Добірка наукової літератури з теми "Non-Cartesian imaging"

Non-Cartesian sampling is widely used for fast magnetic resonance imaging (MRI). Accurate and fast image reconstruction from non-Cartesiank-space data becomes a challenge and gains a lot of attention. Images provided by conventional direct reconstruction methods usually bear ringing, streaking, and other leakage artifacts caused by discontinuous structures. In this paper, we tackle these problems by analyzing the principal point spread function (PSF) of non-Cartesian reconstruction and propose a leakage reduction reconstruction scheme based on discontinuity subtraction. Data fidelity ink-space is enforced during each iteration. Multidimensional nonuniform fast Fourier transform (NUFFT) algorithms are utilized to simulate thek-space samples as well as to reconstruct images. The proposed method is compared to the direct reconstruction method on computer-simulated phantoms and physical scans. Non-Cartesian sampling trajectories including 2D spiral, 2D and 3D radial trajectories are studied. The proposed method is found useful on reducing artifacts due to high image discontinuities. It also improves the quality of images reconstructed from undersampled data.

Brain Magnetic Resonance Imaging (MRI) is invaluable for non-invasively capturing detailed anatomical and functional information. However, motion artifacts, particularly during brain imaging, can compromise the precision of scans. This study explores motion correction techniques, focusing on the widely-used PROPELLER method and its application to Golden-angle Cartesian Randomized Time-resolved (GOCART) acquisition. While PROPELLER effectively corrects in-plane translation and rotation, its use with cartesian data demands increased sampling. GOCART, a high-speed cartesian sampling scheme, has shown promise in Dynamic Contrast-Enhanced (DCE) MRI, yet its specific artifacts in brain imaging remain underexplored. Our simulation framework assesses PROPELLER correction for translational motion in GOCART-sampled data, examining two motion directions, varied frequencies, and different temporal resolutions. Serving as a vital pre-clinical testing tool, this platform contributes to the optimization of motion correction algorithms, addressing challenges and refining imaging protocols for enhanced diagnostic reliability in advanced brain MRI.

The quest for higher spatial and/or temporal resolution in functional MRI (fMRI) while preserving a sufficient temporal signal-to-noise ratio (tSNR) has generated a tremendous amount of methodological contributions in the last decade ranging from Cartesian vs. non-Cartesian readouts, 2D vs. 3D acquisition strategies, parallel imaging and/or compressed sensing (CS) accelerations and simultaneous multi-slice acquisitions to cite a few. In this paper, we investigate the use of a finely tuned version of 3D-SPARKLING. This is a non-Cartesian CS-based acquisition technique for high spatial resolution whole-brain fMRI. We compare it to state-of-the-art Cartesian 3D-EPI during both a retinotopic mapping paradigm and resting-state acquisitions at 1mm3 (isotropic spatial resolution). This study involves six healthy volunteers and both acquisition sequences were run on each individual in a randomly-balanced order across subjects. The performances of both acquisition techniques are compared to each other in regards to tSNR, sensitivity to the BOLD effect and spatial specificity. Our findings reveal that 3D-SPARKLING has a higher tSNR than 3D-EPI, an improved sensitivity to detect the BOLD contrast in the gray matter, and an improved spatial specificity. Compared to 3D-EPI, 3D-SPARKLING yields, on average, 7% more activated voxels in the gray matter relative to the total number of activated voxels.

