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DERM-SUCCESS FDA Pivotal Study: A Multi-Reader Multi-Case Evaluation of Primary Care Physicians' Skin Cancer Detection Using AI-Enabled Elastic Scattering Spectroscopy

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: DERM-SUCCESS FDA Pivotal Study: A Multi-Reader Multi-Case Evaluation of Primary Care Physicians' Skin Cancer Detection Using AI-Enabled Elastic Scattering Spectroscopy
Συγγραφείς: Ferris, Laura K, Jaklitsch, Erik, Seiverling, Elizabeth V, Agresta, Thomas, Cyr, Peggy
Πηγή: MaineHealth Maine Medical Center
Στοιχεία εκδότη: MaineHealth Knowledge Connection
Έτος έκδοσης: 2025
Συλλογή: MaineHealth Knowledge Connection
Θεματικοί όροι: artificial intelligence, basal cell carcinoma, diagnostic tools, elastic scattering spectroscopy, machine learning, melanoma, skin cancer, squamous cell carcinoma, technology, Humans, Skin Neoplasms (diagnosis), Physicians, Primary Care, Female, Male, Spectrum Analysis (methods, instrumentation), Sensitivity and Specificity, Middle Aged, United States, Aged, Algorithms, Adult
Περιγραφή: BACKGROUND: Elastic Scattering Spectroscopy (ESS), an optical tissue sampling technique, distinguishes between benign and malignant tissue in vivo without the need to perform a surgical biopsy. A handheld device that employs ESS enabled with an artificial intelligence algorithm was developed as an objective tool to aid primary care physicians (PCPs) in their management of lesions suspicious for skin cancer. The aim of this study was to assess and compare the diagnostic and management performance of PCPs with and without the use of the ESS device in detecting skin cancer. METHODS: In this clinical utility study, 108 PCPs evaluated 100 skin lesion cases (50 aided with the device output and 50 unaided by the device). For each case, PCPs provided a diagnosis, management decision, and level of confidence in that decision initially without, and then subsequently with, device output. Sensitivity, specificity, AUC, and confidence in their assessment prior to, and then with, device output were compared. RESULTS: With visual assessment assisted by device output, diagnostic sensitivity increased significantly from 71.1% to 81.7% (P = .0085) and referral sensitivity increased significantly from 82.0% to 91.4% (P = .0027) compared to visual assessment only. Device-aided diagnostic specificity decreased from 60.9% to 54.7% (P = .1896), and referral specificity decreased from 44.2% to 32.4% (P = .0256). Overall management performance (ie, AUC) also increased from 0.708 to 0.762, and increased from 0.567 to 0.682 for lesions which physicians reported low confidence in their unassisted management decision. Physicians reporting high confidence in their management assessment increased from 36.8% to 53.4%. CONCLUSION: Use of the ESS device output by PCPs significantly improved their diagnostic and management sensitivities as well as their overall management performance. The findings suggest the ESS device can improve PCP skin cancer detection and confidence in their skin lesion evaluation and management.
Τύπος εγγράφου: Thesis
Γλώσσα: unknown
Relation: https://knowledgeconnection.mainehealth.org/mmc/4118; https://pubmed.ncbi.nlm.nih.gov/40448353/
Διαθεσιμότητα: https://knowledgeconnection.mainehealth.org/mmc/4118
https://pubmed.ncbi.nlm.nih.gov/40448353/
Αριθμός Καταχώρησης: edsbas.62563F7A
Βάση Δεδομένων: BASE
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  – Url: https://knowledgeconnection.mainehealth.org/mmc/4118#
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  Data: DERM-SUCCESS FDA Pivotal Study: A Multi-Reader Multi-Case Evaluation of Primary Care Physicians' Skin Cancer Detection Using AI-Enabled Elastic Scattering Spectroscopy
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  Data: MaineHealth Maine Medical Center
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  Data: MaineHealth Knowledge Connection
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  Data: 2025
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  Label: Description
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  Data: BACKGROUND: Elastic Scattering Spectroscopy (ESS), an optical tissue sampling technique, distinguishes between benign and malignant tissue in vivo without the need to perform a surgical biopsy. A handheld device that employs ESS enabled with an artificial intelligence algorithm was developed as an objective tool to aid primary care physicians (PCPs) in their management of lesions suspicious for skin cancer. The aim of this study was to assess and compare the diagnostic and management performance of PCPs with and without the use of the ESS device in detecting skin cancer. METHODS: In this clinical utility study, 108 PCPs evaluated 100 skin lesion cases (50 aided with the device output and 50 unaided by the device). For each case, PCPs provided a diagnosis, management decision, and level of confidence in that decision initially without, and then subsequently with, device output. Sensitivity, specificity, AUC, and confidence in their assessment prior to, and then with, device output were compared. RESULTS: With visual assessment assisted by device output, diagnostic sensitivity increased significantly from 71.1% to 81.7% (P = .0085) and referral sensitivity increased significantly from 82.0% to 91.4% (P = .0027) compared to visual assessment only. Device-aided diagnostic specificity decreased from 60.9% to 54.7% (P = .1896), and referral specificity decreased from 44.2% to 32.4% (P = .0256). Overall management performance (ie, AUC) also increased from 0.708 to 0.762, and increased from 0.567 to 0.682 for lesions which physicians reported low confidence in their unassisted management decision. Physicians reporting high confidence in their management assessment increased from 36.8% to 53.4%. CONCLUSION: Use of the ESS device output by PCPs significantly improved their diagnostic and management sensitivities as well as their overall management performance. The findings suggest the ESS device can improve PCP skin cancer detection and confidence in their skin lesion evaluation and management.
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RecordInfo BibRecord:
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      – Text: unknown
    Subjects:
      – SubjectFull: artificial intelligence
        Type: general
      – SubjectFull: basal cell carcinoma
        Type: general
      – SubjectFull: diagnostic tools
        Type: general
      – SubjectFull: elastic scattering spectroscopy
        Type: general
      – SubjectFull: machine learning
        Type: general
      – SubjectFull: melanoma
        Type: general
      – SubjectFull: skin cancer
        Type: general
      – SubjectFull: squamous cell carcinoma
        Type: general
      – SubjectFull: technology
        Type: general
      – SubjectFull: Humans
        Type: general
      – SubjectFull: Skin Neoplasms (diagnosis)
        Type: general
      – SubjectFull: Physicians
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      – SubjectFull: Primary Care
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      – SubjectFull: Female
        Type: general
      – SubjectFull: Male
        Type: general
      – SubjectFull: Spectrum Analysis (methods
        Type: general
      – SubjectFull: instrumentation)
        Type: general
      – SubjectFull: Sensitivity and Specificity
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      – SubjectFull: Middle Aged
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      – SubjectFull: United States
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      – SubjectFull: Aged
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      – SubjectFull: Algorithms
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      – SubjectFull: Adult
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      – TitleFull: DERM-SUCCESS FDA Pivotal Study: A Multi-Reader Multi-Case Evaluation of Primary Care Physicians' Skin Cancer Detection Using AI-Enabled Elastic Scattering Spectroscopy
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              Y: 2025
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