Three-Dimensional Planning Tool for Breast Conserving Surgery: A Technological Review

Oliveira, Sara P.; Morgado, Pedro J.; Gouveia, Pedro; Teixeira, João F.; Bessa, Silvia; Monteiro, João; Zolfagharnasab, Hooshiar; Reis, Marta M.; Silva, Nuno L.; Veiga, Diana; Cardoso, M.J.; Oliveira, Hélder; Ferreira, Manuel

doi:10.1615/critrevbiomedeng.2018028476

Cited by 5 publications

(6 citation statements)

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“…Breast image fusion technology applied to MRI images and 3D surface scan into a synchronized (3D) digital breast model, is an achievement towards precision medicine. Research from previous authors has focused on multimodal registration of mammography, breast ultrasound and MRI, but never with both clinical validation and 3D surface data integration in the upright position [ 3 ]. To the best of our knowledge, this is the first paper validating MRI/3D scan fusion algorithms to create patient-specific 3D breast models, from cancer patients.…”

Section: Discussionmentioning

confidence: 99%

“…Medical data is multi-sourced: images are acquired in different instants of time and settings, inducing distinct deformations on the soft-tissue anisotropic breast. Previous research has focused primarily on the multimodal radiological registration [ 9 , 10 ], or 3D surface data reconstruction [ 11 ], while image registration between both modalities (breast surface and radiological information) is seldomly addressed [ 3 ].…”

Section: Methodsmentioning

confidence: 99%

“…Innovations in 3D imaging and digital high-tech industrial science have accelerated experimental advances in medical imaging. Recently, medical image fusion has been developed by combining multiple images from multiple imaging modalities to augment image quality and to increase clinical applicability [ 2 , 3 ]. The implicit image fusion and spatial interpretation of the treating physician or the patient can be subjective and prone to error if performed without a patient-specific digital breast model integrating the real breast torso and preoperative tumor location.…”

Section: Introductionmentioning

confidence: 99%

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3D digital breast cancer models with multimodal fusion algorithms

et al. 2020

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Breast cancer image fusion consists of registering and visualizing different sets of a patient synchronized torso and radiological images into a 3D model. Breast spatial interpretation and visualization by the treating physician can be augmented with a patient-specific digital breast model that integrates radiological images. But the absence of a ground truth for a good correlation between surface and radiological information has impaired the development of potential clinical applications. A new image acquisition protocol was designed to acquire breast Magnetic Resonance Imaging (MRI) and 3D surface scan data with surface markers on the patient’s breasts and torso. A patient-specific digital breast model integrating the real breast torso and the tumor location was created and validated with a MRI/3D surface scan fusion algorithm in 16 breast cancer patients. This protocol was used to quantify breast shape differences between different modalities, and to measure the target registration error of several variants of the MRI/3D scan fusion algorithm. The fusion of single breasts without the biomechanical model of pose transformation had acceptable registration errors and accurate tumor locations. The performance of the fusion algorithm was not affected by breast volume. Further research and virtual clinical interfaces could lead to fast integration of this fusion technology into clinical practice.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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3D digital breast cancer models with multimodal fusion algorithms

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“…The underlying idea being the creation of individualized 3D breast cancer models that allow the visualization of the tumor inside of the digital breast. Literature on this topic is sparser [3], and mostly resorts to BMs of pose transformation -computationally complex physical models often generalized from datasets of few patients -to recover large breast deformations caused by variations of the patient position. Moreover, those works usually map prone MRI (or a supine variation) to 3D surface scans of the patient on the surgical position (supine).…”

Section: Multimodal Registration and Validationmentioning

confidence: 99%

“…The creation of these models depends heavily on the advances and performance of multi-modal breast image registration algorithms, which have primordially been focused on the correct mapping of lesions and radiological anatomical structures, without integrating 3D surface scans [3].…”

Section: Introductionmentioning

confidence: 99%

Personalized 3D Breast Cancer Models with Automatic Image Segmentation and Registration

Bessa¹,

Teixeira²,

Carvalho³

et al. 2020

Proceedings of 3DBODY.TECH 2020 - 11th International Conference and Exhibition on 3D Body Scanning and Processing Technologies,

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Breast conservative surgery (BCS) combined with radiotherapy has become the treatment of choice for the majority of women suffering from breast cancer. Every year approximately 2.1million new cases arise worldwide, but fortunately the 10-year survival rate now exceeds 80% mostly due to the early detection of non-palpable breast cancer. The accurate localization of the tumor is of utmost importance to decrease the re-excision rate and necessity of a second surgery, and also pivotal to the minimization of unaesthetic outcomes caused by these interventions. Nevertheless, 7 out of 10 patients will need invasive pre-operative localization and women will live long lives with the dire consequences of cancer treatments. Currently, it is up to the physicians to correlate multimodal 2-dimensial (2D) sectional images to the 3D space for surgical planning. The challenge is now focused on the technology to create an alternative non-invasive tumor location procedure that can be ethical and fit to the clinical set. This paper describes an automatic image segmentation and registration algorithm that fuses 3D optical scans of the breast surface, with interior radiological data for tumor characterization, to build a personalized digital breast model that can potentially be used as a non-invasive digital pre-operative localization technique, improving tumor visualization and surgery planning.

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