Significant reduction in the rate of false-negative cervical smears with neural network-based technology (PAPNET testing system)

Leopold G. Koss, Mark E. Sherman, Michael B. Cohen, Allen R. Anes, Teresa M. Darragh, Luciano B. Lemos, Betty Jane Mcclellan, Dorothy L. Rosenthal, Sedigheh Keyhani-Rofagha, Klaus Schreiber, Philip T. Valente

Research output: Contribution to journalArticle

45 Citations (Scopus)

Abstract

False-negative cervical Pap smears may lead to disability or death from carcinoma of the uterine cervix. New computer technology has led to the development of an interactive, neural network-based vision instrument to increase the accuracy of cervical smear screening. The instrument belongs to a new class of medical devices designed to provide computer-aided diagnosis (CADx). To test the instrument's performance, 487 archival negative smears (index smears) from 228 women with biopsy-documented high-grade precancerous lesions or invasive cervical carcinoma (index women) were retrieved from the files of 10 participating laboratories that were using federally mandated quality assurance procedures. Samples of sequential negative smears (total 9,666) were retrieved as controls. The instrument was used to identify evidence of missed cytological abnormalities, including atypical squamous or glandular cells of undetermined significance (ASCUS, AGUS), low-grade or high-grade squamous intraepithelial lesions (LSIL, HSIL) and carcinoma. Using the instrument, 98 false-negative index smears were identified in 72 of the 228 index women (31.6%, 95% confidence interval [CI]: 25% to 38%). Disregarding the debatable categories of ASCUS or AGUS, there were 44 women whose false-negative smears disclosed squamous intraepithelial lesions (SIL) or carcinoma (19.3%; 95% CI: 14.2% to 24.4%). Unexpectedly, SILs were also identified in 127 of 9,666 control negative smears (1.3%; 95% CI: 1.1% to 1.5%). Compared with historical performance data from several participating laboratories, the instrument increased the detection rate of SILs in control smears by 25% and increased the yield of quality control rescreening 5.1 times (P < 0.0001). These data provide evidence that conventional screening and quality control rescreening of cervical smears fail to identify a substantial number of abnormalities. A significant improvement in performance of screening of cervical smears could be achieved with the use of the instrument described in this report.

Original languageEnglish (US)
Pages (from-to)1196-1203
Number of pages8
JournalHuman Pathology
Volume28
Issue number10
DOIs
StatePublished - 1997
Externally publishedYes

Fingerprint

Vaginal Smears
Technology
Carcinoma
Confidence Intervals
Quality Control
Papanicolaou Test
Cervix Uteri
Biopsy
Equipment and Supplies
Squamous Intraepithelial Lesions of the Cervix
Atypical Squamous Cells of the Cervix

Keywords

  • Cervical cytology
  • Cervical smear screening
  • Computer-aided diagnosis
  • False-negatives
  • Neural networks
  • Papanicolaou smears
  • PAPNET

ASJC Scopus subject areas

  • Pathology and Forensic Medicine

Cite this

Significant reduction in the rate of false-negative cervical smears with neural network-based technology (PAPNET testing system). / Koss, Leopold G.; Sherman, Mark E.; Cohen, Michael B.; Anes, Allen R.; Darragh, Teresa M.; Lemos, Luciano B.; Mcclellan, Betty Jane; Rosenthal, Dorothy L.; Keyhani-Rofagha, Sedigheh; Schreiber, Klaus; Valente, Philip T.

In: Human Pathology, Vol. 28, No. 10, 1997, p. 1196-1203.

