Prone to supine surface-based registration for surgical planning in breast cancer treatment

Breast cancer is the most common invasive cancer in women worldwide. Many women with breast cancer have their malignant tumors detected before the lesions become clinically palpable. Occult lesions must be marked for the surgeon to ensure that they can be effectively resected. Image-guided wire localization (WGL) is the current standard of care for the excision of non-palpable carcinomas during breast conserving surgery. The integration of the information from multimodal imaging may be especially relevant in surgical planning as complement or an alternative to WGL. The combination of information from images in different positions is especially difficult due to large breast deformation. This work presents a system based on surface registration to localize the lesion in the operative position, starting from a prone MRI study and a surface of the patient in the supine positon. The pre-operative surface from the MRI is registered to the surface obtained in a supine position similar to the intraoperative setting. Triangular meshes have been used to model breast surface in both positions and surfaces are aligned using a Laplacian deformation with fiducials automatically obtained from 3 anatomical references. The evaluation of the methodology has been carried out in 13 cases in which a supine- CT was available achieving an average localization error of 6.7 m

Breast Tumor Localization by Prone to Supine Landmark Driven Registration for Surgical Planning

Breast cancer is the most common cancer in women worldwide. Screening programs and imaging improvements have increased the detection of clinically occult non-palpable lesions requiring preoperative localization. Wire guided localization (WGL) is the current standard of care for the excision of non-palpable carcinomas during breast conserving surgery. Due to the current limitations of intraoperative tumor localization approaches, the integration of multimodal imaging information may be especially relevant in surgical planning. This research proposes a novel method for performing preoperative image-to-surgical surface data alignment to determine the position of the tumor at the time of surgery and aid preoperative planning. First, the volume of the breast in the surgical position is reconstructed and a set of surface correspondences is defined. Then, the preoperative (prone) and intraoperative (supine) volumes are co-registered using landmark driven non-rigid registration methods. We compared the performances of diffeomorphic and Bspline based registration methods. Finally, our method was validated using clinical data from 67 patients considering as target registration error (TRE) the distance between the estimated tumor position and the reference surgical position. The proposed method achieved a TRE of 16.21 ± 8.18 mm and it could potentially assist the surgery planning and guidance of breast cancer treatment in the clinical practice.This work was supported in part by the Spanish Ministry of Science and Innovation under Project RTI2018-098682-B-I00 (MCIU/AEI/FEDER,UE), Project PI18/01625 (Instituto de Salud Carlos III) and Grant BGP18/00178 under Beatriz Galindo Programme; in part by the European Union's European Regional Development Fund (ERDF); and in part by the Madrid Government (Comunidad de Madrid-Spain) under the Multiannual Agreement with Universidad Politécnica de Madrid in the line Support for Research and Development Projects for Beatriz Galindo researchers, in the context of the V Plan Regional de Investigación Científíca e Innovación Tecnológica (PRICIT)

