Specific Tissues Research Articles

Fibroblasts and polymer composition are essential for bioengineering of airway epithelium on nonwoven scaffolds

To make tissue engineering a truly effective tool, it is necessary to understand how the patterns of specific tissue development are modulated by and depend on the artificial environment. Even the most advanced approaches still do not fully meet the requirements of practical engineering of tracheobronchial epithelium. This study aimed to test the ability of the synthetic and natural nonwoven scaffolds to support the formation of morphological sound airway epithelium including the basement membrane (BM). We also sought to identify the potential role of fibroblasts in this process. Our results showed that nonwoven scaffolds are generally suitable for producing well-differentiated tracheobronchial epithelium (with cilia and goblet cells), while the structure and functionality of the equivalents appeared to be highly dependent on the composition of the scaffolds. Unlike natural scaffolds, synthetic ones supported the formation of the epithelium only when epithelial cells were cocultured with fibroblasts. Fibroblasts also appeared to be obligatory for basal lamina formation, regardless of the type of the nonwoven material used. However, even in the presence of fibroblasts, the synthetic scaffolds were unable to support the formation of the epithelium and of the BM (in particular, basal lamina) as effectively as the natural scaffolds did.

Evolution of two-pore domain potassium channels and their gene expression in zebrafish embryos.

The two-pore domain potassium (K2P) channels are a major type of potassium channels that maintain the cell membrane potential by conducting passive potassium leak currents independent of voltage change. They play prominent roles in multiple physiological processes, including neuromodulation, perception of pain, breathing and mood control, and response to volatile anesthetics. Mutations in K2P channels have been linked to many human diseases, such as neuronal and cardiovascular disorders and cancers. Significant progress has been made to understand their protein structures, physiological functions, and pharmacological modifiers. However, their expression and function during embryonic development remain largely unknown. We employed the zebrafish model and identified 23 k2p genes using BLAST search and gene cloning. We first analyzed vertebrate K2P channel evolution by phylogenetic and syntenic analyses. Our data revealed that the six subtypes of the K2P genes have already evolved in invertebrates long before the emergence of vertebrates. Moreover, the vertebrate K2P gene number increased, most likely due to two whole-genome duplications. Furthermore, we examined zebrafish k2p gene expression during early embryogenesis by in situ hybridization. Each subgroup's genes showed similar but distinct gene expression domains with some exceptions. Most of them were expressed in neural tissues consistent with their known function of neural excitability regulation. However, a few k2p genes were expressed temporarily in specific tissues or organs, suggesting that these K2P channels may be needed for embryonic development. Our phylogenetic and developmental analyses of K2P channels shed light on their evolutionary history and potential roles during embryogenesis related to their physiological functions and human channelopathies.

Changes in Expression of Key Genes in Alzheimer's Disease: A Specific Brain Tissue Change.

Alzheimer's disease (AD) is an irreversible and neurodegenerative disorder. Its etiology is not clear, but the involvement of genetic components plays a central role in the onset of the disease. In the present study, the expression of 10 genes (APP, PS1 and PS2, APOE, APBA2, LRP1, GRIN2B, INSR, GJB1, and IDE) involved in the main pathways related to AD were analyzed in auditory cortices and cerebellum from 29 AD patients and 29 healthy older adults. Raw analysis revealed tissue-specific changes in genes LRP1, INSR, and APP. A correlation analysis showed a significant effect also tissue-specific AD in APP, GRIN2B, INSR, and LRP1. Furthermore, the E4 allele of the APOE gene revealed a significant correlation with change expression tissue-specific in ABPA2, APP, GRIN2B, LRP1, and INSR genes. To assess the existence of a correction between changes in target gene expression and a probability of AD in each tissue (auditory cortices and cerebellum) an analysis of the effect of expressions was realized and showed that the reduction in the expression of the APP in auditory cortex and GRIN2B cerebellum had a significant effect in increasing the probability of AD, in the same logic, our result also suggesting that increased expression of the LRP1 and INSR genes had a significant effect on increasing the probability of AD. Our results showed tissue-specific gene expression alterations associated with AD and certainly opened new perspectives to characterize factors involved in gene regulation and to obtain possible biomarkers for AD.

