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3D CT Radiomic Analysis Improves Detection of Axillary Lymph Node Metastases Compared to Conventional Features in Patients With Locally Advanced Breast Cancer.
Barszczyk, Mark; Singh, Navneet; Alikhassi, Afsaneh; Van Oirschot, Matthew; Kuling, Grey; Kiss, Alex; Gandhi, Sonal; Nofech-Mozes, Sharon; Look Hong, Nicole; Bilbily, Alexander; Martel, Anne; Matsuura, Naomi; Curpen, Belinda.
Afiliación
  • Barszczyk M; Department of Medical Imaging, University of Toronto, Toronto, ON, Canada.
  • Singh N; Department of Breast Imaging, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.
  • Alikhassi A; Department of Medical Imaging, University of Toronto, Toronto, ON, Canada.
  • Van Oirschot M; Department of Radiology, Trillium Health Partners and the Institute for Better Health, Mississauga, ON, Canada.
  • Kuling G; Sunnybrook Health Sciences Centre, Sunnybrook Research Institute, Toronto, ON, Canada.
  • Kiss A; Department of Materials Science and Engineering, University of Toronto, Toronto, ON, Canada.
  • Gandhi S; Department of Medical Imaging, University of Toronto, Toronto, ON, Canada.
  • Nofech-Mozes S; Department of Breast Imaging, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.
  • Look Hong N; London Regional Cancer Program, London Health Sciences Centre, London, ON, Canada.
  • Bilbily A; Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada.
  • Martel A; Sunnybrook Health Sciences Centre, Sunnybrook Research Institute, Toronto, ON, Canada.
  • Matsuura N; Department of Medical Oncology, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.
  • Curpen B; Department of Laboratory Medicine and Molecular Diagnostics, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.
J Breast Imaging ; 6(4): 397-406, 2024 Jul 30.
Article en En | MEDLINE | ID: mdl-38752527
ABSTRACT

OBJECTIVE:

Preoperative detection of axillary lymph node metastases (ALNMs) from breast cancer is suboptimal; however, recent work suggests radiomics may improve detection of ALNMs. This study aims to develop a 3D CT radiomics model to improve detection of ALNMs compared to conventional imaging features in patients with locally advanced breast cancer.

METHODS:

Retrospective chart review was performed on patients referred to a specialty breast cancer center between 2015 and 2020 with US-guided biopsy-proven ALNMs and pretreatment chest CT. One hundred and twelve patients (224 lymph nodes) met inclusion and exclusion criteria and were assigned to discovery (n = 150 nodes) and testing (n = 74 nodes) cohorts. US-biopsy images were referenced in identifying ALNMs on CT, with contralateral nodes taken as negative controls. Positive and negative nodes were assessed for conventional features of lymphadenopathy as well as for 107 radiomic features extracted following 3D segmentation. Diagnostic performance of individual and combined radiomic features was evaluated.

RESULTS:

The strongest conventional imaging feature of ALNMs was short axis diameter ≥ 10 mm with a sensitivity of 64%, specificity of 95%, and area under the curve (AUC) of 0.89 (95% CI, 0.84-0.94). Several radiomic features outperformed conventional features, most notably energy, a measure of voxel density magnitude. This feature demonstrated a sensitivity, specificity, and AUC of 91%, 79%, and 0.94 (95% CI, 0.91-0.98) for the discovery cohort. On the testing cohort, energy scored 92%, 81%, and 0.94 (95% CI, 0.89-0.99) for sensitivity, specificity, and AUC, respectively. Combining radiomic features did not improve AUC compared to energy alone (P = .08).

CONCLUSION:

3D radiomic analysis represents a promising approach for noninvasive and accurate detection of ALNMs.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Axila / Neoplasias de la Mama / Tomografía Computarizada por Rayos X / Imagenología Tridimensional / Ganglios Linfáticos / Metástasis Linfática Límite: Adult / Aged / Female / Humans / Middle aged Idioma: En Revista: J Breast Imaging Año: 2024 Tipo del documento: Article País de afiliación: Canadá Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Axila / Neoplasias de la Mama / Tomografía Computarizada por Rayos X / Imagenología Tridimensional / Ganglios Linfáticos / Metástasis Linfática Límite: Adult / Aged / Female / Humans / Middle aged Idioma: En Revista: J Breast Imaging Año: 2024 Tipo del documento: Article País de afiliación: Canadá Pais de publicación: Estados Unidos