Measuring digital pathology throughput and tissue dropouts
Digital pathology operations that precede viewing by a pathologist have a substantial impact on costs and fidelity of the digital image. Scan time and file size determine throughput and storage costs, whereas tissue omission during digital capture (“dropouts”) compromises downstream interpretation....
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Published in | Journal of pathology informatics Vol. 13; no. 1; p. 8 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
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United States
Elsevier Inc
01.01.2022
Wolters Kluwer India Pvt. Ltd Medknow Publications & Media Pvt. Ltd Wolters Kluwer - Medknow Elsevier |
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Abstract | Digital pathology operations that precede viewing by a pathologist have a substantial impact on costs and fidelity of the digital image. Scan time and file size determine throughput and storage costs, whereas tissue omission during digital capture (“dropouts”) compromises downstream interpretation. We compared how these variables differ across scanners.
A 212 slide set randomly selected from a gynecologic-gestational pathology practice was used to benchmark scan time, file size, and image completeness. Workflows included the Hamamatsu S210 scanner (operated under default and optimized profiles) and the Leica GT450. Digital tissue dropouts were detected by the aligned overlay of macroscopic glass slide camera images (reference) with images created by the slide scanners whole slide images.
File size and scan time were highly correlated within each platform. Differences in GT450, default S210, and optimized S210 performance were seen in average file size (1.4 vs. 2.5 vs. 3.4 GB) and scan time (93 vs. 376 vs. 721 s). Dropouts were seen in 29.5% (186/631) of successful scans overall: from a low of 13.7% (29/212) for the optimized S210 profile, followed by 34.6% (73/211) for the GT450 and 40.4% (84/208) for the default profile S210 profile. Small dislodged fragments, “shards,” were dropped in 22.2% (140/631) of slides, followed by tissue marginalized at the glass slide edges, 6.2% (39/631). “Unique dropouts,” those for which no equivalent appeared elsewhere in the scan, occurred in only three slides. Of these, 67% (2/3) were “floaters” or contaminants from other cases.
Scanning speed and resultant file size vary greatly by scanner type, scanner operation settings, and clinical specimen mix (tissue type, tissue area). Digital image fidelity as measured by tissue dropout frequency and dropout type also varies according to the tissue type and scanner. Dropped tissues very rarely (1/631) represent actual specimen tissues that are not represented elsewhere in the scan, so in most cases cannot alter the diagnosis. Digital pathology platforms vary in their output efficiency and image fidelity to the glass original and should be matched to the intended application. |
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AbstractList | Background: Digital pathology operations that precede viewing by a pathologist have a substantial impact on costs and fidelity of the digital image. Scan time and file size determine throughput and storage costs, whereas tissue omission during digital capture (“dropouts”) compromises downstream interpretation. We compared how these variables differ across scanners. Methods: A 212 slide set randomly selected from a gynecologic-gestational pathology practice was used to benchmark scan time, file size, and image completeness. Workflows included the Hamamatsu S210 scanner (operated under default and optimized profiles) and the Leica GT450. Digital tissue dropouts were detected by the aligned overlay of macroscopic glass slide camera images (reference) with images created by the slide scanners whole slide images. Results: File size and scan time were highly correlated within each platform. Differences in GT450, default S210, and optimized S210 performance were seen in average file size (1.4 vs. 2.5 vs. 3.4 GB) and scan time (93 vs. 376 vs. 721 s). Dropouts were seen in 29.5% (186/631) of successful scans overall: from a low of 13.7% (29/212) for the optimized S210 profile, followed by 34.6% (73/211) for the GT450 and 40.4% (84/208) for the default profile S210 profile. Small dislodged fragments, “shards,” were dropped in 22.2% (140/631) of slides, followed by tissue marginalized at the glass slide edges, 6.2% (39/631). “Unique dropouts,” those for which no equivalent appeared elsewhere in the scan, occurred in only three slides. Of these, 67% (2/3) were “floaters” or contaminants from other cases. Conclusions: Scanning speed and resultant file size vary greatly by scanner type, scanner operation settings, and clinical specimen mix (tissue type, tissue area). Digital image fidelity as measured by tissue dropout frequency and dropout type also varies according to the tissue type and scanner. Dropped tissues very rarely (1/631) represent actual specimen tissues that are not represented elsewhere in the scan, so in most cases cannot alter the diagnosis. Digital pathology