Keywords:
Oncology, Breast, Computer applications, CT, CT-Quantitative, CAD, Computer Applications-Detection, diagnosis, Radiation therapy / Oncology, Computer Applications-General, Cancer, Molecular, genomics and proteomics, Neoplasia
Authors:
M. Awais, A. Rahim; Karachi/PK
DOI:
10.26044/ecr2019/C-1189
Aims and objectives
There are different phenotypic differences between cancers of the same organ which can only be visualized using radiographic imaging.
[1,
2] Breast carcinoma is the most common cancer with a reported prevalence of 1 in 9 women in Pakistan.
[3] Early and accurate detection of breast cancer and delineation of its histologic subtype is crucial to instituting appropriate treatment.
In the era of personalized medicine,
tailoring therapies to specific molecular and genomic profiles of cancers is essential for improving outcomes and making accurate prognostic inferences.
[4,
5]
Traditionally,
radiologic imaging has been used to diagnose,
stage and follow-up tumours only on the basis of size; in this regard,
the RECIST (Response Evaluation Criteria In Solid Tumours) criteria have been applied extensively.
More recently,
it has been demonstrated that CT textural analysis can provide far more information about tumours than can be perceived by the naked human eye.
[6,
7] These textural features are computed using mathematical computations of the CT voxel data and can be potentially used to predict various histological and molecular parameters.
[8] These parameters have the potential to be used as tumour biomarkers and predict tumour grade,
immunohistochemical features,
response to therapy and overall survival.
Textural analysis provides an unprecedented opportunity to improve the management of patients with cancers and revise clinical decision-making algorithms.
In the present study,
our aim was to ascertain whether CT textural parameters of primary tumour can be used to predict the histopathological and molecular parameters of breast carcinoma.
To our knowledge,
such a study has not been performed previously.