Research output: Contribution to journalArticle

Koss, LG, Sherman, ME, Cohen, MB, Anes, AR, Darragh, TM, Lemos, LB, Mcclellan, BJ, Rosenthal, DL, Keyhani-Rofagha, S, Schreiber, K & Valente, PT 1997, 'Significant reduction in the rate of false-negative cervical smears with neural network-based technology (PAPNET testing system)', Human Pathology, vol. 28, no. 10, pp. 1196-1203. https://doi.org/10.1016/S0046-8177(97)90258-6
Koss, Leopold G. ; Sherman, Mark E. ; Cohen, Michael B. ; Anes, Allen R. ; Darragh, Teresa M. ; Lemos, Luciano B. ; Mcclellan, Betty Jane ; Rosenthal, Dorothy L. ; Keyhani-Rofagha, Sedigheh ; Schreiber, Klaus ; Valente, Philip T. / Significant reduction in the rate of false-negative cervical smears with neural network-based technology (PAPNET testing system). In: Human Pathology. 1997 ; Vol. 28, No. 10. pp. 1196-1203.
@article{2dcc766697e740ad97fc2ac7dcee11e0,
title = "Significant reduction in the rate of false-negative cervical smears with neural network-based technology (PAPNET testing system)",
abstract = "False-negative cervical Pap smears may lead to disability or death from carcinoma of the uterine cervix. New computer technology has led to the development of an interactive, neural network-based vision instrument to increase the accuracy of cervical smear screening. The instrument belongs to a new class of medical devices designed to provide computer-aided diagnosis (CADx). To test the instrument's performance, 487 archival negative smears (index smears) from 228 women with biopsy-documented high-grade precancerous lesions or invasive cervical carcinoma (index women) were retrieved from the files of 10 participating laboratories that were using federally mandated quality assurance procedures. Samples of sequential negative smears (total 9,666) were retrieved as controls. The instrument was used to identify evidence of missed cytological abnormalities, including atypical squamous or glandular cells of undetermined significance (ASCUS, AGUS), low-grade or high-grade squamous intraepithelial lesions (LSIL, HSIL) and carcinoma. Using the instrument, 98 false-negative index smears were identified in 72 of the 228 index women (31.6{\%}, 95{\%} confidence interval [CI]: 25{\%} to 38{\%}). Disregarding the debatable categories of ASCUS or AGUS, there were 44 women whose false-negative smears disclosed squamous intraepithelial lesions (SIL) or carcinoma (19.3{\%}; 95{\%} CI: 14.2{\%} to 24.4{\%}). Unexpectedly, SILs were also identified in 127 of 9,666 control negative smears (1.3{\%}; 95{\%} CI: 1.1{\%} to 1.5{\%}). Compared with historical performance data from several participating laboratories, the instrument increased the detection rate of SILs in control smears by 25{\%} and increased the yield of quality control rescreening 5.1 times (P < 0.0001). These data provide evidence that conventional screening and quality control rescreening of cervical smears fail to identify a substantial number of abnormalities. A significant improvement in performance of screening of cervical smears could be achieved with the use of the instrument described in this report.",
keywords = "Cervical cytology, Cervical smear screening, Computer-aided diagnosis, False-negatives, Neural networks, Papanicolaou smears, PAPNET",
author = "Koss, {Leopold G.} and Sherman, {Mark E.} and Cohen, {Michael B.} and Anes, {Allen R.} and Darragh, {Teresa M.} and Lemos, {Luciano B.} and Mcclellan, {Betty Jane} and Rosenthal, {Dorothy L.} and Sedigheh Keyhani-Rofagha and Klaus Schreiber and Valente, {Philip T.}",
year = "1997",
doi = "10.1016/S0046-8177(97)90258-6",
language = "English (US)",
volume = "28",
pages = "1196--1203",
journal = "Human Pathology",
issn = "0046-8177",
publisher = "W.B. Saunders Ltd",
number = "10",

}

TY - JOUR

T1 - Significant reduction in the rate of false-negative cervical smears with neural network-based technology (PAPNET testing system)

AU - Koss, Leopold G.

AU - Sherman, Mark E.

AU - Cohen, Michael B.

AU - Anes, Allen R.

AU - Darragh, Teresa M.

AU - Lemos, Luciano B.

AU - Mcclellan, Betty Jane

AU - Rosenthal, Dorothy L.

AU - Keyhani-Rofagha, Sedigheh

AU - Schreiber, Klaus

AU - Valente, Philip T.

