Focus: A Multifaceted Battle Against Cancer: Extracting Knowledge from Chemical Imaging Data Using Computational Algorithms for Digital Cancer Diagnosis

Fourier transform infrared (FTIR) spectroscopic imaging is an emerging microscopy modality for clinical histopathologic diagnoses as well as for biomedical research. Spectral data recorded in this modality are indicative of the underlying, spatially resolved biochemical composition but need computerized algorithms to digitally recognize and transform this information to a diagnostic tool to identify cancer or other physiologic conditions. Statistical pattern recognition forms the backbone of these recognition protocols and can be used for highly accurate results. Aided by biochemical correlations with normal and diseased states and the power of modern computer-aided pattern recognition, this approach is capable of combating many standing questions of traditional histology-based diagnosis models. For example, a simple diagnostic test can be developed to determine cell types in tissue. As a more advanced application, IR spectral data can be integrated with patient information to predict risk of cancer, providing a potential road to precision medicine and personalized care in cancer treatment. The IR imaging approach can be implemented to complement conventional diagnoses, as the samples remain unperturbed and are not destroyed. Despite high potential and utility of this approach, clinical implementation has not yet been achieved due to practical hurdles like speed of data acquisition and lack of optimized computational procedures for extracting clinically actionable information rapidly. The latter problem has been addressed by developing highly efficient ways to process IR imaging data but remains one that has considerable scope for progress. Here, we summarize the major issues and provide practical considerations in implementing a modified Bayesian classification protocol for digital molecular pathology. We hope to familiarize readers with analysis methods in IR imaging data and enable researchers to develop methods that can lead to the use of this promising technique for digital diagnosis of cancer.     

Structural changes in the innercortex cells of soybean root nodules are induced by short-term exposure to high salt or oxygen concentrations

After a 2 h exposure of intact soybean nodules to high concentrations of NaCl (100mol m_?3) or oxygen (8OkPa O₂), morphometric computations carried out using an image analysis technique on semi-thin sections showed that both treatments induced a decrease in the area of the inner-cortex cells, which were then characterized by a tangential elongation. In contrast, no significant change in area occurred in the middle-cortex cells although their elongation decreased. Electron microscopic observations showed that in the inner-cortex cells changes included the presence of wall infoldings, an enlarged periplasmic space and a lobate nucleus whose chromatin distribution differed from that of the control. Structural changes also occurred in the endoplasmic reticulum, microbodies, mitochondria and plastids. From several of these changes, which are similar to those noted in osmocontractil cells in response to external stimuli, it can be hypothesized that the inner cortex may provide a potential mechanism for the control of oxygen diffusion through the nodules.     

Automatic detection of pulmonary nodules in CT images by incorporating 3D tensor filtering with local image feature analysis

Computer-aided detection (CAD) technology has been developed and demonstrated its potential to assist radiologists in detecting pulmonary nodules especially at an early stage. In this paper, we present a novel scheme for automatic detection of pulmonary nodules in CT images based on a 3D tensor filtering algorithm and local image feature analysis. We first apply a series of preprocessing steps to segment the lung volume and generate the isotropic volumetric CT data. Next, a unique 3D tensor filtering approach and local image feature analysis are used to detect nodule candidates. A 3D level set segmentation method is used to correct and refine the boundaries of nodule candidates subsequently. Then, we extract the features of the detected candidates and select the optimal features by using a CFS (Correlation Feature Selection) subset evaluator attribute selection method. Finally, a random forest classifier is trained to classify the detected candidates. The performance of this CAD scheme is validated using two datasets namely, the LUNA16 (Lung Nodule Analysis 2016) database and the ANODE09 (Automatic Nodule Detection 2009) database. By applying a 10-fold cross-validation method, the CAD scheme yielded a sensitivity of 79.3% at an average of 4 false positive detections per scan (FP/Scan) for the former dataset, and a sensitivity of 84.62% and 2.8 FP/Scan for the latter dataset, respectively. Our detection results show that the use of 3D tensor filtering algorithm combined with local image feature analysis constitutes an effective approach to detect pulmonary nodules.     

Validation of a deformable image registration produced by a commercial treatment planning system in head and neck

In recent years one of the areas of interest in radiotherapy has been adaptive radiation therapy (ART), with the most efficient way of performing ART being the use of deformable image registration (DIR). In this paper we use the distances between points of interest (POIs) in the computed tomography (CT) and the cone beam computed tomography (CBCT) acquisition images and the inverse consistence (IC) property to validate the RayStation treatment planning system (TPS) DIR algorithm. This study was divided into two parts: Firstly the distance-accuracy of the TPS DIR algorithm was ascertained by placing POIs on anatomical features in the CT and CBCT images from five head and neck cancer patients. Secondly, a method was developed for studying the implication of these distances on the dose by using the IC. This method compared the dose received by the structures in the CT, and the structures that were quadruply-deformed. The accuracy of the TPS was 1.7 ± 0.8 mm, and the distance obtained with the quadruply-deformed IC method was 1.7 ± 0.9 mm, i.e. the difference between the IC method multiplied by two, and that of the TPS validation method, was negligible. Moreover, the IC method shows very little variation in the dose-volume histograms when comparing the original and quadruply-deformed structures. This indicates that this algorithm is useful for planning adaptive radiation treatments using CBCT in head and neck cancer patients, although these variations must be taken into account when making a clinical decision to adapt a treatment plan.     

