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Research Article | DOI: https://doi.org/10.31579/2693-4779/178
1 Director from Division of Diagnostic Imaging & Interventional Ultrasound - CMM Diagnostic Center - Cava de’ Tirreni, Italy
2 Member of the Board of Directors T. & L. De Beaumont Bonelli Foundation for Cancer Research - Naples, Italy
3 President Foundation T. & L. De Beaumont Bonelli for Cancer Research - Naples, Italy
*Corresponding Author: Giulio Tarro, President Foundation T. & L. De Beaumont Bonelli for Cancer Research - Naples, Italy.
Citation: Ersilio Trapanese, Giulio Tarro, (2024), Research Article: PhiΦBreast New Diagnostic Techniques for Breast Cancer Detection, Clinical Research and Clinical Trials, 9(2); DOI:10.31579/2693-4779/178
Copyright: © 2024, Giulio Tarro. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Received: 11 January 2024 | Accepted: 31 January 2024 | Published: 08 February 2024
Keywords: phiφbreast, predictive algorithm, golden ratio, fibonacci sequence, breast cancer
Background:
Today, breast cancer is one of the most aggressive cancers in women and new cases continue to increase worldwide. In order to reduce mortality, we need to detect this life-threatening disease at an earlier stage.
For two years, we have conducted a study for the identification and characterization of suspicious breast lesions using a new diagnostic technique applied to ultrasonography and mammography called “PhiΦBreast.”
Methods:
We have conducted a study for the identification and characterization of suspicious breast lesions using a new diagnostic technique applied to mammography and ultrasonography.
Ultrasound systems with high frequency probes was used, 10-15 MHz, and Digital Breast Tomosynthesis (DBT).
Identification and characterization of category C4-C5 lesions of the breast with high Predictive Positive PPV value, with 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 Cytology (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 and the use of this new diagnostic tecnique is to detect the breast cancer in early stage. 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 Ratio (Φ) and Fibonacci sequence.
Results:
With the use of 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 technique has shown a sensitivity of 95%, a specificity of 97%, a positive predictive value (PPV) of 97%, and negative predictive value (NPV) of 96%.
Furthermore, with a Predictive Algorithm associated with malignant cytology after FNAC, we have classified different types of potentially life-threatening cancers for patients.
Conclusion:
PhiΦBreast could be an important new model diagnostic technique to be applied mammography and ultrasound for detection of malignant lesions of category C4-C5.
In diagnostic imaging is fundamental to recognize predictively the characteristics of a potentially aggressive tumor. This new model could represent the cornerstone as an important contribution for early diagnosis of breast cancer.
Breast cancer is the most commonly diagnosed cancer among US women, with an estimated 268,600 newly diagnosed women with invasive disease (48,100 cases of ductal carcinoma in situ [DCIS]) in 2019, accounting for approximately 15.2%-30% of all new cancer cases among women, depending on the data sources [1-2].
In Europe, every year more than 200,000 women are affected by breast cancer every year, with an incidence ranging from 5 to 10
For two years, we have conducted a study for the identification and characterization of suspicious breast lesions using a new diagnostic technique applied to ultrasonography and mammography called “PhiΦBreast.”
All patients underwent to two-dimensional ultrasound examination (2 DUS).
Dynamic imaging sequences were acquired using ultrasound system with a 10-15 MHz high-frequency linear probes and Digital Breast Tomosynthesis procedure.
High-resolution real-time ultrasonography (US) can detect characteristics of breast nodules.
Characterization of the mammary nodules was performed according to the following criteria: shape, echostructure, level of echogenicity, margins, size and topographical area.
Using the method of PhiΦBreast ultrasonographic study, on 55/987 patients were identified solid lesions markedly hypoechoic echostructure, round shape, with irregular and infiltrative margins and cuneiform shape with blurred margins (Figure 1).
Figure 1. Ultrasonography Image of Suspicious Nodular Lesions Identified with PhiΦBreast Model.
Panel A solid lesion, round shape, markedly hypoechoic echostructure with irregular and infiltrative margins. Panel B solid lesion, cuneiform shape, markedly hypoechoic echostructure with blurred margins.
After having their consent, 55 selected patients underwent a mammography examination with subsequent diagnostic deepening Fine Needle Aspiration Cytology (FNAC) procedure under ultrasonography guidance.
PhiΦBreast imaging applied to the mammography in the craniocaudal (CC) view and mediolateral oblique (MLO) view has given risotto a mapping of neoplastic nonpalpable breast lesions (Figure 2 and Figure 3).
Figure 2. Golden Ratio (Φ) Breast Cancer Detection and Fibonacci Sequence
Cranial-caudal view (CC) show Fibonacci Spiral approximates the Golden Ratio (Φ) using mammogram inscribed in squares of integer Fibonacci number side, shown for square size (13,21,34,55,89,144) making use the following nomenclature "Fibonacci- number Side” (FS1, FS2, FS3, FS4, FS5, FS6). The arrow show extraordinary X-ray vision of the cancer accurately detected in FS6 side.
Figure 3: PhiΦBreast A New Diagnostic Technique for Breast Cancer Detection
Panel A show mediolateral oblique view (MLO) of the breast at mammographic X-ray with applied Golden Ratio and Fibonacci numbers of healthy individual. No nodules were detected along the Golden Ratio. Panel B PhiΦBreast imaging applied to the mammogram has provided a mapping of neoplastic lesion. White arrow highlights cancerous tumor detected in FS6 side of the Golden Spiral. Cancerous mass appears as a bright centrally dense and irregular image with borders spiculated edges.
PhiΦBreast produced important data for the elaboration of a Predictive Algorithm on the probability of development of various histological types of tumors and the percentage detectable in the areas of the Golden Ratio and the Fibonacci numbers, when applied in the breast (13,21,34,55,89,144) using the following nomenclature "Fibonacci-number Side" (FS1, FS2, FS3, FS4, FS5, FS6) (Table 1).
