Incorporating heterogeneity and anisotropy for surgical applications in breast deformation modeling.

Ringel, Morgan J; Richey, Winona L; Heiselman, Jon S; Meszoely, Ingrid M; Miga, Michael I

Ringel, Morgan J; Richey, Winona L; Heiselman, Jon S; Meszoely, Ingrid M; Miga, Michael I.

Afiliación

Ringel MJ; Vanderbilt University, Department of Biomedical Engineering, Nashville, TN, USA; Vanderbilt Institute for Surgery and Engineering, Nashville, TN, USA. Electronic address: morgan.j.ringel@Vanderbilt.edu.
Richey WL; Vanderbilt University, Department of Biomedical Engineering, Nashville, TN, USA; Vanderbilt Institute for Surgery and Engineering, Nashville, TN, USA.
Heiselman JS; Vanderbilt University, Department of Biomedical Engineering, Nashville, TN, USA; Vanderbilt Institute for Surgery and Engineering, Nashville, TN, USA; Memorial Sloan-Kettering Cancer Center, Department of Surgery, NY, New York, USA.
Meszoely IM; Vanderbilt University Medical Center, Division of Surgical Oncology, Nashville, TN, USA.
Miga MI; Vanderbilt University, Department of Biomedical Engineering, Nashville, TN, USA; Vanderbilt Institute for Surgery and Engineering, Nashville, TN, USA; Vanderbilt University, Department of Radiology and Radiological Sciences, Nashville, TN, USA; Vanderbilt University Medical Center, Department of Neu

Clin Biomech (Bristol, Avon) ; 104: 105927, 2023 04.

Article en En | MEDLINE | ID: mdl-36890069

RESUMEN

BACKGROUND: Simulating soft-tissue breast deformations is of interest for many applications including image fusion, longitudinal registration, and image-guided surgery. For the surgical use case, positional changes cause breast deformations that compromise the use of preoperative imaging to inform tumor excision. Even when acquiring imaging in the supine position, which better reflects surgical presentation, deformations still occur due to arm motion and orientation changes. A biomechanical modeling approach to simulate supine breast deformations for surgical applications must be both accurate and compatible with the clinical workflow. METHODS: A supine MR breast imaging dataset from n = 11 healthy volunteers was used to simulate surgical deformations by acquiring images in arm-down and arm-up positions. Three linear-elastic modeling approaches with varying levels of complexity were used to predict deformations caused by this arm motion: a homogeneous isotropic model, a heterogeneous isotropic model, and a heterogeneous anisotropic model using a transverse-isotropic constitutive model. FINDINGS: The average target registration errors for subsurface anatomical features were 5.4 ± 1.5 mm for the homogeneous isotropic model, 5.3 ± 1.5 mm for the heterogeneous isotropic model, and 4.7 ± 1.4 mm for the heterogeneous anisotropic model. A statistically significant improvement in target registration error was observed between the heterogeneous anisotropic model and both the homogeneous and the heterogeneous isotropic models (P < 0.01). INTERPRETATION: While a model that fully incorporates all constitutive complexities of anatomical structure likely achieves the best accuracy, a computationally tractable heterogeneous anisotropic model provided significant improvement and may be applicable for image-guided breast surgeries.

Asunto(s)

Mama; Cirugía Asistida por Computador; Humanos; Anisotropía; Mama/diagnóstico por imagen; Mama/cirugía; Imagen por Resonancia Magnética/métodos; Cirugía Asistida por Computador/métodos; Algoritmos

Palabras clave

Breast cancer; FEM; Lumpectomy; Registration; Surgical guidance

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Mama / Cirugía Asistida por Computador Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Clin Biomech (Bristol, Avon) Asunto de la revista: ENGENHARIA BIOMEDICA / FISIOLOGIA Año: 2023 Tipo del documento: Article Pais de publicación: Reino Unido

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