platforms vary in their output efficiency and image fidelity to the glass original and should be matched to the intended application. Digital pathology operations that precede viewing by a pathologist have a substantial impact on costs and fidelity of the digital image. Scan time and file size determine throughput and storage costs, whereas tissue omission during digital capture (“dropouts”) compromises downstream interpretation. We compared how these variables differ across scanners. A 212 slide set randomly selected from a gynecologic-gestational pathology practice was used to benchmark scan time, file size, and image completeness. Workflows included the Hamamatsu S210 scanner (operated under default and optimized profiles) and the Leica GT450. Digital tissue dropouts were detected by the aligned overlay of macroscopic glass slide camera images (reference) with images created by the slide scanners whole slide images. File size and scan time were highly correlated within each platform. Differences in GT450, default S210, and optimized S210 performance were seen in average file size (1.4 vs. 2.5 vs. 3.4 GB) and scan time (93 vs. 376 vs. 721 s). Dropouts were seen in 29.5% (186/631) of successful scans overall: from a low of 13.7% (29/212) for the optimized S210 profile, followed by 34.6% (73/211) for the GT450 and 40.4% (84/208) for the default profile S210 profile. Small dislodged fragments, “shards,” were dropped in 22.2% (140/631) of slides, followed by tissue marginalized at the glass slide edges, 6.2% (39/631). “Unique dropouts,” those for which no equivalent appeared elsewhere in the scan, occurred in only three slides. Of these, 67% (2/3) were “floaters” or contaminants from other cases. Scanning speed and resultant file size vary greatly by scanner type, scanner operation settings, and clinical specimen mix (tissue type, tissue area). Digital image fidelity as measured by tissue dropout frequency and dropout type also varies according to the tissue type and scanner. Dropped tissues very rarely (1/631) represent actual specimen tissues that are not represented elsewhere in the scan, so in most cases cannot alter the diagnosis. Digital pathology platforms vary in their output efficiency and image fidelity to the glass original and should be matched to the intended application. BACKGROUNDDigital pathology operations that precede viewing by a pathologist have a substantial impact on costs and fidelity of the digital image. Scan time and file size determine throughput and storage costs, whereas tissue omission during digital capture ("dropouts") compromises downstream interpretation. We compared how these variables differ across scanners. METHODSA 212 slide set randomly selected from a gynecologic-gestational pathology practice was used to benchmark scan time, file size, and image completeness. Workflows included the Hamamatsu S210 scanner (operated under default and optimized profiles) and the Leica GT450. Digital tissue dropouts were detected by the aligned overlay of macroscopic glass slide camera images (reference) with images created by the slide scanners whole slide images. RESULTSFile size and scan time were highly correlated within each platform. Differences in GT450, default S210, and optimized S210 performance were seen in average file size (1.4 vs. 2.5 vs. 3.4 GB) and scan time (93 vs. 376 vs. 721 s). Dropouts were seen in 29.5% (186/631) of successful scans overall: from a low of 13.7% (29/212) for the optimized S210 profile, followed by 34.6% (73/211) for the GT450 and 40.4% (84/208) for the default profile S210 profile. Small dislodged fragments, "shards," were dropped in 22.2% (140/631) of slides, followed by tissue marginalized at the glass slide edges, 6.2% (39/631). "Unique dropouts," those for which no equivalent appeared elsewhere in the scan, occurred in only three slides. Of these, 67% (2/3) were "floaters" or contaminants from other cases. CONCLUSIONSScanning speed and resultant file size vary greatly by scanner type, scanner operation settings, and clinical specimen mix (tissue type, tissue area). Digital image fidelity as measured by tissue dropout frequency and dropout type also varies according to the tissue type and scanner. Dropped tissues very rarely (1/631) represent actual specimen tissues that are not represented elsewhere in the scan, so in most cases cannot alter the diagnosis. Digital pathology platforms vary in their output efficiency and image fidelity to the glass original and should be matched to the intended application. |
ArticleNumber | 100170 |
Author | Siegmund, Stephanie Milstone, David S. Hwang, David H. Bruce, Alexander Mutter, George L. |
AuthorAffiliation | 1 Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA 2 Department of Pathology, Harvard Medical School, Boston, MA, USA |
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BackLink | https://www.ncbi.nlm.nih.gov/pubmed/35136675$$D View this record in MEDLINE/PubMed |
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CitedBy_id | crossref_primary_10_1016_j_jpi_2023_100321 crossref_primary_10_1002_aisy_202300672 |