Studies on the Macronuclei of Doublet Paramecium tetraurelia: Distribution of Macronuclei and DNA at Fission*

SYNOPSIS. Doublet Paramecium tetraurelia would be expected to contain 2 macronuclei if their nuclear complement were strictly analogous to that of singlets. However, most doublets are unimacronucleate. It is shown in this study that dimacronucleate cells are present only in young clones. Unimacronucleate cells arise either through abnormalities in the determination and distribution of macronuclear anlagen during the first cell cycle after conjugation, or from dimacronucleate cells through abnormal division and segregation of macronuclei during the fission process. When a change in the number of macronuclei occurs through abnormalities in the division and segregation of daughter macronuclei, the daughter cells produced typically have DNA contents more similar than those expected from either random segregation of daughter macronuclei, or from the normal segregation pattern in ciliates in which changes in the number of macronuclei in progeny cells do not occur. This suggests that part of the regulation process of macronuclear DNA content in Paramecium may occur through control of the segregation pattern of daughter macronuclei.     

Classification and Reconstruction of a Heterogeneous Set of Electron Microscopic Images: A Case Study of GroEL–Substrate Complexes

Image analysis methods were used to separate images of a large macromolecular complex, the chaperonin GroEL, in a preparation in which it is partially liganded to a nonnative protein substrate, glutamine synthetase. The relatively small difference (6%) in size between the chaperonin in its free and complexed forms, and the absence of gross changes in overall conformation, made separation of the two types of particles challenging. Different approaches were evaluated and used for alignment and classification of images, both in two common projections and in three dimensions, yielding 2D averages and a 3D reconstruction. The results of 3D analysis describe the conformational changes effected by binding of this particular protein substrate and demonstrate the utility of 2D analysis as an indicator of structural change in this system.     

Reproductive biology and pollinators in two enantiostylous Qualea species (Vochysiaceae) in the Brazilian Cerrado

• Enantiostyly is a floral polymorphism in which two floral forms in the same species differ in deflection of the stigma to right or left position. In monomorphic enantiostylous plants, flowers of the two morphs occur within the same individual, usually in the same proportion. In self‐compatible species the function of monomorphic enantiostyly is proposed to increase outcrossing rates and offer a reproductive advantage under pollination limitation. Enantiostylous species are usually self‐compatible and show heteranthery, with poricide anthers and pollen as pollinator reward; however, there are families, such as Vochysiaceae, that have different characteristics.
• We analysed the reproductive system and pollination biology of Qualea parviflora and Q. multiflora, two enantiostylous species from the Brazilian Cerrado that have specific morphological and physiological traits. For this, we characterized flower traits, performed hand pollinations and studied floral visitors.
• We found no differences between morphs in the proportion of flowers, nectar produced or its concentration, pollen quantity and fruit set. Both species were self‐incompatible and quite generalist regarding floral visitors.
• Enantiostyly in self‐incompatible plants seems to confer a reproductive advantage by reducing self‐interference resulting from stigma clogging. This novel result helps to expand our knowledge on this complex floral polymorphism and opens new avenues for future research on this topic.

     

In vitro dynamics of chromatin organization and migration

The organization of eukaryotic chromatin is not static but changes as a function of cell status during processes such as proliferation, differentiation, and migration. DNA quantification has not been used extensively to investigate chromatin dynamics in combination with cellular migration. In this context, an optimized DNA-specific, nonperturbant method has been developed for studying chromatin organization, using the fluorescent vital bisbenzimidazole probe Hoechst 33342: this property has been described by Hamori et al. (1980). Computer-assisted image analysis was used to follow migratory activity and chromatin organization of L929 fibroblasts during in vitro wound healing. Cell movements were analyzed using an optical flow technique, which consists in the calculation of the velocity field of cells and nuclear movements in the frame. This system allows the correlation of cell migration and position in the cell cycle. It makes it possible to study chromatin dynamics using a quantitative analysis of nuclear differentiation reorganization (nuclear texture) and to correlate this with migration characteristics. The present system would be of interest for studying cell-extracellular matrix interactions using differing substrates, and also the migratory response to chemotactic factors. Such a model is a prerequisite for gaining better understanding of drug action.