Accuracy and Reliability of Infrared Thermography in Assessment of the Breasts of Women Affected by Cancer

Evaluate reliability and accuracy of infrared thermography in the assessment of women wth breasts cancer. Thirty-five participants had unilateral breast cancer and 17 control subjects were assessed using infrared thermography. To evaluate reliability, two professionals, who were experienced, measured the temperature of the infrared images in two different moments, with a one-week interval. Biopsy was used as a gold standard exam with regard identify breast cancer. The analysis illustrated excellent reliability in terms of the affected, contralateral and control breasts with the intra-class correlation coefficient values ranging from 0.948 to 0.999. Standard measurement error ranged from 0.04 to 0.28 °C, and minimum detectable change deviated from 0.11 to 0.78 °C. Moreover, low to moderate accuracy were observed in terms of the establishment of the breast cancer diagnosis with values of the area under the receiver operating characteristic (ROC) curve ranging from 0.571 and 0.749. Breasts affected by cancer present higher skin temperature compared to contralateral and control. Furthermore, excellent reliability of the analysis of the infrared images and low-moderate accuracy in terms diagnosis were observed. Considering the results, infrared thermography can be applied as an instrument complement the assessment of breast cancer patients, but not for diagnostic purposes.

[1]  A. Akobeng,et al.  Understanding diagnostic tests 3: receiver operating characteristic curves , 2007, Acta paediatrica.

[2]  Bernard Rachet,et al.  Cancer survival in five continents: a worldwide population-based study (CONCORD). , 2008, The Lancet. Oncology.

[3]  A. Hrõbjartsson,et al.  Guidelines for Reporting Reliability and Agreement Studies (GRRAS) were proposed. , 2011, Journal of clinical epidemiology.

[4]  D. Miglioretti,et al.  Screening outcomes in older US women undergoing multiple mammograms in community practice: does interval, age, or comorbidity score affect tumor characteristics or false positive rates? , 2013, Journal of the National Cancer Institute.

[5]  G. Wishart,et al.  The accuracy of digital infrared imaging for breast cancer detection in women undergoing breast biopsy. , 2010, European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology.

[6]  J. Kaneene,et al.  Risk factors for colic in the Michigan (USA) equine population. , 1997, Preventive veterinary medicine.

[7]  M. Espié.  The management of breast cancer. , 2014, Diagnostic and interventional imaging.

[8]  Francis Sahngun Nahm,et al.  Interexaminer reliability of infrared thermography for the diagnosis of complex regional pain syndrome , 2013, Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging.

[9]  M. Etehadtavakol,et al.  Level set method for segmentation of infrared breast thermograms , 2014, EXCLI journal.

[10]  Medical Advisory Secretariat.  Cancer screening with digital mammography for women at average risk for breast cancer, magnetic resonance imaging (MRI) for women at high risk: an evidence-based analysis. , 2010, Ontario health technology assessment series.

[11]  E. Y.-K. Ng,et al.  A review of thermography as promising non-invasive detection modality for breast tumor , 2009 .

[12]  Mohammad Ataei,et al.  Nonlinear analysis using Lyapunov exponents in breast thermograms to identify abnormal lesions , 2012 .

[13]  Pavel Crystal,et al.  Using sonography to screen women with mammographically dense breasts. , 2003, AJR. American journal of roentgenology.

[14]  P. Gupta,et al.  Evaluation of digital infra-red thermal imaging as an adjunctive screening method for breast carcinoma: a pilot study. , 2014, International journal of surgery.

[15]  J. Weir.  Quantifying test-retest reliability using the intraclass correlation coefficient and the SEM. , 2005, Journal of strength and conditioning research.

[16]  Mahnaz Etehadtavakol,et al.  BREAST THERMOGRAPHY AS A POTENTIAL NON-CONTACT METHOD IN THE EARLY DETECTION OF CANCER: A REVIEW , 2013 .

[17]  E. Y. K. Ng,et al.  Application of K- and Fuzzy c-Means for Color Segmentation of Thermal Infrared Breast Images , 2010, Journal of Medical Systems.

[18]  Weiwei Zhu,et al.  Cumulative probability of false-positive recall or biopsy recommendation after 10 years of screening mammography , 2011 .

[19]  E. Guirro,et al.  Reliability of different methodologies of infrared image analysis of myofascial trigger points in the upper trapezius muscle , 2015, Brazilian journal of physical therapy.

[20]  D. Miglioretti,et al.  Cumulative Probability of False-Positive Recall or Biopsy Recommendation After 10 Years of Screening Mammography , 2011, Annals of Internal Medicine.

[21]  Delaine Rodrigues-Bigaton,et al.  Intra and inter-rater reliability of infrared image analysis of masticatory and upper trapezius muscles in women with and without temporomandibular disorder. , 2013, Brazilian journal of physical therapy.

[22]  S. Koscielny,et al.  The rationale for early diagnosis of cancer--the example of breast cancer. , 1999, Acta oncologica.

[23]  E. Ng,et al.  Using shape contexts method for registration of contra lateral breasts in thermal images. , 2014, World journal of clinical oncology.

[24]  Brian L Sprague,et al.  Screening ultrasound as an adjunct to mammography in women with mammographically dense breasts. , 2015, American journal of obstetrics and gynecology.

[25]  S. Feig,et al.  Screening mammography benefit controversies: sorting the evidence. , 2014, Radiologic clinics of North America.

[26]  I. Fentiman,et al.  Digital infrared thermal imaging (DITI) of breast lesions: sensitivity and specificity of detection of primary breast cancers. , 2011, Clinical radiology.

[27]  Françoise Argoul,et al.  Wavelet-based multifractal analysis of dynamic infrared thermograms to assist in early breast cancer diagnosis , 2014, Front. Physiol..

[28]  M. Brioschi,et al.  Termometria cutânea: novos conceitos Skin thermometry: new concepts , 2003 .

[29]  Janet E. Hiller,et al.  A systematic review of elastography, electrical impedance scanning, and digital infrared thermography for breast cancer screening and diagnosis , 2013, Breast Cancer Research and Treatment.

[30]  M. Greiner,et al.  Principles and practical application of the receiver-operating characteristic analysis for diagnostic tests. , 2000, Preventive veterinary medicine.

[31]  Alessandra Kelly de Oliveira,et al.  Evolution of Skin Temperature after the Application of Compressive Forces on Tendon, Muscle and Myofascial Trigger Point , 2015, PloS one.

[32]  Vinod Chandran,et al.  Separable and non-separable discrete wavelet transform based texture features and image classification of breast thermograms , 2013 .