L'IRM fonctionnelle (IRMf) est actuellement l'une des techniques de neuroimagerie fonctionnelle les plus utilisées pour sonder l'activité cérébrale de manière non invasive grâce au contraste dépendant du niveau d'oxygène dans le sang (BOLD) qui reflète le couplage neurovasculaire. Elle offre un compromis intéressant entre la résolution spatiale et temporelle afin d'étudier le cerveau entier en tant qu'agrégation de systèmes fonctionnels intrinsèques. La recherche d'une résolution spatiale et/ou temporelle plus élevée en IRMf tout en préservant un rapport signal/bruit temporel suffisant~(tSNR) a généré une quantité considérable de contributions méthodologiques au cours de la dernière décennie, allant des methodes d'encodage cartésiennes ou non cartésiennes, des stratégies d'acquisition 2D ou 3D, de l'imagerie parallèle et/ou de échantillonnage compressif (CS) et des acquisitions multibande, pour n'en citer que quelques-unes. Dans ce travail, nous nous concentrons sur l'utilisation du CS dans l'IRMf, plus spécifiquement, nous considérons le schéma d'encodage SPARKLING.L'objectif principal de cette thèse est d'évaluer 3D-SPARKLING en tant que schéma d'acquisition viable pour l'IRMf à haute résolution et pour cerveau entier.À cet égard, nous avons d'abord comparé ses performances avec l'état de l'art en matière: 3D-EPI. Après avoir observé une plus grande sensibilité aux imperfections statiques et dynamiques du champ magnétique dans les données 3D-SPARKLING, nous avons établi un protocole expérimental pour les corriger. Enfin, nous avons étudié les possibilités et les limites de l'utilisation d'une reconstruction par fenêtre glissante en combinaison avec le schéma d'encodage SPARKLING pour améliorer rétrospectivement la résolution temporelle pendant la reconstruction des images en IRMf. Une étude de simulation dans laquelle la vérité terrain est contrôlée a été menée et a démontré la possibilité de détecter les oscillations à haute fréquence dans le signal BOLD et de séparer le bruit physiologique de l'activité neuronale
Functional MRI (fMRI) is currently one of the most commonly used functional neuroimaging techniques to probe brain activity non-invasively through the blood oxygen level-dependent (BOLD) contrast that reflects neurovascular coupling. It offers an interesting trade-off between spatial and temporal resolution in order to study the whole brain as an aggregation of intrinsic functional systems. The quest for higher spatial and/or temporal resolution in fMRI while preserving a sufficient temporal signal-to-noise ratio~(tSNR) has generated a tremendous amount of methodological contributions in the last decade ranging from Cartesian vs. non-Cartesian readouts, 2D vs. 3D acquisition strategies, parallel imaging and/or compressed sensing~(CS) accelerations and simultaneous multi-slice acquisitions to cite a few. In this work, we focus on the use of CS in fMRI; more specifically, we consider Spreading Projection Algorithm for Rapid K-space sampLING (SPARKLING) encoding scheme.The main focus and goal of this thesis involves the evaluation of 3D-SPARKLING as a viable acquisition scheme for high-resolution whole-brain fMRI. In this regard, we initially compared its capabilities with state-of-the-art 3D-EPI. After observing higher sensitivity to static and dynamic magnetic field imperfections in 3D-SPARKLING data, we established an experimental protocol to correct them. Finally, we studied the capabilities and limitations of employing a sliding-window reconstruction in combination with the SPARKLING encoding scheme to enhance temporal resolution during image reconstruction in fMRI retrospectively. A simulation study where the ground truth is controlled was conducted and demonstrated the possibility of detecting high-frequency oscillations in the BOLD signal and separating physiological noise from neural activity