Gene expression variation underlying tissue-specific responses to copper stress in Drosophila melanogaster.

Copper is one of a handful of biologically necessary heavy metals that is also a common environmental pollutant. Under normal conditions, copper ions are required for many key physiological processes. However, in excess, copper results in cell and tissue damage ranging in severity from temporary injury to permanent neurological damage. Because of its biological relevance, and because many conserved copper-responsive genes respond to nonessential heavy metal pollutants, copper resistance in Drosophila melanogaster is a useful model system with which to investigate the genetic control of the heavy metal stress response. Because heavy metal toxicity has the potential to differently impact specific tissues, we genetically characterized the control of the gene expression response to copper stress in a tissue-specific manner in this study. We assessed the copper stress response in head and gut tissue of 96 inbred strains from the Drosophila Synthetic Population Resource using a combination of differential expression analysis and expression quantitative trait locus mapping. Differential expression analysis revealed clear patterns of tissue-specific expression. Tissue and treatment specific responses to copper stress were also detected using expression quantitative trait locus mapping. Expression quantitative trait locus associated with MtnA, Mdr49, Mdr50, and Sod3 exhibited both genotype-by-tissue and genotype-by-treatment effects on gene expression under copper stress, illuminating tissue- and treatment-specific patterns of gene expression control. Together, our data build a nuanced description of the roles and interactions between allelic and expression variation in copper-responsive genes, provide valuable insight into the genomic architecture of susceptibility to metal toxicity, and highlight candidate genes for future functional characterization.

Exploratory study of cold hypersensitivity in Japanese women: genetic associations and somatic symptom burden

Temperature perception is essential for humans to discern the environment and maintain homeostasis. However, some individuals experience cold hypersensitivity, characterized by a subjective feeling of coldness despite ambient environmental temperatures being normal, the underlying mechanisms of which are unknown. In this study, we aimed to investigate the relationship between subjective cold symptoms and somatic burden or single nucleotide polymorphisms to understand the causes of cold hypersensitivity. We conducted an online questionnaire survey [comprising 30 questions, including past medical history, subjective symptoms of cold hypersensitivity, and the Somatic Symptom Scale-8 (SSS-8)]. Respondents were 1200 Japanese adult female volunteers (age: 20–59 years), recruited between April 21 and May 25, 2022, who were customers of MYCODE, a personal genome service in Japan. Among the 1111 participants, 599 (54%) reported cold hypersensitivity. Higher cold hypersensitivity severity was positively associated with the SSS-8 scores. Additionally, a genome-wide association study for cold hypersensitivity was conducted using array-based genomic data obtained from genetic testing. We identified 11 lead variants showing suggestive associations (P < 1 × 10–5) with cold hypersensitivity, some of which showed a reasonable change in expression in specific tissues in the Genotype-Tissue Expression database. The study findings shed light on the underlying causes of cold hypersensitivity.

In vitro culture and tissue-derived specific expression of melanocytes from ovary of adult Silky Fowl

BackgroundThe presence of a significant number of melanocytes in the ovary and follicular membrane of Silky Fowl suggests their potential involvement in follicle development. Currently, there is a lack of available data regarding to the isolation of primary melanocytes from adult chickens. To date, primary melanocytes and their in vitro culture system have been successfully conducted in the peritoneum of chicken embryos. Herein, melanocytes from silky fowl ovaries were isolated and identified. MethodsSilky Fowl ovaries were obtained by mixed digestion of 0.1% collagenase II and 0.25% trypsin-EDTA. Melanocytes could be further purified and cultured up to five generations in vitro. RNA-seq analysis was used to investigate whether there were differences in the functional status of melanocytes in different tissues and developmental stages. ResultsConsequently, differential gene expressions between peritoneal and ovarian melanocytes were compared. These findings demonstrated that the Silky Fowl ovary had higher expression levels of genes involved in the production of sexual hormones and melanogenesis, while those of melanocytes derived from the peritoneum were involved in amino acid metabolism, lipid synthesis, and overall metabolic rates. This suggests that the role of melanocytes is dependent on the origin tissue and developmental stage, and is tightly connected to the function of the specific source tissue from which the cells were derived. ConclusionsThis study provides a method for isolating adult melanocytes and serve as a basis for further investigate the effect of SFOM on germ cells.