Development of techniques for surgical planning in breast cancer treatment

Breast cancer is the most common cancer among women worldwide. In 2020, there were 2.3 million newly diagnosed female breast cancer cases, representing almost one in four of all cancers in women. Screening programs and imaging improvements have increased the detection of clinically occult non-palpable breast lesions for which the treatment of choice is breast conserving surgery (BCS). Preoperative imaging has limited utility as a surgical guidance tool because images are acquired in signifcantly diferent orientations than the typical patient setup for surgery. Therefore, a localization of occult breast lesions is needed prior to the intervention. In this Thesis, we developed diferent approaches to estimate the localization of the tumor in the surgical position, which may provide alternatives or complementary techniques to current preoperative localization methods used in clinical practice. The aim of the developed approaches is to align preoperative imaging data in the prone position with intraoperative data in the supine position using the surface of the patient acquired in the operating room. The frst approach proposed is based on a novel method to perform a surface driven registration for large deformations using automatically obtained landmarks to transform the prone preoperative volume to the surgical space and to estimate the tumor localization. The second approach consists of a novel biomechanical model of the breast under the efect of gravity that integrates a visco-hyperelastic constitutive model to simulate the prone to supine pose transformation and estimate the tumor position. Finally, we designed a novel methodology to learn the large deformation of the breast from the preoperative to intraoperative position using a surface-tovolume deep learning based registration approach decreasing signifcantly the computation time required to localize the tumor position. These proposals have been developed and evaluated with a cohort of 67 retrospective cases of breast cancer that include imagining information both in prone and supine positions. The results obtained have demonstrated that the proposed methodologies have the potential to be used as complementary or alternative methods for tumor prelocalization in the surgery or therapy of breast cancer. RESUMEN El cáncer de mama es el cáncer más frecuente en mujeres en todo el mundo. En el año 2020, se diagnosticaron 2,3 millones de nuevos casos de cáncer de mama en mujeres, lo que representa casi uno de cada cuatro cánceres femeninos. Los programas de cribado y las mejoras en el diagnóstico por imagen han aumentado la detección de lesiones mamarias no palpables para las que el tratamiento de elección es la cirugía conservadora de la mama. El diagnóstico por imagen preoperatorio tiene utilidad limitada como herramienta para guiar la cirugía, ya que las imágenes se adquieren en posiciones muy diferentes con respecto a la posición de la cirugía. Por lo tanto, es necesario localizar las lesiones mamarias ocultas antes de la intervención. En esta Tesis doctoral, hemos desarrollado diferentes aproximaciones para estimar la localización del tumor en la posición quirúrgica, que pueden proporcionar técnicas alternativas o complementarias a los actuales métodos de localización preoperatoria utilizados en la práctica clínica. El objetivo de los enfoques desarrollados es alinear los datos de imagen preoperatorios en posición prona con los datos intraoperatorios en posición supina utilizando la superficie de la paciente adquirida en el quirófano. El primer enfoque propuesto se basa en un nuevo método para realizar un registro guiado por la superficie para grandes deformaciones utilizando puntos de referencia obtenidos automáticamente para transformar el volumen preoperatorio en decúbito prono al espacio quirúrgico y estimar la localización del tumor. El segundo enfoque consiste en un nuevo modelo biomecánico de la mama bajo el efecto de la gravedad que integra un modelo constitutivo viscohiperelástico para simular la transformación de la postura prona a supina y estimar la posición del tumor. Por último, hemos diseñado una nueva metodología para aprender la gran deformación de la mama desde la posición preoperatoria a la intraoperatoria utilizando un enfoque de registro basado en el aprendizaje profundo de superficie a volumen que disminuye significativamente el tiempo de cálculo necesario para localizar la posición del tumor. Estas propuestas han sido desarrolladas y evaluadas con una cohorte de 67 casos retrospectivos de cáncer de mama que incluyen información de imagen tanto en posición prona como supina. Los resultados obtenidos han demostrado que las metodologías propuestas tienen potencial para ser utilizadas como métodos complementarios o alternativos para la prelocalización tumoral en la cirugía o terapia del cáncer de mama

Prone to supine surface based registration workflow for breast tumor localization in surgical planning

Breast cancer is the most frequent cancer in women worldwide. Screening programs and imaging improvements have increased the detection of clinically occult non-palpable lesions requiring preoperative localization. Image-guided wire localization (WGL) is the current standard of care for the excision of non-palpable carcinomas during breast conserving surgery (BCS). Due to the current limitations of intraoperative tumor localization approaches, the integration of the information from multimodal imaging may be especially relevant in surgical planning. This work presents a workflow to perform a prone image-to-surgical physical data alignment in order to determine the correspondence between the tumor identified in the preoperative image and the final position of the tumor in the surgical position. The evaluation of the methodology has been carried out in 18 cases achieving an average localization error of 10.40 mm and 9.84 mm in 11 small lesion cases (less than 1 cm in diameter)

Prone to supine surface-based registration for surgical planning in breast cancer treatment

Breast cancer is the most common invasive cancer in women worldwide. Many women with breast cancer have their malignant tumors detected before the lesions become clinically palpable. Occult lesions must be marked for the surgeon to ensure that they can be effectively resected. Image-guided wire localization (WGL) is the current standard of care for the excision of non-palpable carcinomas during breast conserving surgery. The integration of the information from multimodal imaging may be especially relevant in surgical planning as complement or an alternative to WGL. The combination of information from images in different positions is especially difficult due to large breast deformation. This work presents a system based on surface registration to localize the lesion in the operative position, starting from a prone MRI study and a surface of the patient in the supine positon. The pre-operative surface from the MRI is registered to the surface obtained in a supine position similar to the intraoperative setting. Triangular meshes have been used to model breast surface in both positions and surfaces are aligned using a Laplacian deformation with fiducials automatically obtained from 3 anatomical references. The evaluation of the methodology has been carried out in 13 cases in which a supine- CT was available achieving an average localization error of 6.7 m