A Rapid Segmentation-Insensitive "Digital Biopsy" Method for Radiomic Feature Extraction: Method and Pilot Study Using CT Images of Non-Small Cell Lung Cancer.

Quantitative imaging approaches compute features within images' regions of interest. Segmentation is rarely completely automatic, requiring time-consuming editing by experts. We propose a new paradigm, called "digital biopsy," that allows for the collection of intensity- and texture-based features from these regions at least 1 order of magnitude faster than the current manual or semiautomated methods. A radiologist reviewed automated segmentations of lung nodules from 100 preoperative volume computed tomography scans of patients with non-small cell lung cancer, and manually adjusted the nodule boundaries in each section, to be used as a reference standard, requiring up to 45 minutes per nodule. We also asked a different expert to generate a digital biopsy for each patient using a paintbrush tool to paint a contiguous region of each tumor over multiple cross-sections, a procedure that required an average of <3 minutes per nodule. We simulated additional digital biopsies using morphological procedures. Finally, we compared the features extracted from these digital biopsies with our reference standard using intraclass correlation coefficient (ICC) to characterize robustness. Comparing the reference standard segmentations to our digital biopsies, we found that 84/94 features had an ICC >0.7; comparing erosions and dilations, using a sphere of 1.5-mm radius, of our digital biopsies to the reference standard segmentations resulted in 41/94 and 53/94 features, respectively, with ICCs >0.7. We conclude that many intensity- and texture-based features remain consistent between the reference standard and our method while substantially reducing the amount of operator time required

Synchrotron Microtomography and Neutron Radiography Characterization of the Microstruture and Water Absorption of Concrete from Pompeii

There is renewed interest in using advanced techniques to characterize ancient Roman concrete. In the present work, samples were drilled from the "Hospitium" in Pompeii and were analyzed by synchrotron microtomography (uCT) and neutron radiography to study how the microstructure, including the presence of induced cracks, affects their water adsorption. The water distribution and absorptivity were quantified by neutron radiography. The 3D crack propagation, pore size distribution and orientation, tortuosity, and connectivity were analyzed from uCT results using advanced imaging methods. The concrete characterization also included classical methods (e.g., differential thermal-thermogravimetric, X-ray diffractometry, and scanning electron microscopy). Ductile fracture patterns were observed once cracks were introduced. When compared to Portland cement mortar/concrete, Pompeii samples had relatively high porosity, low connectivity, and similar coefficient of capillary penetration. In addition, the permeability was predicted from models based on percolation theory and the pore structure data to evaluate the fluid transport properties

Optimizing SUV Analysis: A Multicenter Study on Preclinical FDG-PET/CT Highlights the Impact of Standardization

PURPOSE: Preclinical imaging, with translational potential, lacks a standardized method for defining volumes of interest (VOIs), impacting data reproducibility. The aim of this study was to determine the interobserver variability of VOI sizes and standard uptake values (SUV mean and SUV max) of different organs using the same [ 18F]FDG-PET and PET/CT datasets analyzed by multiple observers. In addition, the effect of a standardized analysis approach was evaluated. PROCEDURES: In total, 12 observers (4 beginners and 8 experts) analyzed identical preclinical [ 18F]FDG-PET-only and PET/CT datasets according to their local default image analysis protocols for multiple organs. Furthermore, a standardized protocol was defined, including detailed information on the respective VOI size and position for multiple organs, and all observers reanalyzed the PET/CT datasets following this protocol. RESULTS: Without standardization, significant differences in the SUV mean and SUV max were found among the observers. Coregistering CT images with PET images improved the comparability to a limited extent. The introduction of a standardized protocol that details the VOI size and position for multiple organs reduced interobserver variability and enhanced comparability. CONCLUSIONS: The protocol offered clear guidelines and was particularly beneficial for beginners, resulting in improved comparability of SUV mean and SUV max values for various organs. The study suggested that incorporating an additional VOI template could further enhance the comparability of the findings in preclinical imaging analyses. </p

Contrast-enhanced micro-computed tomography and image processing integrated approach for microstructural analysis of biological soft fibrous tissues