Besides image contrast, imaging speed is probably the most important consideration in clinical magnetic resonance imaging (MRI). MR scanners currently operate at the limits of potential imaging speed, due to technical and physiological problems associated with rapidly switched gradient systems. Parallel imaging (parallel MRI or pMRI) is a method which allows one to significantly shorten the acquisition time of MR images without changing the contrast behavior of the underlying MR sequence. The accelerated image acquisition in pMRI is accomplished without relying on more powerful technical equipment or exceeding physiological boundaries. Because of these properties, pMRI is currently employed in many clinical routines, and the number of applications where pMRI can be used to accelerate imaging is increasing. However, there is also growing criticism of parallel imaging in certain applications. The primary reason for this is the intrinsic loss in the SNR due to the accelerated acquisition. In addition, other effects can also lead to a reduced image quality. Due to unavoidable inaccuracies in the pMRI reconstruction process, local and global errors may appear in the final reconstructed image. The local errors are visible as noise enhancement, while the global errors result in the so-called fold-over artifacts. The appearance and strength of these negative effects, and thus the image quality, depend upon different factors, such as the parallel imaging method chosen, specific parameters in the method, the sequence chosen, as well as specific sequence parameters. In general, it is not possible to optimize all of these parameters simultaneously for all applications. The application of parallel imaging in can lead to very pronounced image artifacts, i.e. parallel imaging can amplify errors. On the other hand, there are applications such as abdominal MR or MR angiography, in which parallel imaging does not reconstruct images robustly. Thus, the application of parallel imaging leads to errors. In general, the original euphoria surrounding parallel imaging in the clinic has been dampened by these problems. The reliability of the pMRI methods currently implemented is the main criticism. Furthermore, it has not been possible to significantly increase the maximum achievable acceleration with parallel imaging despite major technical advances. An acceleration factor of two is still standard in clinical routine, although the number of independent receiver channels available on most MR systems (which are a basic requirement for the application of pMRI) has increased by a factor of 3-6 in recent years. In this work, a novel and elegant method to address this problem has been demonstrated. The idea behind the work is to combine two methods in a synergistic way, namely non-Cartesian acquisition schemes and parallel imaging. The so-called non-Cartesian acquisition schemes have several advantages over standard Cartesian acquisitions, in that they are often faster and less sensitive to physiological noise. In addition, such acquisition schemes are very robust against fold-over artifacts even in the case of vast undersampling of k-space. Despite the advantages described above, non-Cartesian acquisition schemes are not commonly employed in clinical routines. A reason for that is the complicated reconstruction techniques which are required to convert the non-Cartesian data to a Cartesian grid before the fast Fourier transformation can be employed to arrive at the final MR image. Another reason is that Cartesian acquisitions are routinely accelerated with parallel imaging, which is not applicable for non-Cartesian MR acquisitions due to the long reconstruction times. This negates the speed advantage of non-Cartesian acquisition methods. Through the development of the methods presented in this thesis, reconstruction times for accelerated non-Cartesian acquisitions using parallel imaging now approach those of Cartesian images. In this work, the reliability of such methods has been demonstrated. In addition, it has been shown that higher acceleration factors can be achieved with such techniques than possible with Cartesian imaging. These properties of the techniques presented here lead the way for an implementation of such methods on MR scanners, and thus also offer the possibility for their use in clinical routine. This will lead to shorter examination times for patients as well as more reliable diagnoses
Neben dem Bildkontrast ist die Aufnahmegeschwindigkeit die entscheidende Größe für die klinische Anwendung der Magnetresonanz-Tomographie (MRT). Heutzutage arbeiten MR-Tomographen bereits häufig am Limit dessen, was technisch möglich und physiologisch noch vertretbar ist. Die parallele Bildgebung (parallele MRT, pMRT) ist ein Verfahren, welches es ermöglicht, die Aufnahmezeiten von MRT-Bildern signifikant zu verkürzen, ohne dabei das Kontrastverhalten der zu Grunde liegenden MR Sequenz zu verändern. Die beschleunigte Bildakquisition in der pMRT wird erzielt, ohne auf eine leistungsfähigere technische Ausstattung der MR-Tomographen angewiesen zu sein und ohne dabei die physiologischen Grenzwerte zu überschreiten. Wegen dieser Eigenschaften wird die pMRT heutzutage vielfach in der klinischen Routine eingesetzt. Dabei wächst die Zahl der klinischen MR Anwendungen, welche mittels paralleler Bildgebung beschleunigt werden. Neben dieser Entwicklung ist heutzutage aber auch eine zunehmende Kritik am Einsatz der parallelen Bildgebung bei bestimmten Applikationen festzustellen. Ein Hauptgrund dafür ist der intrinsische Verlust an Signal-Rausch-Verhältnis durch die beschleunigte Akquisition. Es gibt weitere Effekte, welche die Bildqualität vermindern können. Durch unvermeidbare Ungenauigkeiten bei den Verfahren der pMRT kann es zu lokalen und zu globalen Fehlern in den rekonstruierten Bildern kommen. Die lokalen Fehler sind als Rauschverstärkung sichtbar, wohingegen die globalen Fehler zu so genannten Faltungsartefakten im Bild führen. Das Auftreten und die Stärke dieser Störeffekte hängen von unterschiedlichen Parametern ab. Im Allgemeinen ist es nicht möglich alle Abhängigkeiten für jede Applikation gleichzeitig zu optimieren. Der Einsatz der parallelen Bildgebung kann zu massiven Bildartefakten führen, d.h. die parallele Bildgebung kann Fehler verstärken. Auf der anderen Seite gibt es Applikationen, wie zum Beispiel die abdominelle MR-Bildgebung oder die MR-Angiographie, bei denen die pMRT nicht zuverlässig funktioniert. Die Anwendung der pMRT verursacht also erst die Fehler. Ganz allgemein kann im klinischen Umfeld beobachtet werden, dass die anfängliche Euphorie gegenüber der parallelen Bildgebung einer gewissen Ernüchterung gewichen ist. Der Zuverlässigkeit der implementierten pMRT-Methoden gilt dabei die Hauptkritik. Des Weiteren ist es nicht gelungen, trotz großen technischen Fortschritts, die maximal zu erreichende Beschleunigung mittels paralleler Bildgebung signifikant zu erhöhen. Standard in der klinischen Routine ist immer noch ein Beschleunigungsfaktor von zwei, obwohl sich die Anzahl der unabhängigen Empfangskanäle eines MR Systems (eine Grundvoraussetzung für die Verwendung der pMRT) in den letzten Jahren um einen Faktor 3-6 erhöht hat. In dieser Arbeit wurde erstmalig gezeigt, dass es eine elegante Möglichkeit gibt, diese Probleme zu adressieren. Die Idee besteht darin, Synergieeffekte zu nutzen, die aus einer Kombination von so genannten nicht-kartesischen Abtastverfahren mit der parallelen Bildgebung entstehen. Die nicht-kartesischen Aufnahmeverfahren haben gegenüber den herkömmlichen kartesischen Verfahren einige Vorteile. Sie sind in der Regel schneller und weniger empfindlich für physiologisches Rauschen als kartesische Aufnahmeverfahren. Außerdem sind sie sehr robust gegenüber Faltungsartefakten, selbst bei starker Unterabtastung der k Raumdaten. Trotz der eben beschriebenen Vorteile finden nicht-kartesische Aufnahmeverfahren kaum Verwendung in der klinischen Routine. Ein Grund hierfür sind die komplexen Rekonstruktionsverfahren, die an Stelle der schnellen Fourier-Transformation angewendet werden müssen, um ein MR-Bild aus nicht-kartesischen Daten zu erzeugen. Ein weiterer Grund liegt darin, dass kartesische MR-Aufnahmen mittlerweile routinemäßig mit paralleler Bildgebung beschleunigt werden, wohingegen dies bei nicht-kartesischen MR-Aufnahmen wegen der langen Rekonstruktionszeiten nicht praktikabel ist. Dadurch wird der oben erwähnte Geschwindigkeitsvorteil der nicht-kartesischen Verfahren irrelevant. Durch die Entwicklung der in dieser Doktorarbeit vorgestellten Methoden konnten erstmals Rekonstruktionszeiten in der nicht-kartesischen Bildgebung erzielt werden, die vergleichbar sind mit denen in der kartesischen Bildgebung. In der vorliegenden Arbeit konnte die höhere Zuverlässigkeit dieser neuen Verfahren demonstriert werden. Des Weiteren wurde gezeigt, dass höhere Beschleunigungsfaktoren erzielt werden können als dies mit kartesischen Verfahren bisher möglich war. Diese Eigenschaften der vorgestellten Methoden bahnen den Weg für eine Implementierung solcher Verfahren an MR Geräten und damit deren Anwendung in der klinischen Routine. Letztendlich wird dies zu kürzeren Untersuchungszeiten der Patienten und zuverlässigeren Diagnosen führen

