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Table 1 Studies retrieved from a systematic review of literature on breast thermography published in the twenty-first century

From: Breast thermography: a systematic review and meta-analysis

Author, year, Ref

Sample size (n cancer)

Patient description

Protocol

Sensitivity

specificity

Thermal resolution

Type of interpretation

Highlights and observations

Parisky et al., 2003 [53]

875 lesions in 769 patients (187)

Patients undergoing breast biopsy because of mammographically suspicious lesions

Dynamic

97.37%

14.41%

Unknown

Proprietary software

Funded by Computerized Thermal Imaging (manufacturer)

Thermogram interpretation required previous manual localization of the suspicious region

Images were acquired with the patient lying prone with the breasts suspended through openings in the imaging bed

Button et al., 2004 [54]

29 (8)

Patients scheduled for breast biopsy

Unknown

81.25%

53.66%

Unknown

Visual

Funded by Omnicorder Technologies Inc. (manufacturer)

Images were acquired with the patient lying prone with the breasts suspended through openings in the imaging bed

Yuan et al., 2005 [55]

106 (49)

Patients with breast tumors scheduled for surgery

Static

89.5%

91.9%

0.1K

Visual

 

Arora et al., 2008 [56]

94 lesions in 92 patients (60)

Patients undergoing breast biopsy because of abnormal mammographic and/or ultrasound findings

Dynamic

90.0%

44.1%

0.08K

Proprietary software

Funded by Infrared Sciences Corp. (manufacturer)

Wishart et al., 2010 [57]

106 lesions in 100 women (65)

Patients undergoing breast biopsy because of a lump on clinical breast examination or an abnormality on screening mammography

Dynamic

78%

48%

Unknown

Visual

Equipment loaned by Infrared Sciences Corp. (manufacturer)

Higher sensitivity (78%) and specificity (75%) with the proposed algorithm in women under 50. When combined with mammography, sensitivity increased to 89%

Wang et al., 2010 [58]

298 lesions in 276 patients (174)

Women undergoing excisional biopsy because of suspicious findings on mammograms or ultrasound

Static

92.0%

44.3%

0.1K

Linear combination of five IR signs

Funded by AG Digital Technology Corp. (manufacturer)

Thermogram interpretation required previous manual localization of the suspicious region

Kontos et al., 2011 [59]

63 (20)

Symptomatic patients

Static

25%

85%

Unknown

Color differences

Equipment loaned by Meditherm (manufacturer)

Kolaric et al., 2013 [60]

26 (20)

Patients scheduled for surgery with pathophysiological examination

Unknown

100%

55.6%

0.07K

Visual

5 of the 20 patients had bilateral cancer

Thermography detected 5 cancers that were missed by mammography

Collet et al., 2014 [61]

105 lesions in 99 patients (33)

Women undergoing biopsy for suspicious imaging findings

Dynamic

78.8%

48.6%

Unknown

Proprietary software

 

Yao et al., 2014 [62]

2036 (480)

Women undergoing biopsy for abnormal mammography and/or ultrasound results

Static

84.4%

94.0%

Unknown

Thermal releasing curve

Thermography obtained higher sensitivity than mammography (78.3%) and ultrasound (83.1%), but specificity of mammography was higher (98%)

Francis et al., 2014 [63]

36 (12)

Patients referred to the breast clinic for suspected breast abnormalities

Static

83.3%

83.3%

Unknown

Machine Learning

Rotational thermography. Images were acquired with the patient lying prone with the breasts suspended through openings in the imaging bed

Omranipour et al., 2016 [64]

132 (87)

Women undergoing biopsy for any clinical, mammographic, or ultrasonographic finding. They attended for any breast-related complaint or just for opportunistic screening

Dynamic

92.8%

41.9%

0.08K

Visual

Mammography had a lower sensitivity (80.5%) but a higher specificity (73.3%). The combination of mammography and thermography yielded a sensitivity of 96.6% with a specificity of 44.4%

Araujo et al., 2018 [65]

50 (14)

Patients with a suspected mass

Unknown

92.86%

86.11%

Unknown

Parameterized Mahalanobis distance

 

Morales-Cervantes et al., 2018 [66]

206 (8)

Patients with clinical evidence of a tumor suggestive of cancer had risk factors for breast cancer and were heading for consultation

Static

100%

68.68%

0.07K

Asymmetric thermal and vascular pattern

 

Sarigoz et al., 2018 [67]

54 (21)

Patients with palpable breast masses that were scheduled for biopsy due to suspicious findings in clinical and radiological evaluation

Static

95.24%

69.70%

0.1K

Thermal asymmetry

Thermogram interpretation required previous manual localization of the suspicious region

Hellgren et al., 2019 [68]

1727 (12)

Asymptomatic women with dense breasts

Dynamic

58.33%

87.11%

Unknown

Proprietary software

Funded by Real Imaging Ltd. (manufacturer)

All patients with suspicious thermograms but normal mammograms and ultrasounds were referred to MRI

Thermography detected 6 cancers in 5 women, in addition to the 7 that were identified by mammography

Sun et al., 2019 [69]

407 (196)

Patients with non-inflammatory, unilateral, and single-breast lesions undergoing biopsy

Static

86.7%

86.7%

Unknown

Thermal releasing curve, thermal asymmetry, and vascular features

 

Kakileti et al., 2020 [70]

470 (78)

470 women who presented for a breast health checkup

50.6% symptomatic:

49.4% asymptomatic:

Static

91.02%

82.39%

89.85%

69.04%

100%

92.41%

0.02K—0.5K

Proprietary software that uses ML

Funded by Thermalytix (manufacturer)

Images are acquired at two sites with three different thermal cameras

Asymptomatic: 100% sensitivity and 92.41% specificity

Symptomatic: 89.85% sensitivity and 69.04% specificity

27% young women (under 40): 100% sensitivity. 11 of the cancers were discovered in this group, all of them symptomatic

Mammography had lower sensitivity (85.96%) but higher specificity (94.05%). Among the asymptomatic group, the sensitivity of mammography was only 50%

Thermography correctly identified 71% of the T1 tumors (smaller than 2 cm), whereas mammography detected 68% of them

Singh et al., 2021 [71]

258 (63)

Symptomatic women

Static

82.5%

80.5%

0.02K

Proprietary software that uses ML

Funded by Thermalytix (manufacturer)

Da Luz et al., 2022 [72]

25 (10)

Patients referred for evaluation after breast lump detection

72% had dense breasts

Static

83%

74%

Unknown

Thermal asymmetry

Thermogram interpretation required previous manual localization of suspicious regions

Mammography obtained lower sensitivity (73%) and specificity (70%) and missed 4 cancers, all of them in patients with dense breasts. 6 of the biopsied benign nodules had BIRADS 4–6 on mammography (unnecessary biopsies)

Bansal et al., 2023 [73]

459 (21)

Women attending screening mammography;

36.6% with dense and 63.4% with non-dense breast tissue,

15% symptomatic and 85% asymptomatic

Unknown

95.24%

88.58%

Unknown

Proprietary software that uses ML

Funded by Thermalytix (manufacturer)

In women with dense breasts, the sensitivity was 100% and the specificity was 81.65%. Among these women, 22% were reported as BI-RADS 0 on mammography

Martín-Del-Campo-Mena et al., 2023 [74]

3337 (129)

Patients receiving screening mammography or complementary tests due to suspicion of breast cancer

Dynamic

94.87%

72.26%

0.02K

Machine Learning

Mammography had higher sensitivity (100%) and specificity (97.1%)