Stimuli-responsive hydrogel based on natural polymers for breast cancer.

Aims: Breast cancer is the most common malignancy among women in both high- and low-resource settings. Conventional breast cancer therapies were inefficient and had low patient compliance. Stimuli-responsive hydrogels possessing similar physicochemical features as soft tissue facilitate diagnostic and therapeutic approaches for breast cancer subtypes. Scope: Polysaccharides and polypeptides are major natural polymers with unique biocompatibility, biodegradability, and feasible modification approaches utilized frequently for hydrogel fabrication. Alternating the natural polymer-based hydrogel properties in response to external stimuli such as pH, temperature, light, ultrasonic, enzyme, glucose, magnetic, redox, and electric have provided great potential for the evolution of novel drug delivery systems (DDSs) and various advanced technologies in medical applications. Stimuli-responsive hydrogels are triggered by specific cancer tissue features, promote target delivery techniques, and modify release therapeutic agents at localized sites. This narrative review presented innovation in preparing and characterizing the most common stimuli-responsive natural polymer-based hydrogels for diagnostic and therapeutic applications in the breast cancer area. Conclusion: Stimuli-responsive hydrogels display bioinspiration products as DDSs for breast cancer subtypes, protect the shape of breast tissue, provide modified drug release, enhance therapeutic efficacy, and minimize chemotherapy agents' side effects. The potential benefits of smart natural polymer-based hydrogels make them an exciting area of practice for breast cancer diagnosis and treatment.

Best practices for the execution, analysis, and data storage of plant single-cell/nucleus transcriptomics.

Single-cell and single-nucleus RNA-sequencing technologies capture the expression of plant genes at an unprecedented resolution. Therefore, these technologies are gaining traction in plant molecular and developmental biology for elucidating the transcriptional changes across cell types in a specific tissue or organ, upon treatments, in response to biotic and abiotic stresses, or between genotypes. Despite the rapidly accelerating use of these technologies, collective and standardized experimental and analytical procedures to support the acquisition of high-quality data sets are still missing. In this commentary, we discuss common challenges associated with the use of single-cell transcriptomics in plants and propose general guidelines to improve reproducibility, quality, comparability, and interpretation and to make the data readily available to the community in this fast-developing field of research.

Analysis of organoid and immune cell co-cultures by machine learning-empowered image cytometry.

Organoids are three-dimensional (3D) structures that can be derived from stem cells or adult tissue progenitor cells and exhibit an extraordinary ability to autonomously organize and resemble the cellular composition and architectural integrity of specific tissue segments. This feature makes them a useful tool for analyzing therapeutical relevant aspects, including organ development, wound healing, immune disorders and drug discovery. Most organoid models do not contain cells that mimic the neighboring tissue’s microenvironment, which could potentially hinder deeper mechanistic studies. However, to use organoid models in mechanistic studies, which would enable us to better understand pathophysiological processes, it is necessary to emulate the in situ microenvironment. This can be accomplished by incorporating selected cells of interest from neighboring tissues into the organoid culture. Nevertheless, the detection and quantification of organoids in such co-cultures remains a major technical challenge. These imaging analysis approaches would require an accurate separation of organoids from the other cell types in the co-culture. To efficiently detect and analyze 3D organoids in co-cultures, we developed a high-throughput imaging analysis platform. This method integrates automated imaging techniques and advanced image processing tools such as grayscale conversion, contrast enhancement, membrane detection and structure separation. Based on machine learning algorithms, we were able to identify and classify 3D organoids within dense co-cultures of immune cells. This procedure allows a high-throughput analysis of organoid-associated parameters such as quantity, size, and shape. Therefore, the technology has significant potential to advance contextualized research using organoid co-cultures and their potential applications in translational medicine.

