PhiΦBreast & Theory of Spiral Cancer - New Diagnostic Techniques Breast Cancer Detection

Abstract

\n Background Breast cancer today is one of the most aggressive in women and new cases continue to increase worldwide. The incidence of this tumor is kept under control especially by surgery and to reduce mortality we need detect life threatening disease at an earlier stage. We conducted two years a study for the identification and characterization of suspicious breast lesions using a new diagnostic technique applied to ultrasonography and mammography called “PhiΦBreast.” Methods Identification and characterization of category C4-C5 lesions of the breast with high Predictive Positive PPV value, by means of a new innovative method called “PhiΦBreast” using the Golden Ratio (Phi, or Φ 1.618...) Fibonacci sequence and a Predictive Algorithm, applied to the ultrasonography and mammography with subsequent deepening with cytological examination using fine needle aspiration (FNAC), according to evaluation criteria of the Breast Imaging Report Data System (BI-RADS) and the American College of Radiology (ACR). Usefulness of this research is to detect the breast cancer early on with this new diagnostic technique, in addition to develop a classification model of the histological type identified in the section areas and the percentage of probability in relation between the golden spiral and Fibonacci sequence. This amazing intuition gave rise Theory of Spiral Cancer. Results Using Golden Ratio and Fibonacci sequence, applied to ultrasonography and mammography, we have experimented and developed a diagnostic map with characteristics of high probability of identifying suspicious lesions at an early stage. We examined 987 women, 55 lesions detected with PhiΦBreast pattern were classified according to BI-RADS descriptors for US-imaging, including morphologic features that had a high predictive value for the malignancy (p <0.001). This innovative diagnostic tecnique has shown a sensitivity 95%, a specificity 97%, a positive predictive value 97%, a negative predictive value 96%. The discriminating capacity of PhiΦBreast was significantly better than normal ultrasonography (P < 0,05). Furthermore with a predictive algorithm associated with malignant cytology after FNAC, we have classified different types of cancer potentially life threatening for patients. Conclusion PhiΦBreast could be an important new model diagnostic technique to be applied ultrasound and mammography for detection malignant lesions of category C4-C5.