Mouse models of cancer are an invaluable tool for studying the mechanism of the disease and the effect of new therapies. Recent years have seen an explosive growth in the development of such models and consequently there is an increased need for better imaging techniques to study them. The goal of this work was to develop a technique that satisfied the requirements for preclinical cancer imaging: high spatial resolution, good soft tissue differentiation, excellent motion immunity, fast and non-invasive imaging to enable high-throughput, longitudinal studies.

T₂-weighted and diffusion-weighted magnetic resonance imaging (MRI) has been shown to be effective for tumor characterization clinically. But translation of these techniques to the mouse is challenging. The higher spatial resolution and faster physiologic motion make conventional approaches very susceptible to phase artifacts. Additionally, at higher magnetic fields required for these studies, T*₂ and T₂ are significantly shorter and T₁ is longer, making in vivo imaging even harder.

A rigorous cancer imaging protocol was developed by optimizing and integrating various components of the system, including MR hardware, animal handling, and pulse sequence design to achieve reliable, repeatable and rapid imaging. The technique presented here relies heavily on the non-Cartesian sampling strategy of PROPELLER (Periodically Rotated Overlapping ParallEL Lines with Enhanced Reconstruction) MRI. The novel data acquisition and reconstruction overcomes the adverse effects of physiological motion, allows for rapid setup and acquisition and provides excellent tissue contrast. The sequence was optimized to enable T₂-weighted and diffusion-weighted imaging in tumor-bearing mice with in-plane resolution of 117μm and slice thickness of 1mm. Multi-slice datasets covering the entire thorax and abdomen were acquired in ∼30 minutes.

The imaging protocol developed here was applied to a high-throughput, longitudinal study in a mouse model of liver metastases. The liver is a common site of distal metastases in colon and rectal cancer, and if detected early has an improved prognosis. Unfortunately, severe respiratory motion make it hard to image. The relative merits of the proposed PROPELLER technique were analyzed with respect to the accepted gold-standard for abdominal cancer imaging, computed tomography (CT).