Nel sistema muscolo-scheletrico, tendini e legamenti svolgono un ruolo importante al fine di garantire mobilità e stabilità. Questi tessuti sono composti principalmente da collagene e presentano una struttura altamente fibrosa. Evidenziare i componenti della microstruttura di legamenti e tendini in immagini tridimensionali (3D) è di fondamentale importanza per estrarre informazioni significative che posso anvere ripercussioni sulla scienza di base e sulle applicazioni ortopediche. In particolare, le proprietà meccaniche delle microstrutture fibrose sono fortemente influenzate da alcune caratteristiche geometriche, come la volume fraction, l’orientamento e il diametro; tuttavia, determinare l'orientamento e il diametro della fibra 3D è impegnativo. In questa prospettiva, questa tesi mirava ad unire tomografia microcomputerizzata (microCT) ed elaborazione delle immagini in un approccio integrato al fine di identificare e migliorare le informazioni microstrutturali sui tessuti biologici fibrosi, includendo i dati di volume e orientamento. La procedura complessiva è stata applicata per la prima volta su campioni di tendine del ginocchio umano e su legamento collaterale bovino. In una prima fase, sono state testate preparazioni specifiche del campione, inclusa una disidratazione chimica o soluzioni di acido fosfotungstico (PTA) al 2 % in acqua (H2O) o in soluzione di etanolo al 70% (EtOH), così da migliorare il contrasto dell'immagine di questi specifici tessuti. Inoltre, utilizzando i dati scansionati, è stata sviluppata una nuova tecnica di elaborazione delle immagini basata sul filtro 3D hessiano multiscala per evidenziare le strutture fibrose ed ottenere informazioni quantitative sulle fibre. È interessante notare che, per qualsiasi strategia di preparazione del campione di tendini/legamenti, l'approccio proposto è risultato adeguato per rilevare e caratterizzare le proprietà del fascicolo. I risultati del test hanno mostrato che la disposizione delle fibre è fortemente allineata lungo la direzione longitudinale principale nel tendine del tendine, più delle fibre del legamento collaterale bovino. Inoltre, questa tecnica è stata ulteriormente applicata al fine di determinare come il Legamento Crociato Anteriore (LCA) umano risponda a carichi uniassiali rispetto a valori crescenti di deformazione, considerando sia un tessuto sano che uno in condizioni patologiche, cioè acquisito da un paziente con l'artrosi. Anche in questi casi, l'approccio integrato si è rivelato valido ed affidabile nell'individuare orientamento e dimensione dei fascicoli presenti e, quindi, attraverso un modello meccanico strutturale - basato su specifiche leggi costitutive - nello stimare il modulo elastico di questi tessuti. Sono state infatti stimate le curve sforzo-deformazione, ottenendo un valore di modulo elastico di 60.8 MPa e 7.7 MPa rispettivamente per il LCA sano e patologico. In conclusione, è stato progettato e validato in via preliminare un nuovo protocollo microCT per il miglioramento del contrasto dedicato all'analisi microstrutturale dei tessuti molli biologici con caratteristiche fibrose. In una peculiare applicazione al LCA, le informazioni ottenute con il protocollo sono state utilizzate per implementare un modello meccanico dei tessuti fibrosi, stimando così il comportamento biomeccanico dei tessuti sani e patologici.ABSTRACT In the musculoskeletal system, tendons and ligaments play an important role in ensuring mobility and stability. These tissues are primarily composed of collagen and present a highly fibrous structure. Highlighting the microstructure components of ligaments and tendons in three-dimensional (3D) images is crucial for extracting meaningful information impacting basic science and orthopaedic applications. In particular, the mechanical properties of the fibrous microstructures are strongly influenced by their volume fraction, orientation, and diameter. However, determining the 3D fibre orientation and diameter is challenging. In this picture, this thesis aimed at integrating microcomputed tomography (microCT) and image processing approach to identify and enhance microstructural information about biological soft fibrous tissues, including volume and orientation. The overall procedure was first applied on human hamstring tendon and bovine collateral ligament samples. In a first phase specific sample preparations – including either a chemical dehydration, or by 2% of phosphotungstic acid (PTA) in water (H2O) or in 70% ethanol (EtOH) solution – were tested to enhance image contrast of these specific soft tissues. Further, using the scanned data, a novel image processing technique based on 3D Hessian multiscale filter for highlighting fibrous structures was developed to obtain quantitative fibre information. Interestingly, for any strategy of tendon/ligament sample preparation, the proposed approach was adequate for detecting and characterizing fascicle features. The test results showed the fibre arrangement strongly aligned along the main longitudinal direction in the human hamstring tendon more than fibres on the bovine collateral ligament. Moreover, this technique was further applied in order to determine how the human Anterior Cruciate Ligament (ACL) responds to uniaxial loads with respect to increasing values of strain, considering both a healthy tissue and a one under pathological conditions, i.e., acquired from a patient with osteoarthritis. Also in these cases, the integrated approach was valuable and reliable in identifying orientation and size of present fascicles and, thus, through a structural mechanical model - based on specific constitutive law - to estimate the elastic modulus of these tissues. In fact, stress-strain curves were estimated, obtaining a value of elastic modulus of 60.8 MPa and 7.7 MPa for the healthy and pathological ACLs, respectively. In conclusion, a novel contrast enhancement microCT protocol was designed and preliminarily validated for the microstructural analysis of biological soft fibrous tissues. In a peculiar application to ACL, the information obtained with the protocol was used to implement a mechanical model of fibrous tissues, thus estimating the biomechanical behaviour of the healthy and pathological tissues