Transcriptional profile of ribosome-associated quality control components and their associated phenotypes in mammalian cells

During protein synthesis, organisms detect translation defects that induce ribosome stalling and result in protein aggregation. The Ribosome-associated Quality Control (RQC) complex, comprising TCF25, LTN1, and NEMF, is responsible for identifying incomplete protein products from unproductive translation events, targeting them for degradation. Although RQC disruption causes adverse effects on vertebrate neurons, data regarding mRNA/protein expression and regulation across tissues are lacking. Employing high-throughput methods, we analyzed public datasets to explore RQC gene expression and phenotypes. Our findings revealed widespread expression of RQC components in human tissues; however, silencing of RQC yielded only mild negative effects on cell growth. Notably, TCF25 exhibited elevated mRNA levels that were not reflected in the protein content. We experimentally demonstrated that this disparity arose from post-translational protein degradation by the proteasome. Additionally, we observed that cellular aging marginally influenced RQC expression, leading to reduced mRNA levels in specific tissues. Our results suggest the necessity of RQC expression in all mammalian tissues. Nevertheless, when RQC falters, alternative mechanisms seem to compensate, ensuring cell survival under nonstress conditions.

Accurate Intervertebral Disc Segmentation Approach Based on Deep Learning.

Automatically segmenting specific tissues or structures from medical images is a straightforward task for deep learning models. However, identifying a few specific objects from a group of similar targets can be a challenging task. This study focuses on the segmentation of certain specific intervertebral discs from lateral spine images acquired from an MRI scanner. In this research, an approach is proposed that utilizes MultiResUNet models and employs saliency maps for target intervertebral disc segmentation. First, a sub-image cropping method is used to separate the target discs. This method uses MultiResUNet to predict the saliency maps of target discs and crop sub-images for easier segmentation. Then, MultiResUNet is used to segment the target discs in these sub-images. The distance maps of the segmented discs are then calculated and combined with their original image for data augmentation to predict the remaining target discs. The training set and test set use 2674 and 308 MRI images, respectively. Experimental results demonstrate that the proposed method significantly enhances segmentation accuracy to about 98%. The performance of this approach highlights its effectiveness in segmenting specific intervertebral discs from closely similar discs.

Tissue clearing and its applications in human tissues: A review

AbstractIn three‐dimensional (3D) space, an unbiased and systemic view of human specimens between structures and functions is required. However, conventional histological sections from specimens have made only limited progress in exploring intact information about 3D biological tissues. With significant advances in optical physics and chemical engineering, state‐of‐the‐art tissue‐clearing methods can revolutionize the intact subcellular level of human tissue histological analysis, from thick human tissues to intact human organs. The present review summarizes the principle of tissue clearing so that a trainee researcher can implement effective human tissue‐clearing protocols. Furthermore, this review highlights existing tissue‐clearing methods in specific human tissue applications, describes imaging strategies, and presents various efficient computational approaches for processing and visualizing large image data. Finally, potential future directions for developing tissue‐clearing methods for human tissues are also discussed.

Fat Matters: Exploring Cancer Risk through the Lens of Computed Tomography and Visceral Adiposity.

Obesity is an established risk factor for cancer. However, conventional measures like body mass index lack precision in assessing specific tissue quantities, particularly of the two primary abdominal fat compartments, visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT). Computed tomography (CT) stands as the gold standard for precisely quantifying diverse tissue types. VAT, distinguished by heightened hormonal and metabolic activity, plays a pivotal role in obesity-related tumor development. Excessive VAT is linked to aberrant secretion of adipokines, proinflammatory cytokines, and growth factors, fostering the carcinogenesis of obesity-related tumors. Accurate quantification of abdominal fat compartments is crucial for understanding VAT as an oncological risk factor. The purpose of the present research is to elucidate the role of CT, performed for staging purposes, in assessing VAT (quantity and distribution) as a critical factor in the oncogenesis of obesity-related tumors. In the field of precision medicine, this work takes on considerable importance, as quantifying VAT in oncological patients becomes fundamental in understanding the influence of VAT on cancer development-the potential "phenotypic expression" of excessive VAT accumulation. Previous studies analyzed in this research showed that VAT is a risk factor for clear cell renal cell carcinoma, non-clear cell renal cell carcinoma, prostate cancer, and hepatocarcinoma recurrence. Further studies will need to quantify VAT in other oncological diseases with specific mutations or gene expressions, in order to investigate the relationship of VAT with tumor genomics.