The non-Cartesian MR microscopy technique proposed here is a valuable tool in the “Cancer analysis toolkit”. It allows for high-throughput, longitudinal experiments in free-breathing mice generating both structural and functional information with minimal artifacts and excellent spatial resolution. This work should find broad applications in various mouse models of cancer for studying the pathology of the disease, its progression as well as its response to treatment.

Dissertation

abstract: Magnetic Resonance Imaging (MRI) is limited in speed and resolution by the inherently low Signal to Noise Ratio (SNR) of the underlying signal. Advances in sampling efficiency are required to support future improvements in scan time and resolution. SNR efficiency is improved by sampling data for a larger proportion of total imaging time. This is challenging as these acquisitions are typically subject to artifacts such as blurring and distortions. The current work proposes a set of tools to help with the creation of different types of SNR efficient scans. An SNR efficient pulse sequence providing diffusion imaging data with full brain coverage and minimal distortion is first introduced. The proposed method acquires single-shot, low resolution image slabs which are then combined to reconstruct the full volume. An iterative deblurring algorithm allowing the lengthening of spiral SPoiled GRadient echo (SPGR) acquisition windows in the presence of rapidly varying off-resonance fields is then presented. Finally, an efficient and practical way of collecting 3D reformatted data is proposed. This method constitutes a good tradeoff between 2D and 3D neuroimaging in terms of scan time and data presentation. These schemes increased the SNR efficiency of currently existing methods and constitute key enablers for the development of SNR efficient MRI.
Dissertation/Thesis
Ph.D. Electrical Engineering 2011

Magnetic resonance imaging (MRI) is a non-invasive and safe medical imaging technique. This imaging modality collects samples in the Fourier domain, called as the k-space. The k-space is traversed along continuous trajectories using varying magnetic gradients. Scan times in MRI are generally limited by either signal-to-noise ratio (SNR) or the gradient amplitude and slew rate. SNR limitations are met by advances in higher-field systems as well as improved design for receive coils. Further hardware improvements in gradient sys- tem switching times enable rapid imaging with higher resolution. The k-space is usually traversed in multiple shots, especially for higher resolution images. Scan time reduction in MRI is important to improve patient comfort, reduce image artifacts related to motion, improve dynamic imaging. With the development of the theory of compressed sensing and recent advances in deep learning-based image reconstruction methods, it is possible to reconstruct MRI images with an undersampled k-space data. For practical implemen- tation of compressed sensing in MRI, a variable density (VD) sampling is utilized. In the recent years, many methods have been proposed to undersample Cartesian trajectory to reduce scan time, however, the non-Cartesian trajectories have been observed to be more advantageous in terms of better utilization of gradients and benign artifacts. In this the- sis, we focus on the design non-Cartesian k-space trajectories that result in a good image reconstruction with shorter read-out times. PSNR and SSIM are used as metrics to com- pare image reconstruction quality and the sensitivity of the trajectories to system-related effects such as off-resonance and gradient imperfection are also studied. In the first part of the thesis, two types of deterministic trajectories based on sinusoids and space-filling curves (SFCs) are designed. For sinusoids-based trajectories, sinusoidal curves are used to traverse the k-space. To introduce VD in the four-shot setup, a linear chirp is used, instead of a sinusoid. For SFC-based trajectories, VD trajectories using Hilbert, Peano and Morton SFCs are designed under three schemas. These trajectories are compared with the commonly used echo-planar imaging (EPI) trajectory. It is observed that the sinusoids-based trajectories using linear chirps result in a 3 dB improvement in PSNR with 50 % reduction in read-out time and the SFC-based trajectories result in an improvement of 7 dB reconstruction quality with a similar read-out time as the EPI trajectory for a brain analytical phantom image. In the second part, the problem of making the trajectories feasible is considered such that the gradient constraints are satisfied. A generalized framework based on the projec- tion of infeasible trajectories onto the set of feasible trajectories is developed. The biggest advantage of the framework is that it provides a bouquet of methods with tunable param- eters, and the user can choose a trajectory that best suits their purpose of either reducing the read-out time or improving image quality. An existing method in the literature becomes a special case of this framework. Under the framework, traveling salesman prob- lem (TSP)-based and random-like stochastic trajectories are considered. The proposed methods result in shorter read-out times and/or better reconstruction performances as compared to the state-of-the-art methods. In particular, the proposed projection with permutation (PP) method results in a similar reconstruction quality with about 67% reduction in read-out time. In the third part, a greedy approach is discussed to learn a non-Cartesian trajectory for knee MRI images using distance-based rules. The trajectory is constructed such that it results in the highest average improvement in the reconstruction performance on the test images. A stochastic version of the algorithm is proposed to reduce the computational complexity of the greedy algorithm. The learned trajectory is observed to result in a visually better reconstruction with a 0.7 dB improvement than the learned Cartesian- based and TSP-based trajectories with similar read-out times. To summarize, in this thesis, non-Cartesian trajectories have been designed using deterministic, probabilistic and learning-based approaches. The proposed trajectories are observed to perform better than their state-of-the-art counterparts. For low-resolution images, the PP method outperforms the deterministic and other random-like trajectories both in terms of read-out time and reconstruction performance. Among the four-shot trajectories for high resolution brain imaging, the sinusoids-based deterministic trajectory performs better than the probabilistic trajectories with a shorter read-out time. For high resolution knee images, four-shot learned trajectory based on greedy method results in a better image quality for a similar read-out time.
Meity

