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BACKGROUND: The protein ki67 (pki67) is a marker of tumor aggressiveness, and its expression has been proven to be useful in the prognostic and predictive evaluation of several types of tumors. To numerically quantify the pki67 presence in cancerous tissue areas, pathologists generally analyze histochemical images to count the number of tumor nuclei marked for pki67. This allows estimating the ki67-index, that is the percentage of tumor nuclei positive for pki67 over all the tumor nuclei. Given the high image resolution and dimensions, its estimation by expert clinicians is particularly laborious and time consuming. Though automatic cell counting techniques have been presented so far, the problem is still open. RESULTS: In this paper we present a novel automatic approach for the estimations of the ki67-index. The method starts by exploiting the STRESS algorithm to produce a color enhanced image where all pixels belonging to nuclei are easily identified by thresholding, and then separated into positive (i.e. pixels belonging to nuclei marked for pki67) and negative by a binary classification tree. Next, positive and negative nuclei pixels are processed separately by two multiscale procedures identifying isolated nuclei and separating adjoining nuclei. The multiscale procedures exploit two Bayesian classification trees to recognize positive and negative nuclei-shaped regions. CONCLUSIONS: The evaluation of the computed results, both through experts' visual assessments and through the comparison of the computed indexes with those of experts, proved that the prototype is promising, so that experts believe in its potential as a tool to be exploited in the clinical practice as a valid aid for clinicians estimating the ki67-index. The MATLAB source code is open source for research purposes

Background: In the clinical practice, the objective quantification of histological results is essential not only to define objective and well-established protocols for diagnosis, treatment, and assessment, but also to ameliorate disease comprehension. Software: The software MIAQuant_Learn presented in this work segments, quantifies and analyzes markers in histochemical and immunohistochemical images obtained by different biological procedures and imaging tools. MIAQuant_Learn employs supervised learning techniques to customize the marker segmentation process with respect to any marker color appearance. Our software expresses the location of the segmented markers with respect to regions of interest by mean-distance histograms, which are numerically compared by measuring their intersection. When contiguous tissue sections stained by different markers are available, MIAQuant_Learn aligns them and overlaps the segmented markers in a unique image enabling a visual comparative analysis of the spatial distribution of each marker (markers' relative location). Additionally, it computes novel measures of markers' co-existence in tissue volumes depending on their density. Conclusions: Applications of MIAQuant_Learn in clinical research studies have proven its effectiveness as a fast and efficient tool for the automatic extraction, quantification and analysis of histological sections. It is robust with respect to several deficits caused by image acquisition systems and produces objective and reproducible results. Thanks to its flexibility, MIAQuant_Learn represents an important tool to be exploited in basic research where needs are constantly changing.

In the clinical practice, automatic image analysis methods quickly quantizing histological results by objective and replicable methods are getting more and more necessary and widespread. Despite several commercial software products are available for this task, they are very little flexible, and provided as black boxes without modifiable source code. To overcome the aforementioned problems, we employed the commonly used MATLAB platform to develop an automatic method, MIAQuant, for the analysis of histochemical and immunohistochemical images, stained with various methods and acquired by different tools. It automatically extracts and quantifies markers characterized by various colors and shapes; furthermore, it aligns contiguous tissue slices stained by different markers and overlaps them with differing colors for visual comparison of their localization. Application of MIAQuant for clinical research fields, such as oncology and cardiovascular disease studies, has proven its efficacy, robustness and flexibility with respect to various problems; we highlight that, the flexibility of MIAQuant makes it an important tool to be exploited for basic researches where needs are constantly changing. MIAQuant software and its user manual are freely available for clinical studies, pathological research, and diagnosis.

Background Pregnancy on dialysis is increasingly being reported. This study evaluates the behavioural profile of the children of mothers on dialysis and the parental stress their mothers undergo when compared with a group of mothers affected by a different chronic disease (microcythaemia) and a group of healthy control mothers. Methods Between 2000 and 2012, 23 on-dialysis mothers gave birth to 24 live-born children in Italy (23 pregnancies, 1 twin pregnancy, one of the twins deceased soon after delivery); of these, 16 mothers and 1 father (whose wife died before the inquiry) were included in the study (1 mother had died and the father was unavailable; 2 were not asked to participate because their children had died and 3 were unavailable; children: median age: 8.5, min-max: 2-13 years). Twenty-three mothers affected by transfusion-dependent microcythaemia or drepanocitosis (31 pregnancies, 32 children) and 35 healthy mothers (35 pregnancies, 35 children; median age of the children: 7, min-max: 1-13 years) were recruited as controls. All filled in the validated questionnaires: 'Child Behaviour Checklist' (CBCL) and the 'Parental Stress Index-Short Form' (PSI-SF). Results The results of the CBCL questionnaire were similar for mothers on dialysis and healthy controls except for pervasive developmental problems, which were significantly higher in the dialysis group, while microcythaemia mothers reported higher emotional and behavioural problems in their children in 8 CBCL sub-scales. Two/16 children in the dialysis and 3/32 in the microcythaemia group had pathological profiles, as assessed by T-scores (p: ns). PSI-SF indicated a normal degree of parental stress in microcythaemia subjects and healthy controls, while mothers on dialysis declared significantly lower stress, suggesting a defensive response in order to minimize problems, stress or negativity in their relationship with their child. Conclusions According to the present analysis, the emotional and behavioural o