Uncovering the essential roles of glutamate carboxypeptidase 2 orthologs in Caenorhabditis elegans.

Human glutamate carboxypeptidase 2 (GCP2) from the M28B metalloprotease group is an important target for therapy in neurological disorders and an established tumor marker. However, its physiological functions remain unclear. To better understand general roles, we used the model organism Caenorhabditis elegans to genetically manipulate its three existing orthologous genes and evaluate the impact on worm physiology. The results of gene knockout studies showed that C. elegans GCP2 orthologs affect the pharyngeal physiology, reproduction, and structural integrity of the organism. Promoter-driven GFP expression revealed distinct localization for each of the three gene paralogs, with gcp-2.1 being most abundant in muscles, intestine, and pharyngeal interneurons, gcp-2.2 restricted to the phasmid neurons, and gcp-2.3 located in the excretory cell. The present study provides new insight into the unique phenotypic effects of GCP2 gene knockouts in C. elegans, and the specific tissue localizations. We believe that elucidation of particular roles in a non-mammalian organism can help to explain important questions linked to physiology of this protease group and in extension to human GCP2 involvement in pathophysiological processes.

Size-dependent vector effect of microplastics on the bioaccumulation of polychlorinated biphenyls in tilapia: A tissue-specific study

Microplastics play a significant role in interactions between organisms and hydrophobic organic contaminants (HOCs), leading to a joint toxic effect on aquatic organisms. This study extensively investigated the tissue-specific accumulation of polychlorinated biphenyls (PCBs) resulting from different sized microplastics in tilapia (Oreochromis mossambicus) using a passive dosing device. Based on biological feeding behavior considerations, 1 mm and 2 μm polystyrene (PS) microplastics with concentrations of 2 and 5 mg L−1 were investigated. A physiologically based toxicokinetic (PBTK) model was applied to evaluate the exchange kinetics and fluxes among the tissues. Moreover, an in vitro simulation experiment was conducted to theoretically validate the vector effect. The findings demonstrated that the effects caused by HOCs and microplastics on organisms were influenced by multiple factors such as size and surface properties. The mass transfer kinetics of HOCs in specific tissues were closely related to their adsorption capacity and position microplastics could reach. Specifically, although 2 μm microplastics exhibited high adsorption capacity for PCBs, they were only retained in the intestines and did not significantly contribute to the bioaccumulation of PCBs in gills or muscle. While 1 mm microplastics were ingested but just paused in the mouth and subsequently flew through the gills with oral mucus. Their vector effects increased the desorption of microplastic-bound PCB-118 in the gill mucus microcosm, thereby facilitating the mass transfer and accumulation of PCB-118 in gills and muscle. This study sheds new light on how the size-dependent vector generated by microplastics affects the tissue-specific accumulation of HOCs in aquatic organisms.

Brown adipose tissue CoQ deficiency activates the integrated stress response and FGF21-dependent mitohormesis