PY - 1997

Y1 - 1997

N2 - False-negative cervical Pap smears may lead to disability or death from carcinoma of the uterine cervix. New computer technology has led to the development of an interactive, neural network-based vision instrument to increase the accuracy of cervical smear screening. The instrument belongs to a new class of medical devices designed to provide computer-aided diagnosis (CADx). To test the instrument's performance, 487 archival negative smears (index smears) from 228 women with biopsy-documented high-grade precancerous lesions or invasive cervical carcinoma (index women) were retrieved from the files of 10 participating laboratories that were using federally mandated quality assurance procedures. Samples of sequential negative smears (total 9,666) were retrieved as controls. The instrument was used to identify evidence of missed cytological abnormalities, including atypical squamous or glandular cells of undetermined significance (ASCUS, AGUS), low-grade or high-grade squamous intraepithelial lesions (LSIL, HSIL) and carcinoma. Using the instrument, 98 false-negative index smears were identified in 72 of the 228 index women (31.6%, 95% confidence interval [CI]: 25% to 38%). Disregarding the debatable categories of ASCUS or AGUS, there were 44 women whose false-negative smears disclosed squamous intraepithelial lesions (SIL) or carcinoma (19.3%; 95% CI: 14.2% to 24.4%). Unexpectedly, SILs were also identified in 127 of 9,666 control negative smears (1.3%; 95% CI: 1.1% to 1.5%). Compared with historical performance data from several participating laboratories, the instrument increased the detection rate of SILs in control smears by 25% and increased the yield of quality control rescreening 5.1 times (P < 0.0001). These data provide evidence that conventional screening and quality control rescreening of cervical smears fail to identify a substantial number of abnormalities. A significant improvement in performance of screening of cervical smears could be achieved with the use of the instrument described in this report.

AB - False-negative cervical Pap smears may lead to disability or death from carcinoma of the uterine cervix. New computer technology has led to the development of an interactive, neural network-based vision instrument to increase the accuracy of cervical smear screening. The instrument belongs to a new class of medical devices designed to provide computer-aided diagnosis (CADx). To test the instrument's performance, 487 archival negative smears (index smears) from 228 women with biopsy-documented high-grade precancerous lesions or invasive cervical carcinoma (index women) were retrieved from the files of 10 participating laboratories that were using federally mandated quality assurance procedures. Samples of sequential negative smears (total 9,666) were retrieved as controls. The instrument was used to identify evidence of missed cytological abnormalities, including atypical squamous or glandular cells of undetermined significance (ASCUS, AGUS), low-grade or high-grade squamous intraepithelial lesions (LSIL, HSIL) and carcinoma. Using the instrument, 98 false-negative index smears were identified in 72 of the 228 index women (31.6%, 95% confidence interval [CI]: 25% to 38%). Disregarding the debatable categories of ASCUS or AGUS, there were 44 women whose false-negative smears disclosed squamous intraepithelial lesions (SIL) or carcinoma (19.3%; 95% CI: 14.2% to 24.4%). Unexpectedly, SILs were also identified in 127 of 9,666 control negative smears (1.3%; 95% CI: 1.1% to 1.5%). Compared with historical performance data from several participating laboratories, the instrument increased the detection rate of SILs in control smears by 25% and increased the yield of quality control rescreening 5.1 times (P < 0.0001). These data provide evidence that conventional screening and quality control rescreening of cervical smears fail to identify a substantial number of abnormalities. A significant improvement in performance of screening of cervical smears could be achieved with the use of the instrument described in this report.

KW - Cervical cytology

KW - Cervical smear screening

KW - Computer-aided diagnosis

KW - False-negatives

KW - Neural networks

KW - Papanicolaou smears

KW - PAPNET

UR - http://www.scopus.com/inward/record.url?scp=12644256648&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=12644256648&partnerID=8YFLogxK

U2 - 10.1016/S0046-8177(97)90258-6

DO - 10.1016/S0046-8177(97)90258-6

M3 - Article

C2 - 9343327

AN - SCOPUS:12644256648

VL - 28

SP - 1196

EP - 1203

JO - Human Pathology

JF - Human Pathology

SN - 0046-8177

IS - 10

ER -