Complexity Reduction in Image-Based Breast Cancer Care

The diversity of malignancies of the breast requires personalized diagnostic and therapeutic decision making in a complex situation. This thesis contributes in three clinical areas: (1) For clinical diagnostic image evaluation, computer-aided detection and diagnosis of mass and non-mass lesions in breast MRI is developed. 4D texture features characterize mass lesions. For non-mass lesions, a combined detection/characterisation method utilizes the bilateral symmetry of the breast s contrast agent uptake. (2) To improve clinical workflows, a breast MRI reading paradigm is proposed, exemplified by a breast MRI reading workstation prototype. Instead of mouse and keyboard, it is operated using multi-touch gestures. The concept is extended to mammography screening, introducing efficient navigation aids. (3) Contributions to finite element modeling of breast tissue deformations tackle two clinical problems: surgery planning and the prediction of the breast deformation in a MRI biopsy device

Comparing Regularized Kelvinlet Functions and the Finite Element Method for Registration of Medical Images to Sparse Organ Data

Image-guided surgery collocates patient-specific data with the physical environment to facilitate surgical decision making in real-time. Unfortunately, these guidance systems commonly become compromised by intraoperative soft-tissue deformations. Nonrigid image-to-physical registration methods have been proposed to compensate for these deformations, but intraoperative clinical utility requires compatibility of these techniques with data sparsity and temporal constraints in the operating room. While linear elastic finite element models are effective in sparse data scenarios, the computation time for finite element simulation remains a limitation to widespread deployment. This paper proposes a registration algorithm that uses regularized Kelvinlets, which are analytical solutions to linear elasticity in an infinite domain, to overcome these barriers. This algorithm is demonstrated and compared to finite element-based registration on two datasets: a phantom dataset representing liver deformations and an in vivo dataset representing breast deformations. The regularized Kelvinlets algorithm resulted in a significant reduction in computation time compared to the finite element method. Accuracy as evaluated by target registration error was comparable between both methods. Average target registration errors were 4.6 +/- 1.0 and 3.2 +/- 0.8 mm on the liver dataset and 5.4 +/- 1.4 and 6.4 +/- 1.5 mm on the breast dataset for the regularized Kelvinlets and finite element method models, respectively. This work demonstrates the generalizability of using a regularized Kelvinlets registration algorithm on multiple soft tissue elastic organs. This method may improve and accelerate registration for image-guided surgery applications, and it shows the potential of using regularized Kelvinlets solutions on medical imaging data.Comment: 17 pages, 9 figure

Current engineering developments for robotic systems in flexible endoscopy

The past four decades have seen an increase in the incidence of early-onset gastrointestinal cancer. Because early-stage cancer detection is vital to reduce mortality rate, mass screening colonoscopy provides the most effective prevention strategy. However, conventional endoscopy is a painful and technically challenging procedure that requires sedation and experienced endoscopists to be performed. To overcome the current limitations, technological innovation is needed in colonoscopy. In recent years, researchers worldwide have worked to enhance the diagnostic and therapeutic capabilities of endoscopes. The new frontier of endoscopic interventions is represented by robotic flexible endoscopy. Among all options, self-propelling soft endoscopes are particularly promising thanks to their dexterity and adaptability to the curvilinear gastrointestinal anatomy. For these devices to replace the standard endoscopes, integration with embedded sensors and advanced surgical navigation technologies must be investigated. In this review, the progress in robotic endoscopy was divided into the fundamental areas of design, sensing, and imaging. The article offers an overview of the most promising advancements on these three topics since 2018. Continuum endoscopes, capsule endoscopes, and add-on endoscopic devices were included, with a focus on fluid-driven, tendon-driven, and magnetic actuation. Sensing methods employed for the shape and force estimation of flexible endoscopes were classified into model- and sensor-based approaches. Finally, some key contributions in molecular imaging technologies, artificial neural networks, and software algorithms are described. Open challenges are discussed to outline a path toward clinical practice for the next generation of endoscopic devices

Engineering precision surgery: Design and implementation of surgical guidance technologies

In the quest for precision surgery, this thesis introduces several novel detection and navigation modalities for the localization of cancer-related tissues in the operating room. The engineering efforts have focused on image-guided surgery modalities that use the complementary tracer signatures of nuclear and fluorescence radiation. The first part of the thesis covers the use of “GPS-like” navigation concepts to navigate fluorescence cameras during surgery, based on SPECT images of the patient. The second part of the thesis introduces several new imaging modalities such as a hybrid 3D freehand Fluorescence and freehand SPECT imaging and navigation device. Furthermore, to improve the detection of radioactive tracer-emissions during robot-assisted laparoscopic surgery, a tethered DROP-IN gamma probe is introduced. The clinical indications that are used to evaluate the new technologies were all focused on sentinel lymph node procedures in urology (i.e. prostate and penile cancer). Nevertheless, all presented techniques are of such a nature, that they can be applied to different surgical indications, including sentinel lymph node and tumor-receptor-targeted procedures, localization the primary tumor and metastatic spread. This will hopefully contribute towards more precise, less invasive and more effective surgical procedures in the field of oncology. Crystal Photonics GmbH Eurorad S.A. Intuitive Surgical Inc. KARL STORZ Endoscopie Nederland B.V. MILabs B.V. PI Medical Diagnostic Equipment B.V. SurgicEye GmbH Verb Surgical Inc.LUMC / Geneeskund

Patient-Specific Implants in Musculoskeletal (Orthopedic) Surgery

Most of the treatments in medicine are patient specific, aren’t they? So why should we bother with individualizing implants if we adapt our therapy to patients anyway? Looking at the neighboring field of oncologic treatment, you would not question the fact that individualization of tumor therapy with personalized antibodies has led to the thriving of this field in terms of success in patient survival and positive responses to alternatives for conventional treatments. Regarding the latest cutting-edge developments in orthopedic surgery and biotechnology, including new imaging techniques and 3D-printing of bone substitutes as well as implants, we do have an armamentarium available to stimulate the race for innovation in medicine. This Special Issue of Journal of Personalized Medicine will gather all relevant new and developed techniques already in clinical practice. Examples include the developments in revision arthroplasty and tumor (pelvic replacement) surgery to recreate individual defects, individualized implants for primary arthroplasty to establish physiological joint kinematics, and personalized implants in fracture treatment, to name but a few

Brain and Human Body Modeling

This open access book describes modern applications of computational human modeling with specific emphasis in the areas of neurology and neuroelectromagnetics, depression and cancer treatments, radio-frequency studies and wireless communications. Special consideration is also given to the use of human modeling to the computational assessment of relevant regulatory and safety requirements. Readers working on applications that may expose human subjects to electromagnetic radiation will benefit from this book’s coverage of the latest developments in computational modelling and human phantom development to assess a given technology’s safety and efficacy in a timely manner. Describes construction and application of computational human models including anatomically detailed and subject specific models; Explains new practices in computational human modeling for neuroelectromagnetics, electromagnetic safety, and exposure evaluations; Includes a survey of modern applications for which computational human models are critical; Describes cellular-level interactions between the human body and electromagnetic fields