Coenzyme Q (CoQ) is essential for mitochondrial respiration and required for thermogenic activity in brown adipose tissues (BAT). CoQ deficiency leads to a wide range of pathological manifestations, but mechanistic consequences of CoQ deficiency in specific tissues, such as BAT, remain poorly understood. Here, we show that pharmacological or genetic CoQ deficiency in BAT leads to stress signals causing accumulation of cytosolic mitochondrial RNAs and activation of the eIF2α kinase PKR, resulting in activation of the integrated stress response (ISR) with suppression of UCP1 but induction of FGF21 expression. Strikingly, despite diminished UCP1 levels, BAT CoQ deficiency displays increased whole-body metabolic rates at room temperature and thermoneutrality resulting in decreased weight gain on high-fat diets (HFD). In line with enhanced metabolic rates, BAT and inguinal white adipose tissue (iWAT) interorgan crosstalk caused increased browning of iWAT in BAT-specific CoQ deficient animals. This mitohormesis-like effect depends on the ATF4-FGF21 axis and BAT-secreted FGF21, revealing an unexpected role for CoQ in the modulation of whole-body energy expenditure with wide-ranging implications for primary and secondary CoQ deficiencies.

Outcome on Mesenteric Mass Response of Small-Intestinal Neuroendocrine Tumors Treated by 177Lu-DOTATATE Peptide Receptor Radionuclide Therapy: The MesenLuth Study, a National Study from the French Group of Endocrine Tumors and Endocan-RENATEN Network.

A mesenteric mass (MM), characterized by fibrotic reaction, is present in most small-intestinal neuroendocrine tumors (SI-NETs). 177Lu-DOTATATE peptide receptor radionuclide therapy (PRRT) has shown its efficacy in patients with progressive SI-NETs. However, because of specific tissue characteristics of desmoplastic MMs, we hypothesize that these lesions may be refractory to 177Lu-DOTATATE PRRT. Methods: From the national French Groupe d'étude des Tumeurs Endocrines database, we identified patients with an advanced SI-NET and a MM (≥2 cm with a retractile aspect) of a SI-NET treated by at least 1 course of 177Lu-DOTATATE PRRT. The primary endpoint was a MM objective response rate (ORR) of less than 5%. Secondary endpoints were metabolic response, MM-related safety, and clinical response, as well as MM progression-free survival (PFS) and non-MM PFS. Results: In total, 52 patients were included. The MM ORR was 4% (n = 2), and the non-MM ORR was 8% (n = 4). No patient had a MM metabolic response, and the non-MM metabolic response rate was 12% (n = 6). Among the 26 patients with baseline MM-related symptoms, 46% had a clinical response. Four patients presented with gastrointestinal complications during PRRT. The median MM-related PFS was not reached, and the non-MM PFS was 50.3 mo (95% CI, 38.2-61.7 mo). Conclusion: This study confirms that 177Lu-DOTATATE PRRT does not lead to morphologic response on MMs (ORR < 5%). However, it allows MM stability, with few MM-related side effects, and has a relevant impact on MM-related symptoms.

Genome-wide identification and expression profiling of photosystem II (PsbX) gene family in upland cotton (Gossypium hirsutum L)

BackgroundPhotosystem II (PSII) constitutes an intricate assembly of protein pigments, featuring extrinsic and intrinsic polypeptides within the photosynthetic membrane. The low-molecular-weight transmembrane protein PsbX has been identified in PSII, which is associated with the oxygen-evolving complex. The expression of PsbX gene protein is regulated by light. PsbX's central role involves the regulation of PSII, facilitating the binding of quinone molecules to the Qb (PsbA) site, and it additionally plays a crucial role in optimizing the efficiency of photosynthesis. Despite these insights, a comprehensive understanding of the PsbX gene's functions has remained elusive.ResultsIn this study, we identified ten PsbX genes in Gossypium hirsutum L. The phylogenetic analysis results showed that 40 genes from nine species were classified into one clade. The resulting sequence logos exhibited substantial conservation across the N and C terminals at multiple sites among all Gossypium species. Furthermore, the orthologous/paralogous, Ka/Ks ratio revealed that cotton PsbX genes subjected to positive as well as purifying selection pressure might lead to limited divergence, which resulted in the whole genome and segmental duplication. The expression patterns of GhPsbX genes exhibited variations across specific tissues, as indicated by the analysis. Moreover, the expression of GhPsbX genes could potentially be regulated in response to salt, intense light, and drought stresses. Therefore, GhPsbX genes may play a significant role in the modulation of photosynthesis under adverse abiotic conditions.ConclusionWe examined the structure and function of PsbX gene family very first by using comparative genomics and systems biology approaches in cotton. It seems that PsbX gene family plays a vital role during the growth and development of cotton under stress conditions. Collectively, the results of this study provide basic information to unveil the molecular and physiological function of PsbX genes of cotton plants.

