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

Tubular structure filtering by ranking orientation responses of path operators

National audienceThin objects in 3D volumes, for instance vascular networks in medical imaging or various kinds of fibres in materials science, have been of interest for some time to computer vision. Particularly, tubular objects are everywhere elongated in one principal direction –which varies spatially– and are thin in the other two perpendicular di- rections. Filters for detecting such structures use for instance an analysis of the three principal directions of the Hessian, which is a local feature. In this article, we present a low-level tubular structure detection filter. This filter relies on paths, which are semi-global features that avoid any blurring effect induced by scale-space convolution. More precisely, our filter is based on recently developed morphological path operators. These require sampling only in a few principal directions, are robust to noise and do not assume feature regularity. We show that by ranking the directional response of this operator, we are further able to efficiently distinguish between blob, thin planar and tubular structures. We validate this approach on several applications, both from a qualitative and a quantitative point of view, demonstrating an efficient response on tubular structures

Analysis and processing of dynamic and structural magnetic resonance imaging signals for studying small vessel disease

Cerebral small vessel disease (CSVD) describes multiple and dynamic pathological processes disrupting the optimum functioning of perforating arterioles, capillaries and venules, increasing the risk of stroke and dementia. Although the pathogenesis of this disease is still elusive, the breakdown of the blood-brain barrier (BBB), which would hinder brain waste clearance, is thought to play a pivotal factor in it. Nonetheless, the microscopic origin and nature of these abnormalities and the lack of a ground truth make the study of CSVD in vivo in humans via magnetic resonance imaging (MRI) challenging and signal processing schemes likely to be sub-optimal. In this doctoral thesis, we proposed signal analysis and processing techniques to improve the quantification and characterisation of subtle and clinically relevant neuroimaging features of CSVD. We applied our proposals to analyses of structural and dynamic-contrast enhanced MRI (sMRI and DCE-MRI) to better characterise CSVD. DCE-MRI is commonly used to investigate cerebrovascular dysfunction, but the extremely subtle nature of the signal in CSVD makes it unclear whether signal changes are caused by microscopic yet critical BBB abnormalities. Moreover, ethical and safety considerations in vivo and the lack of validation frameworks hinder optimising imaging protocols and processing schemes. To cope with these issues, we thus proposed an open-source computational human brain model for mimicking the four-dimensional DCE-MRI acquisition process. With it, we quantified the substantial impact of spatiotemporal considerations on permeability mapping, detected sources of errors that had been overlooked in the past, and provided evidence of the harmful effect of post-processing or lack thereof on DCE-MRI assessments. Perivascular spaces (PVS) in the brain, which are involved in brain waste clearance, can become visible in sMRI scans of patients with neuroimaging features of CSVD, but their automatic quantification is challenging due to the size of PVS, the incidence and presence of imaging artefacts, and the lack of a ground truth. We first proposed a computational model of sMRI to study and compare current PVS segmentation techniques and identify major areas of improvement. We confirmed that optimal segmentation requires tuning depending on image quality and that motion artefacts are particularly detrimental to PVS quantification. We then proposed a processing strategy that distinguished high-quality from motion-corrupted images and processed them accordingly. We demonstrated such an approximation leads to estimates that correlate better with clinical visual scores and agree more with full manual counts. After optimisation using our proposals, we also found PVS measurements were associated with BBB permeability, in accordance with the link between brain waste clearance and endothelial dysfunction. This work provides means for understanding the effect of image acquisition and processing on the assessment of subtle markers of brain health to maximise confidence of studies of endothelial dysfunction and brain waste clearance via MRI. It also constitutes a cornerstone on which future optimisation and development can be based upon