Biomedical subjects

André Huisman

Publications and source records attributed to André Huisman.

3 recordsLinked to original sources

PubMed2007

Discrimination between benign and malignant prostate tissue using chromatin texture analysis in 3-D by confocal laser scanning microscopy.

BACKGROUND: Analysis of chromatin texture may improve both the diagnosis and the assessment of the prognosis of prostate cancer. Confocal laser scanning microscopy (CLSM) allows performing measurements in nuclei reconstructed in 3-D. The aim of this study was to evaluate the clinical usefulness of 3-D texture analysis of prostate tissue. METHODS: Image stacks of eight prostate cancer sections were obtained by CLSM of both benign and malignant areas. Texture feature values were computed for individual nuclei. The discriminative power of the texture features was established by receiver operating characteristic (ROC) analysis and linear discriminant analysis (LDA). RESULTS: Texture features were identified that could discriminate between benign and malignant nuclei. LDA correctly classified 89% of the nuclei of the pooled set of benign and malignant nuclei. CONCLUSIONS: 3-D nuclear texture features allow discrimination of most benign and malignant prostate nuclei. We estimate that the classification rates can be increased by improving the image quality.

Adenocarcinoma↗

PubMed2005

Implementation of accurate and fast DNA cytometry by confocal microscopy in 3D.

BACKGROUND: DNA cytometry is a powerful method for measuring genomic instability. Standard approaches that measure DNA content of isolated cells may induce selection bias and do not allow interpretation of genomic instability in the context of the tissue. Confocal Laser Scanning Microscopy (CLSM) provides the opportunity to perform 3D DNA content measurements on intact cells in thick histological sections. Because the technique is technically challenging and time consuming, only a small number of usually manually selected nuclei were analyzed in different studies, not allowing wide clinical evaluation. The aim of this study was to describe the conditions for accurate and fast 3D CLSM cytometry with a minimum of user interaction to arrive at sufficient throughput for pilot clinical applications. METHODS: Nuclear DNA was stained in 14 microm thick tissue sections of normal liver and adrenal stained with either YOYO-1 iodide or TO-PRO-3 iodide. Different pre-treatment strategies were evaluated: boiling in citrate buffer (pH 6.0) followed by RNase application for 1 or 18 hours, or hydrolysis. The image stacks obtained with CLSM at microscope magnifications of x40 or x100 were analyzed off-line using in-house developed software for semi-automated 3D fluorescence quantitation. To avoid sectioned nuclei, the top and bottom of the stacks were identified from ZX and YZ projections. As a measure of histogram quality, the coefficient of variation (CV) of the diploid peak was assessed. RESULTS: The lowest CV (10.3%) was achieved with a protocol without boiling, with 1 hour RNase treatment and TO-PRO-3 iodide staining, and a final image recording at x60 or x100 magnifications. A sample size of 300 nuclei was generally achievable. By filtering the set of automatically segmented nuclei based on volume, size and shape, followed by interactive removal of the few remaining faulty objects, a single measurement was completely analyzed in approximately 3 hours. CONCLUSIONS: The described methodology allows to obtain a largely unbiased sample of nuclei in thick tissue sections using 3D DNA cytometry by confocal laser scanning microscopy within an acceptable time frame for pilot clinical applications, and with a CV small enough to resolve smaller near diploid stemlines. This provides a suitable method for 3D DNA ploidy assessment of selected rare cells based on morphologic characteristics and of clinical samples that are too small to prepare adequate cell suspensions.

Adrenal Glands↗

PubMed2005

Development of 3D chromatin texture analysis using confocal laser scanning microscopy.

INTRODUCTION: Analysis of nuclear texture features as a measure of nuclear chromatin changes has been proven to be useful when measured on thin (5-6 microm) tissue sections using conventional 2D bright field microscopy. The drawback of this approach is that most nuclei are not intact because of those thin sections. Confocal laser scanning microscopy (CLSM) allows measurements of texture in 3D reconstructed nuclei. The aim of this study was to develop 3D texture features that quantitatively describe changes in chromatin architecture associated with malignancy using CLSM images. METHODS: Thirty-five features thoughtfully chosen from 4 categories of 3D texture features (discrete texture features, Markovian features, fractal features, grey value distribution features) were selected and tested for invariance properties (rotation and scaling) using artificial images with a known grey value distribution. The discriminative power of the 3D texture features was tested on artificially constructed benign and malignant 3D nuclei with increasing nucleolar size and advancing chromatin margination towards the periphery of the nucleus. As a clinical proof of principle, the discriminative power of the texture features was assessed on 10 benign and 10 malignant human prostate nuclei, evaluating also whether there was more texture information in 3D whole nuclei compared to a single 2D plane from the middle of the nucleus. RESULTS: All texture features showed the expected invariance properties. Almost all features were sensitive to variations in the nucleolar size and to the degree of margination of chromatin. Fourteen texture features from different categories had high discriminative power for separating the benign and malignant nuclei. The discrete texture features performed less than expected. There was more information on nuclear texture in 3D than in 2D. CONCLUSION: A set of 35 3D nuclear texture features was used successfully to assess nuclear chromatin patterns in 3D images obtained by confocal laser scanning microscopy, and as a proof of principle we showed that these features may be clinically useful for analysis of prostate neoplasia.

Cell Nucleus↗