Following Spinoza’s lead, this book imagines an embodied environmental ethics based on the relations between sentient beings and sustained by affections, sensibility, the senses, and contact. Engaging embodied, cognitive, phenomenological, and psychoanalytic aspects of affectivity, Omar Felipe Giraldo and Ingrid Fernanda Toro help us understand how places inhabit us, and therefore, how places transformed lovingly have the immense capacity to modify the body, to redirect desire, to clarify our sensibility – in order to create an affectivity in a direction opposite to the regime imposed by this ecocidal society. Beginning with a discussion of environmental epistemology on ontological monisms and dualisms, Giraldo and Toro question theoretical approaches that correctly challenge Cartesian dichotomies but which they claim continue to examine the environmental problem from two angles: culture versus nature, the human versus the non-human. The environmental crisis is more than a technological or economic problem. In this book, Giraldo and Toro argue that it is a threat to survival inscribed in the deepest foundations of our body, in the intimacy of our skin, in the intensity and tone of our affections, in our desires, in our perceptions, and in our sensory-motor capacities.

In cardiovascular magnetic resonance imaging, scan time is of critical importance, as many applications require breath-holding to suppress respiratory-related image artefacts. In this chapter, approaches to reduce scan time, while maintaining resolution, are described. Besides partial sampling of k-space, non-Cartesian k-space trajectories are introduced, followed by an overview of data under-sampling techniques as they are implemented on clinical magnetic resonance systems. Advantages and limitations of each of these methods are briefly described.

Disaffected from the court and shaken out of conventional assumptions about human nature by the Ghost’s revelations, Hamlet begins to think of comparisons with non-human life, beginning with his father as ‘old mole’ (1.5.170). Later he turns to worms, and his attention suggests a willed strategy of existential and ecological discovery, since worms occupied a place diametrically opposite to humans in the traditional hierarchy of life. Renaissance Humanists often used the perceived inferiority of worms and other animals to define human uniqueness. Their gradations of being, by extension, justified human mastery of the earth represented in Hamlet by Claudius’s modernizing transformation of Denmark into a military-industrial state. Adopting a worm-oriented perspective (wryly imagined by conservation ecologist André Voisin in my epigraph), Hamlet begins to question his own conventional Humanist reflexes, such as those on display in his opening soliloquy (e.g. ‘O God, a beast that wants discourse of reason /Would have mourned longer’ [1.2.150–51]). Recent critics have shown how analogies between social behaviour and animals in Hamlet and other Shakespeare plays reflect the rediscovery of classical scepticism towards human superiority by Humanists such as Michel de Montaigne, before René Descartes and other Enlightenment philosophers elevated mind and soul into essential qualities of human nature. As in other areas of ecology and environmentalism discussed in this book, early modern reflections such as Hamlet’s look forward to today’s post-Cartesian and post-human enquiries into human, animal, and cyborgian crossovers. In this chapter I want to align these pre-modern and present-day horizons with the scientific revolution that links them: evolutionary biology’s tracing of human origins to the shared creaturely and genetic life of the planet. Worms will be my trope for Hamlet’s attention to what Giorgio Agamben calls a ‘zone of indeterminacy’ between human and animal life, and what Andreas Höfele identifies as the complex doubleness of similarity and difference that runs through all of Shakespeare’s animal–human relations, beginning with the comic dialogues of Crab and Lance in The Two Gentlemen of Verona.