Microcalcification morphological descriptors and parenchyma fractal dimension hierarchically interact in breast cancer: A diagnostic perspective

Garima Verma, Maria Laura Luciani, Alessandro Palombo, Linda Metaxa, Giovanna Panzironi, Federica Pediconi, Alessandro Giuliani, Mariano Bizzarri, Virginia Todde

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Introduction Herein, we propose a Systems Biology approach aimed at identifying quantitative morphological parameters useful in discriminating benign from malignant breast microcalcifications at digital mammography. Materials and methods The study includes 31 patients in which microcalcifications had been detected during XR mammography and were further confirmed by stereotactic (XR-guided) biopsies. Patients were classified according to the BIRADS (Breast Imaging-Reporting and Data System), along with their parenchyma fractal dimension and biopsy size. A geometrical-topological characterization of microcalcifications was obtained as well. Results The 'size of biopsy’ was the parameter endowed with the highest discriminant power between malignant and benign lesions thus confirming the reliability of surgeon judgment. The quantitative shape evaluation of both lesions and parenchyma allowed for a promising prediction of the BIRADS score. The area of lesions and parenchyma fractal dimension show a complex distribution for malignant breast calcifications that are consistent with their qualitative morphological pattern. Fractal dimension analysis enables the user to obtain reliable results as proved by its efficiency in the prediction of the morphology of breast cancer. Conclusion By reconstructing a phase-space distribution of biophysical parameters, different patterns of aggregation are recognized corresponding to different calcium deposition patterns, while the combination of tissue and microcalcification morphological descriptors provide a statistically significant prediction of tumour grade. Clinical relevance The development of an automated morphology evaluation system can help during clinical evaluation while also sketching mechanistic hypotheses of microcalcification generation.

Original languageEnglish
Pages (from-to)1-6
Number of pages6
JournalComputers in Biology and Medicine
Volume93
DOIs
Publication statusPublished - Feb 1 2018

Fingerprint

Calcinosis
Fractals
Biopsy
Fractal dimension
Mammography
Breast Neoplasms
Breast
Imaging techniques
Information Systems
Tumors
Calcium
Agglomeration
Systems Biology
Tissue
Neoplasms

Keywords

  • Fractal dimension
  • Mammography
  • Microcalcification
  • Quantitative morphology
  • Radiology
  • Systems biology

ASJC Scopus subject areas

  • Computer Science Applications
  • Health Informatics

Cite this

Microcalcification morphological descriptors and parenchyma fractal dimension hierarchically interact in breast cancer : A diagnostic perspective. / Verma, Garima; Luciani, Maria Laura; Palombo, Alessandro; Metaxa, Linda; Panzironi, Giovanna; Pediconi, Federica; Giuliani, Alessandro; Bizzarri, Mariano; Todde, Virginia.

In: Computers in Biology and Medicine, Vol. 93, 01.02.2018, p. 1-6.

Research output: Contribution to journalArticle

Verma, Garima ; Luciani, Maria Laura ; Palombo, Alessandro ; Metaxa, Linda ; Panzironi, Giovanna ; Pediconi, Federica ; Giuliani, Alessandro ; Bizzarri, Mariano ; Todde, Virginia. / Microcalcification morphological descriptors and parenchyma fractal dimension hierarchically interact in breast cancer : A diagnostic perspective. In: Computers in Biology and Medicine. 2018 ; Vol. 93. pp. 1-6.
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abstract = "Introduction Herein, we propose a Systems Biology approach aimed at identifying quantitative morphological parameters useful in discriminating benign from malignant breast microcalcifications at digital mammography. Materials and methods The study includes 31 patients in which microcalcifications had been detected during XR mammography and were further confirmed by stereotactic (XR-guided) biopsies. Patients were classified according to the BIRADS (Breast Imaging-Reporting and Data System), along with their parenchyma fractal dimension and biopsy size. A geometrical-topological characterization of microcalcifications was obtained as well. Results The 'size of biopsy’ was the parameter endowed with the highest discriminant power between malignant and benign lesions thus confirming the reliability of surgeon judgment. The quantitative shape evaluation of both lesions and parenchyma allowed for a promising prediction of the BIRADS score. The area of lesions and parenchyma fractal dimension show a complex distribution for malignant breast calcifications that are consistent with their qualitative morphological pattern. Fractal dimension analysis enables the user to obtain reliable results as proved by its efficiency in the prediction of the morphology of breast cancer. Conclusion By reconstructing a phase-space distribution of biophysical parameters, different patterns of aggregation are recognized corresponding to different calcium deposition patterns, while the combination of tissue and microcalcification morphological descriptors provide a statistically significant prediction of tumour grade. Clinical relevance The development of an automated morphology evaluation system can help during clinical evaluation while also sketching mechanistic hypotheses of microcalcification generation.",
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