Table 1. ΦGolden Ratio and The Nomenclature *Fibonacci-number Side
Percentage of tumors detected in the Fibonacci-number Side: FS1-FS2 10% of ductal carcinomas in situ; FS3-FS4 21% of invasive ductal carcinomas; FS5 14% invasive lobular tumors and FS6 55% invasive carcinomas not otherwise specified.
The results of cytology identified 55 tumors:13 ductal carcinomas in situ, 10 invasive ductal carcinomas, 6 invasive lobular tumors and 26 invasive carcinomas not otherwise specified.
The surgery was established based on the type of tumor identified in patients in the preoperative phase.
The histological diagnosis confirmed the tumor nature of the cells of the analyzed tissues, performed according to the criteria established by the American College of Radiology (ACR) and Reporting Breast Imaging and Data System (BI- RADS).
Patients underwent blood chemistry controls and tumor markers. The follow up period lasted about 1 year.
The Golden Ratio (Phi, or Φ 1.618...) is a potentially unifying quantity of structure and function in nature, as best observed in phyllotactic patterns in plants. For centuries, Phi (Φ) has been identified in human anatomy, and in recent decades, Φ has been proved in human physiology as well with scientific studies of some authors [9-10]. With the use of Golden Ratio [11] and Fibonacci sequence [12] 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>This innovative diagnostic technique has shown a sensitivity of 95%, a specificity of 97%, a positive predictive value (PPV) of 97%, and negative predictive value (NPV) of 96%. Furthermore, with a Predictive Algorithm associated with malignant cytology after FNAC, we have classified different types of potentially life-threatening cancers for patients.
Fascinated by golden ratio and Fibonacci sequence, we have devised a new diagnostic imaging model called PhiΦBreast applied to ultrasonography and
mammography to early detection nodular lesions with echostructural features of malignancy.
The National Cancer Institute (NCI) recommends five categories for diagnosis of breast aspiration cytology [13] in order to bring a degree of uniformity to the diagnostic repoting. These categories are unsatisfactory (C1), benign lesion (C2), atypical, probably benign (C3), suspicious, probably malignant (C4), and malignat (C5).
However, some authors believe that C3 and C4 should be categorized in the same category [14-15].
The analyzed cytological samples were classified according to NHSBSP into the following categories: C4-C5 [16].
A modern predictive algorithm has been elaborated.
This diagnostic technique called PhiΦBreast in ultrasonography and mammography, respecting the criteria of the American College of Radiology (ACR) [17] & Breast Imaging Report Data System (BI-RADS) [18] proved to be reliable. Having compared our research with important magnetic resonance imaging (MRI) studies performed by various researchers [27,28.29.30.31], the early identification of malignant lesions was confirmed, with a high positive predictive value (PPV) with a sensitivity (95%) specificity (97%) value positive predictive (97%) negative predictive value (96%).
We selected 55 patients, which were subjected to a diagnostic deepening with mammography exam and used as a reading interpretation to mammogram the PhiΦBreast imaging method and subsequent FNAC [19] under ultrasound guidance with a 19-gauge needle by execution of three passages through the nodular lesion.
Suspicious lesions detected from topographic mapping were classified category C4-C5 (NCI guidelines) [20].
Patients were treated with different surgical techniques.
The Veronesi quadrantectomy [21] represents a milestone in the treatment of breast cancer, currently the first scientifically validated conservative protocol.
The Nipple Sparing Mastectomy (NSM) [22], the Skin-Sparing Mastectomy that includes the Nipple-Areolar Complex (SSM+NAC) [23] with lymphadenectomy and Intraoperative Radiation Teraphy (IORT) [24].
Post-operative histological results were all classified as carcinomas.
We paid special attention to the ability of PhiΦBreast to offer an innovative topographic diagnostic imaging of suspicious lesions and using a predictive algorithm.
Different types of tumors were detected in the Golden Section areas, using Fibonacci numbers for mapping and classify the percentage of cancers identified in the different sections.
Percentage of tumors detected in the Fibonacci-number side was as follows: FS1-FS2 (10%) of ductal carcinomas in situ; FS3-FS4 (21%) of invasive ductal carcinomas; FS5 (14%) invasive lobular tumors and FS6 (55%) invasive carcinomas not otherwise specified.
These new diagnostic techniques have been discussed in previous studies [ 25-26].
Described by other authors, irregular and spiculated margins have been shown to be associated with an increased likelihood of malignancy.
Liberman et al. [27] described in a study that a spicular margin was the most suspicious characteristic identified with a high PPV.
Wedegärtner et al. [28] reported an irregular margin of the lesion to be the most reliable morphological feature to indicate malignancy.
Schnall and colleagues [29] identified spiculated margins to be a highly predictive feature of the cancer image and Gutierrez et al. [30] found irregular or spiculated margins conferring the highest probability of malignancy by BI-RADS classification.
In a retrospective study, Tozaki and collaborators [31] found irregular shape (97%) and spiculated margins (100%) among the features with higher predictive value for carcinoma.
Availing Golden Ratio (Φ), Fibonacci sequence and Predictive Algorithm applied to ultrasonography and mammography, we have given rise to a new diagnostic imaging model called PhiΦBreast for the identification of category C4-C5 lesions with high PPV in respecting the criteria of the American College of Radiology (ACR) and Breast Imaging Reporting Data System (BI-RADS).
This original scientific paper could bring progress in science, an important advancement and discovery which could save more lives from despair and in the worst-case scenario of the patient's death.
PhiΦBreast could have important diagnostic imaging applications as a new strategy for thwart breast cancer.
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