-level screening test was inversely associated with probability of a histologic false-positive result (P = .015). In screening, a low positive predictive value of the colposcopy-referring test may result in unnecessary treatments.