Individual and combined effectiveness of palpation, thermography, and mammography in breast cancer screening

Gohagan, John K.; Rodes, Ned D.; Blackwell, Charles W.; Darby, William P.; Farrell, Corinne; Herder, Timothy; Pearson, Dinah K.; Spitznagel, Edward L.; Wallace, Marsha

doi:10.1016/0091-7435(80)90016-x

Cited by 16 publications

(8 citation statements)

References 6 publications

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“…This entity was considered rather extensively in the 1970s and 1980s [4], and was approved by the US Food and Drug Administration (FDA) as an adjunctive tool for the diagnosis of breast cancer, but not as a useful screening or diagnostic tool for breast malignancy, due to its low sensitivity and specificity [5,6]. However, since advanced digital equipment and recent advancements in technology and image processing methods have led to superior detection of heat waves, the current study focuses again on the subject, in order to investigate the potentially improved detection of breast pathology by digital thermographs.…”

Section: Introductionmentioning

confidence: 99%

Comparison of the Accuracy of Thermography and Mammography in the Detection of Breast Cancer

et al. 2016

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Background: Benefits and harms of screening mammography have been disputed in recent years. This fact, along with the limitations of mammography as well as its unavailability in all our medical centers, tempted us to evaluate the accuracy of thermography in detecting breast abnormalities. Patients and Methods: All patients who were candidates for breast biopsy were examined by both mammography and thermography before tissue sampling in a referral center between January 2013 and January 2014. We defined sensitivities and specificities, and positive predictive values (PPVs) and negative predictive values (NPVs), of the 2 modalities in comparison with histologic results as the gold standard. Results: 132 patients were included. The median age of all patients was 49.5 ± 10.3 years (range 24-75 years). The sensitivity, specificity, PPV, NPV, and accuracy for mammography were 80.5%, 73.3%, 85.4%, 66.0%, and 76.9%, respectively, whereas for thermography the figures were 81.6%, 57.8%, 78.9%, 61.9%, and 69.7%, respectively. Conclusion: Our study confirms that, at the present time, thermography cannot substitute for mammography for the early diagnosis of breast cancer.

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Section: Introductionmentioning

confidence: 99%

Comparison of the Accuracy of Thermography and Mammography in the Detection of Breast Cancer

et al. 2016

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“…However, it comes with high false-negative rates [2], the danger of ionizing radiation and is uncomfortable for the patients. In addition, it is not an accepted screening method, to detect breast cancer in young women [3], women with radiologically dense breasts or in women with breast implants [4]. As an alternative method, dynamic thermography has been investigated over the recent decades for detection of breast cancer as it eliminates the drawbacks mentioned above.…”

Section: Introductionmentioning

confidence: 99%

Feasibility test of Dynamic Cooling for detection of small tumors in IR thermographic breast imaging

Sadeghi

Boese

Maldonado

et al. 2019

Current Directions in Biomedical Engineering

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Thermographic imaging is a known technology to detect temperature differences. For medical applications, the patterns of heat distribution are used for diagnosis. It is already tested to visualize blood supply, inflammatory processes, and superficial or more extensive tumors, e.g. in the breast tissue. This method was promoted for breast screening purposes and as a substitute for mammography for mid aged women, but the results were not convincing for younger women, where tissue density is higher, tumor growth is often connected to local temperature increase and radiation-based mammography is not an option. Infrared (IR) thermography can support tumor screening. The screening should allow the early detection of small lesions even in the depth. Therefor we evaluated the feasibility of dynamic cooling in combination with IR imaging in a phantom study. A temperature-controllable gel phantom including a heating plate, a depth-adjustable heat source mimicking a tumor, and three sensors for temperature monitoring was built up. A raspberry pi device serves as a control unit to create a stable temperature balance comparable to a human breast. For the experiments, the tumor was placed in various depth. After cooling, the thermal recovery phase of the phantom was imaged using an IR camera and a webcam. A pixel-wise analysis of the IR data detects a higher gradient of temperature change in the tumor region. The experiments demonstrated the feasibility of tumor detection based on dynamic cooling and IR imaging.

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“…It is also uncomfortable, because the breast has to be compressed between flat surfaces to improve image quality. Furthermore, obtaining adequate images from radiologically dense breasts (with little fat) or in women with breast implants are difficult (Foster, 1998), and it is difficult to detect breast cancer in young women (Gohagan, Rodes, Blackwell, & Darby, 2004). Despite of these limitations, mammogram remains the gold standard for screenings (Gohagan et al, 2004;Moore, 2001).…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, obtaining adequate images from radiologically dense breasts (with little fat) or in women with breast implants are difficult (Foster, 1998), and it is difficult to detect breast cancer in young women (Gohagan, Rodes, Blackwell, & Darby, 2004). Despite of these limitations, mammogram remains the gold standard for screenings (Gohagan et al, 2004;Moore, 2001). Since early detection is important, new technologies such as Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET), Computed Tomography-Single Photon Emission Computed Tomography (CT-SPECT) (Del Guerra, Di Domenico, Fantini, & Gambaccini, 2003), and ultrasound have been applied as complement to mammogram (Ng & Fok, 2003).…”

Section: Introductionmentioning

confidence: 99%

A novel cognitive interpretation of breast cancer thermography with complementary learning fuzzy neural memory structure

Tan

Quek

et al. 2007

Expert Systems with Applications

101

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Early detection of breast cancer is the key to improve survival rate. Thermogram is a promising front-line screening tool as it is able to warn women of breast cancer up to 10 years in advance. However, analysis and interpretation of thermogram are heavily dependent on the analysts, which may be inconsistent and error-prone. In order to boost the accuracy of preliminary screening using thermogram without incurring additional financial burden, Complementary Learning Fuzzy Neural Network (CLFNN), FALCON-AART is proposed as the Computer-Assisted Intervention (CAI) tool for thermogram analysis. CLFNN is a neuroscience-inspired technique that provides intuitive fuzzy rules, human-like reasoning, and good classification performance. Confluence of thermogram and CLFNN offers a promising tool for fighting breast cancer.

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Individual and combined effectiveness of palpation, thermography, and mammography in breast cancer screening

Cited by 16 publications

References 6 publications

Comparison of the Accuracy of Thermography and Mammography in the Detection of Breast Cancer

Comparison of the Accuracy of Thermography and Mammography in the Detection of Breast Cancer

Feasibility test of Dynamic Cooling for detection of small tumors in IR thermographic breast imaging

A novel cognitive interpretation of breast cancer thermography with complementary learning fuzzy neural memory structure

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