Molecular Image Analysis: Quantitative Description and Classification of the Nuclear Lamina in Human Mesenchymal Stem Cells

The nuclear lamina is an intermediate filament network that provides a structural framework for the cell nucleus. Changes in lamina structure are found during changes in cell fate such as cell division or cell death and are associated with human diseases. An unbiased method that quantifies changes in lamina shape can provide information on cells undergoing changes in cellular functions. We have developed an image processing methodology that finds and quantifies the 3D structure of the nuclear lamina. We show that measurements on such images can be used for cell classification and provide information concerning protein spatial localization in this structure. To demonstrate the efficacy of this method, we compared the lamina of unmanipulated human mesenchymal stem cells (hMSCs) at passage 4 to cells activated for apoptosis. A statistically significant classification was found between the two populations

Robust nuclear lamina-based cell classification of aging and senescent cells

Changes in the shape of the nuclear lamina are exhibited in senescent cells, as well as in cells expressing mutations in lamina genes. To identify cells with defects in the nuclear lamina we developed an imaging method that quantifies the intensity and curvature of the nuclear lamina. We show that this method accurately describes changes in the nuclear lamina. Spatial changes in nuclear lamina coincide with redistribution of lamin A proteins and local reduction in protein mobility in senescent cell. We suggest that local accumulation of lamin A in the nuclear envelope leads to bending of the structure. A quantitative distinction of the nuclear lamina shape in cell populations was found between fresh and senescent cells, and between primary myoblasts from young and old donors. Moreover, with this method mutations in lamina genes were significantly distinct from cells with wild-type genes. We suggest that this method can be applied to identify abnormal cells during aging, in in vitro propagation, and in lamina disorders

Segmentation and analysis of the three-dimensional redistribution of nuclear components in human mesenchymal stem cells

To better understand the impact of changes in nuclear architecture on nuclear functions, it is essential to quantitatively elucidate the three-dimensional organization of nuclear components using image processing tools. We have developed a novel image segmentation method, which involves a contrast enhancement and a subsequent thresholding step. In addition, we have developed a new segmentation method of the nuclear volume using the fluorescent background signal of a probe. After segmentation of the nucleus, a first-order normalization is performed on the signal positions of the component of interest to correct for the shape of the nucleus. This method allowed us to compare various signal positions within a single nucleus, and also on pooled data obtained from multiple nuclei, which may vary in size and shape. The algorithms have been tested by analyzing the spatial localization of nuclear bodies in relation to the nuclear center. Next, we used this new tool to study the change in the spatial distribution of nuclear components in cells before and after caspase-8 activation, which leads to cell death. Compared to the morphological TopHat method, this method gives similar but significantly faster results. A clear shift in the radial distribution of centromeres has been found, while the radial distribution of telomeres was changed much less. In addition, we have used this new tool to follow changes in the spatial distribution of two nuclear components in the same nucleus during activation of apoptosis. We show that after caspase-8 activation, when centromeres shift to a peripheral localization, the spatial distribution of PML-NBs does not change while that of centromeres did. We propose that the use of this new image segmentation method will contribute to a better understanding of the 3D spatial organization of the cell nucleus

Quantitative comparison of PET and Bremsstrahlung SPECT for imaging the in vivo yttrium-90 microsphere distribution after liver radioembolization.

BackgroundAfter yttrium-90 ((90)Y) microsphere radioembolization (RE), evaluation of extrahepatic activity and liver dosimetry is typically performed on (90)Y Bremsstrahlung SPECT images. Since these images demonstrate a low quantitative accuracy, (90)Y PET has been suggested as an alternative. The aim of this study is to quantitatively compare SPECT and state-of-the-art PET on the ability to detect small accumulations of (90)Y and on the accuracy of liver dosimetry.Methodology/principal findingsSPECT/CT and PET/CT phantom data were acquired using several acquisition and reconstruction protocols, including resolution recovery and Time-Of-Flight (TOF) PET. Image contrast and noise were compared using a torso-shaped phantom containing six hot spheres of various sizes. The ability to detect extra- and intrahepatic accumulations of activity was tested by quantitative evaluation of the visibility and unique detectability of the phantom hot spheres. Image-based dose estimates of the phantom were compared to the true dose. For clinical illustration, the SPECT and PET-based estimated liver dose distributions of five RE patients were compared. At equal noise level, PET showed higher contrast recovery coefficients than SPECT. The highest contrast recovery coefficients were obtained with TOF PET reconstruction including resolution recovery. All six spheres were consistently visible on SPECT and PET images, but PET was able to uniquely detect smaller spheres than SPECT. TOF PET-based estimates of the dose in the phantom spheres were more accurate than SPECT-based dose estimates, with underestimations ranging from 45% (10-mm sphere) to 11% (37-mm sphere) for PET, and 75% to 58% for SPECT, respectively. The differences between TOF PET and SPECT dose-estimates were supported by the patient data.Conclusions/significanceIn this study we quantitatively demonstrated that the image quality of state-of-the-art PET is superior over Bremsstrahlung SPECT for the assessment of the (90)Y microsphere distribution after radioembolization

The nuclear lamina promotes telomere aggregation and centromere peripheral localization during senescence of human mesenchymal stem cells\ud

Ex vivo, human mesenchymal stem cells (hMSCs) undergo spontaneous cellular senescence after a limited number of cell divisions. Intranuclear structures of the nuclear lamina were formed in senescent hMSCs, which are identified by the presence of Hayflick-senescence-associated factors. Notably, spatial changes in lamina shape were observed before the Hayflick senescence-associated factors, suggesting that the lamina morphology can be used as an early marker to identify senescent cells. Here, we applied quantitative image-processing tools to study the changes in nuclear architecture during cell senescence. We found that centromeres and telomeres colocalised with lamina intranuclear structures, which resulted in a preferred peripheral distribution in senescent cells. In addition, telomere aggregates were progressively formed during cell senescence. Once formed, telomere aggregates showed colocalization with -H2AX but not with TERT, suggesting that telomere aggregates are sites of DNA damage. We also show that telomere aggregation is associated with lamina intranuclear structures, and increased telomere binding to lamina proteins is found in cells expressing lamina mutants that lead to increases in lamina intranuclear structures. Moreover, three-dimensional image processing revealed spatial overlap between telomere aggregates and lamina intranuclear structures. Altogether, our data suggest a mechanical link between changes in lamina spatial organization and the formation of telomere aggregates during senescence of hMSCs, which can possibly contribute to changes in nuclear activity during cell senescence. \u

Visualization of the visibility and unique detectability results.

<p>The activity concentration in the hot spheres was 2.4 MBq ml⁻¹ for both the images without (rows 1–3) and with background activity (rows 4–6). In the 1^st and 4^th row, the SPECT+PSF (1^st and 3^rd column) and PET+PSF+TOF (2^nd and 4^th column) slices are overlaid with the location of the visible phantom spheres (red). In rows 2, 3, 5 and 6 a background slice is overlaid with the location of false positive regions. For illustrative reasons, only the largest false positive ROIs are shown (red: 10 mm; green: 13 mm; blue: 17 mm; yellow: 22 mm; purple: 37 mm). Clustered ROIs with connecting center voxels are represented by the ROI with the highest υ_TEST-FP value.</p

Phantom dosimetry.

<p>CDVH of the phantom background ROI and the ROI of the 37-mm diameter sphere. The presented doses were not corrected for PVE.</p