Determination of Alzheimer's disease based on morphology and atrophy using machine learning combined with automated segmentation.

To evaluate the degree of cerebral atrophy for Alzheimer's disease (AD), voxel-based morphometry has been performed with magnetic resonance imaging. Detailed morphological changes in a specific tissue area having the most evidence of atrophy were not considered by the machine-learning technique. To develop a machine-learning system that can capture morphology features for determination of atrophy of brain tissue in early-stage AD and classification of healthy participants or patients. Three-dimensional T1-weighted (3D-T1W) data were obtained from AD Neuroimaging Initiative (200 healthy controls and 200 patients with early-stage AD). Automated segmentation of 3D-T1W data was performed. Deep learning (DL) and support vector machine (SVM) were trained using 66-segmented volume values as input and AD diagnosis as output. DL was performed using 66 volume values or gray matter (GM) and white matter (WM) volume values. SVM learning was performed using 66 volume values and six regions with high variable importance. 3D convolutional neural network (3D-CNN) was trained using the segmented images. Accuracy and area under curve (AUC) were obtained. Variable importance was evaluated from logistic regression analysis. DL for GM and WM volume values, accuracy 0.6; SVM for all volume values, accuracy 0.82 and AUC 0.81; DL for all volume values, accuracy 0.82 and AUC 0.8; 3D-CNN using segmental images of the whole brain, accuracy 0.5 and AUC 0.51. SVM using volume values of six regions, accuracy 0.82; image-based 3D-CNN, highest accuracy 0.69. Our results show that atrophic features are more considerable than morphological features in the early detection of AD.

Comparison of Otsu and an adapted Chan–Vese method to determine thyroid active volume using Monte Carlo generated SPECT images

BackgroundThe Otsu method and the Chan–Vese model are two methods proven to perform well in determining volumes of different organs and specific tissue fractions. This study aimed to compare the performance of the two methods regarding segmentation of active thyroid gland volumes, reflecting different clinical settings by varying the parameters: gland size, gland activity concentration, background activity concentration and gland activity concentration heterogeneity.MethodsA computed tomography was performed on three playdough thyroid phantoms with volumes 20, 35 and 50 ml. The image data were separated into playdough and water based on Hounsfield values. Sixty single photon emission computed tomography (SPECT) projections were simulated by Monte Carlo method with isotope Technetium-99 m (^{text {99m}}Tc). Linear combinations of SPECT images were made, generating 12 different combinations of volume and background: each with both homogeneous thyroid activity concentration and three hotspots of different relative activity concentrations (48 SPECT images in total). The relative background levels chosen were 5 %, 10 %, 15 % and 20 % of the phantom activity concentration and the hotspot activities were 100 % (homogeneous case) 150 %, 200 % and 250 %. Poisson noise, (coefficient of variation of 0.8 at a 20 % background level, scattering excluded), was added before reconstruction was done with the Monte Carlo-based SPECT reconstruction algorithm Sahlgrenska Academy reconstruction code (SARec). Two different segmentation algorithms were applied: Otsu’s threshold selection method and an adaptation of the Chan–Vese model for active contours without edges; the results were evaluated concerning relative volume, mean absolute error and standard deviation per thyroid volume, as well as dice similarity coefficient.ResultsBoth methods segment the images well and deviate similarly from the true volumes. They seem to slightly overestimate small volumes and underestimate large ones. Different background levels affect the two methods similarly as well. However, the Chan–Vese model deviates less and paired t-testing showed significant difference between distributions of dice similarity coefficients (p-value <0.01).ConclusionsThe investigations indicate that the Chan–Vese model performs better and is slightly more robust, while being more challenging to implement and use clinically. There is a trade-off between performance and user-friendliness.