Impact of deformation on a supine-positioned image-guided breast surgery approach

Richey, Winona L.; Heiselman, Jon S.; Luo, Ma; Meszoely, Ingrid M.; Miga, Michael I.

doi:10.1007/s11548-021-02452-8

Cited by 13 publications

(11 citation statements)

References 41 publications

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“…The nonrigid model-based registration method performed significantly better than the rigid registration method in both FRE and TRE, which is consistent with the fact that there are large nonrigid deformations that occur between arm-down to arm-up positions. 11 This result suggests that a BCS image guidance system would benefit from nonrigid registration to better localize subsurface breast tumors. However, the nonrigid modelbased registration performance was limited, and possible explanations for this may be the need for additional geometric data, the lack of heterogeneity or anisotropy in the model, or the lack of anatomic structural components in the model such as the suspensory Cooper's ligaments of the breast.…”

Section: Discussionmentioning

confidence: 93%

“…When considering registration, rigid techniques are fast but fail to capture large soft-tissue deformations that occur from changes in position. 10,11 Affine transformations can improve registration accuracy but only represent a global transformation. Nonrigid registration methods that utilize elastic biomechanical models can capture local deformations yet are nontrivial in implementation.…”

Section: Introductionmentioning

confidence: 99%

“…When considering registration, rigid techniques are fast but fail to capture large soft-tissue deformations that occur from changes in position 10 , 11 . Affine transformations can improve registration accuracy but only represent a global transformation.…”

Section: Introductionmentioning

confidence: 99%

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Supine magnetic resonance image registration for breast surgery: insights on material mechanics

et al. 2022

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.PurposeBreast conserving surgery (BCS) is a common procedure for early-stage breast cancer patients. Supine preoperative magnetic resonance (MR) breast imaging for visualizing tumor location and extent, while not standard for procedural guidance, is being explored since it more closely represents the surgical presentation compared to conventional diagnostic imaging positions. Despite this preoperative imaging position, deformation is still present between the supine imaging and surgical state. As a result, a fast and accurate image-to-physical registration approach is needed to realize image-guided breast surgery.ApproachIn this study, three registration methods were investigated on healthy volunteers’ breasts (n = 11) with the supine arm-down position simulating preoperative imaging and supine arm-up position simulating intraoperative presentation. The registration methods included (1) point-based rigid registration using synthetic fiducials, (2) nonrigid biomechanical model-based registration using sparse data, and (3) a data-dense three-dimensional diffeomorphic image-based registration from the Advanced Normalization Tools (ANTs) repository. Additionally, deformation metrics (volume change and anisotropy) were calculated from the ANTs deformation field to better understand breast material mechanics.ResultsThe average target registration errors (TRE) were 10.4 ± 2.3, 6.4 ± 1.5, and 2.8 ± 1.3 mm (mean ± standard deviation) and the average fiducial registration errors (FRE) were 7.8 ± 1.7, 2.5 ± 1.1, and 3.1 ± 1.1 mm for the point-based rigid, nonrigid biomechanical, and ANTs registrations, respectively. The mechanics-based deformation metrics revealed an overall anisotropic tissue behavior and a statistically significant difference in volume change between glandular and adipose tissue, suggesting that nonrigid modeling methods may be improved by incorporating material heterogeneity and anisotropy.ConclusionsOverall, registration accuracy significantly improved with increasingly flexible and data-dense registration methods. Analysis of these outcomes may inform the future development of image guidance systems for lumpectomy procedures.

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Section: Discussionmentioning

confidence: 93%

Section: Introductionmentioning

confidence: 99%

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Supine magnetic resonance image registration for breast surgery: insights on material mechanics

et al. 2022

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“…Over the last 20 years, biomechanical Finite Element (FE) modelling of human breast tissues has been investigated for various medical applications such as surgical procedure training (Babarenda Gamage et al, 2019), preoperative planning (Vavourakis et al (2016); Weis et al (2017)), clinical biopsy (Tagliabue et al, 2019), image registration (Han et al, 2013), mammography (Chung et al, 2008), or image-guided surgery (Richey et al, 2021). The choice of appropriate constitutive equations associated with each breast tissue has strong consequences on numerical simulations.…”

Section: Introductionmentioning

confidence: 99%

In vivo measurement of breast tissues stiffness using a light aspiration device

Briot¹,

Chagnon²,

Connesson³

2022

Clinical Biomechanics

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“…Although MRI-based supine approaches provide information regarding breast tissue motion, it is an addition to the current standard clinical practice. Furthermore, recent studies have shown that there is a significant deformation between surgical position and supine magnetic resonance positioning that need to be accounted for through image guidance [18]. Other groups proposed the use of the intraoperative surface acquired with an optical scan and to deform the preoperative MRI derived volume to match the surgical surface using finite element method (FEM) models with boundary conditions relying on skin-attached or anatomical markers.…”

Section: Introductionmentioning

confidence: 99%

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

Alfano¹,

Cordero‐Grande²,

Ortuño³

et al. 2022

IEEE Access

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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 imageto-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.

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Impact of deformation on a supine-positioned image-guided breast surgery approach

Cited by 13 publications

References 41 publications

Supine magnetic resonance image registration for breast surgery: insights on material mechanics

Supine magnetic resonance image registration for breast surgery: insights on material mechanics

In vivo measurement of breast tissues stiffness using a light aspiration device

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

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