Segmentation techniques of brain arteriovenous malformations for 3D visualization: a systematic review

BACKGROUND Visualization, analysis and characterization of the angioarchitecture of a brain arteriovenous malformation (bAVM) present crucial steps for understanding and management of these complex lesions. Three-dimensional (3D) segmentation and 3D visualization of bAVMs play hereby a significant role. We performed a systematic review regarding currently available 3D segmentation and visualization techniques for bAVMs. METHODS PubMed, Embase and Google Scholar were searched to identify studies reporting 3D segmentation techniques applied to bAVM characterization. Category of input scan, segmentation (automatic, semiautomatic, manual), time needed for segmentation and 3D visualization techniques were noted. RESULTS Thirty-three studies were included. Thirteen (39%) used MRI as baseline imaging modality, 9 used DSA (27%), and 7 used CT (21%). Segmentation through automatic algorithms was used in 20 (61%), semiautomatic segmentation in 6 (18%), and manual segmentation in 7 (21%) studies. Median automatic segmentation time was 10 min (IQR 33), semiautomatic 25 min (IQR 73). Manual segmentation time was reported in only one study, with the mean of 5-10 min. Thirty-two (97%) studies used screens to visualize the 3D segmentations outcomes and 1 (3%) study utilized a heads-up display (HUD). Integration with mixed reality was used in 4 studies (12%). CONCLUSIONS A golden standard for 3D visualization of bAVMs does not exist. This review describes a tendency over time to base segmentation on algorithms trained with machine learning. Unsupervised fuzzy-based algorithms thereby stand out as potential preferred strategy. Continued efforts will be necessary to improve algorithms, integrate complete hemodynamic assessment and find innovative tools for tridimensional visualization

ToScA North America (6 – 8 June 2017, The University of Texas, Austin, TX) Program

ToScA North America will address key areas of science, including Multi-modal Imaging, Geosciences, Forensics, Increasing Contrast, Educational Outreach, Data, Materials Science and Medical and Biological Science.University of Texas High-Resolution X-ray CT Facility (UTCT); Jackson School of Geosciences, The University of Texas at Austin; Natural History Museum (London); Royal Microscopical Society (Oxford, UK)Geological Science

Interactive ray tracing for volume visualization

Journal ArticleWe present a brute-force ray tracing system for interactive volume visualization, The system runs on a conventional (distributed) shared-memory multiprocessor machine. For each pixel we trace a ray through a volume to compute the color for that pixel. Although this method has high intrinsic computational cost, its simplicity and scalability make it ideal for large datasets on current high-end parallel systems

Steerable3D: An ImageJ plugin for neurovascular enhancement in 3-D segmentation

PurposeImage processing plays a fundamental role in the study of central nervous system, for example in the analysis of the vascular network in neurodegenerative diseases. Synchrotron X-ray Phase-contrast micro-Tomography (SXPCT) is a very attractive method to study weakly absorbing samples and features, such as the vascular network in the spinal cord (SC). However, the identification and segmentation of vascular structures in SXPCT images is seriously hampered by the presence of image noise and strong contrast inhomogeneities, due to the sensitivity of the technique to small electronic density variations. In order to help with these tasks, we implemented a user-friendly ImageJ plugin based on a 3D Gaussian steerable filter, tuned up for the enhancement of tubular structures in SXPCT images.MethodsThe developed 3D Gaussian steerable filter plugin for ImageJ is based on the steerability properties of Gaussian derivatives. We applied it to SXPCT images of ex-vivo mouse SCs acquired at different experimental conditions.ResultsThe filter response shows a strong amplification of the source image contrast-to-background ratio (CBR), independently of structures orientation. We found that after the filter application, the CBR ratio increases by a factor ranging from ~6 to ~60. In addition, we also observed an increase of 35% of the contrast to noise ratio in the case of injured mouse SC.ConclusionThe developed tool can generally facilitate the detection/segmentation of capillaries, veins and arteries that were not clearly observable in non-filtered SXPCT images. Its systematic application could allow obtaining quantitative information from pre-clinical and clinical images