Cites_doi | 10.1038/modpathol.2011.220 10.1111/his.13403 10.1111/his.13953 10.4103/jpi.jpi_22_19 10.1007/s00428-015-1780-1 10.1080/00313020126323 10.1136/jclinpath-2020-206943 10.1111/his.12879 10.1038/s41379-020-0601-5 10.1097/PAS.0000000000000930 10.1097/PGP.0b013e3181c713a8 10.1177/1357633X18818745 10.1097/DAD.0000000000000888 10.1136/jclinpath-2020-206786 10.1136/jclinpath-2020-206715 10.5858/arpa.2020-0372-SA |
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References | Sağlam, Usubütün, Dolgun (bb0065) 2017; 1 Carlson, Jarboe, Kindelberger, Nucci, Hirsch, Crum (bb0075) 2010; 29 Browning, Fryer, Roskell (bb0010) 2021; 74 Mills, Gradecki, Horton (bb0085) 2018; 42 Chong, Palma-Diaz, Fisher (bb0035) 2019; 10 Cimadamore, Lopez-Beltran, Scarpelli, Cheng, Montironi (bb0005) 2020; 73 Williams, Hanby, Millican-Slater, Nijhawan, Verghese, Treanor (bb0045) 2018; 72 Snead, Tsang, Meskiri (bb0055) 2016; 68 Stathonikos, Nguyen, Spoto, Verdaasdonk, van Diest (bb0030) 2019; 75 Usubutun, Mutter, Saglam (bb0070) 2012; 25 Duggan, Brashert, Ostor (bb0080) 2001; 33 Hanna, Reuter, Ardon (bb0015) 2020; 33 Stathonikos, Nguyen, van Diest (bb0025) 2021; 74 Voelker, Stauch, Strehl, Azima, Mueller-Hermelink (bb0040) 2020; 26 Lee, Jedrych, Pantanowitz, Ho (bb0050) 2018; 40 Loughrey, Kelly, Houghton (bb0060) 2015; 467 Henriksen, Kolognizak, Houghton (bb0020) 2020; 144 Loughrey (10.4103/jpi.jpi_5_21_bb0060) 2015; 467 Chong (10.4103/jpi.jpi_5_21_bb0035) 2019; 10 Stathonikos (10.4103/jpi.jpi_5_21_bb0025) 2021; 74 Snead (10.4103/jpi.jpi_5_21_bb0055) 2016; 68 Hanna (10.4103/jpi.jpi_5_21_bb0015) 2020; 33 Lee (10.4103/jpi.jpi_5_21_bb0050) 2018; 40 Mills (10.4103/jpi.jpi_5_21_bb0085) 2018; 42 Henriksen (10.4103/jpi.jpi_5_21_bb0020) 2020; 144 Stathonikos (10.4103/jpi.jpi_5_21_bb0030) 2019; 75 Cimadamore (10.4103/jpi.jpi_5_21_bb0005) 2020; 73 Voelker (10.4103/jpi.jpi_5_21_bb0040) 2020; 26 Usubutun (10.4103/jpi.jpi_5_21_bb0070) 2012; 25 Williams (10.4103/jpi.jpi_5_21_bb0045) 2018; 72 Duggan (10.4103/jpi.jpi_5_21_bb0080) 2001; 33 Sağlam (10.4103/jpi.jpi_5_21_bb0065) 2017; 1 Browning (10.4103/jpi.jpi_5_21_bb0010) 2021; 74 Carlson (10.4103/jpi.jpi_5_21_bb0075) 2010; 29 |
References_xml | – volume: 40 start-page: 17 year: 2018 end-page: 23 ident: bb0050 article-title: Validation of digital pathology for primary histopathological diagnosis of routine, inflammatory dermatopathology cases publication-title: Am J Dermatopathol contributor: fullname: Ho – volume: 1 start-page: 177 year: 2017 end-page: 191 ident: bb0065 article-title: Diagnostic and treatment reproducibility of cervical intraepithelial neoplasia/squamous intraepithelial lesion and factors affecting the diagnosis publication-title: Turk Patoloji Derg contributor: fullname: Dolgun – volume: 74 start-page: 129 year: 2021 end-page: 132 ident: bb0010 article-title: Role of digital pathology in diagnostic histopathology in the response to COVID-19: Results from a survey of experience in a UK tertiary referral hospital publication-title: J Clin Pathol contributor: fullname: Roskell – volume: 144 start-page: 1311 year: 2020 end-page: 1320 ident: bb0020 article-title: Rapid validation of telepathology by an academic neuropathology practice during the COVID-19 pandemic publication-title: Arch Pathol Lab Med contributor: fullname: Houghton – volume: 33 start-page: 2115 year: 2020 end-page: 2127 ident: bb0015 article-title: Validation of a digital pathology system including remote review during the COVID-19 pandemic publication-title: Mod Pathol contributor: fullname: Ardon – volume: 42 start-page: 53 year: 2018 end-page: 59 ident: bb0085 article-title: Diagnostic efficiency in digital pathology: A comparison of optical versus digital assessment in 510 surgical pathology cases publication-title: Am J Surg Pathol contributor: fullname: Horton – volume: 10 start-page: 31 year: 2019 ident: bb0035 article-title: The California telepathology service: UCLA’s experience in deploying a regional digital pathology subspecialty consultation network publication-title: J Pathol Inform contributor: fullname: Fisher – volume: 72 start-page: 662 year: 2018 end-page: 671 ident: bb0045 article-title: Digital pathology for the primary diagnosis of breast histopathological specimens: An innovative validation and concordance study on digital pathology validation and training publication-title: Histopathology contributor: fullname: Treanor – volume: 25 start-page: 877 year: 2012 end-page: 884 ident: bb0070 article-title: Reproducibility of endometrial intraepithelial neoplasia diagnosis is good, but influenced by the diagnostic style of pathologists publication-title: Mod Pathol contributor: fullname: Saglam – volume: 75 start-page: 621 year: 2019 end-page: 635 ident: bb0030 article-title: Being fully digital: Perspective of a Dutch academic pathology laboratory publication-title: Histopathology contributor: fullname: van Diest – volume: 26 start-page: 261 year: 2020 end-page: 270 ident: bb0040 article-title: Diagnostic validity of static telepathology supporting hospitals without local pathologists in low-income countries publication-title: J Telemed Telecare contributor: fullname: Mueller-Hermelink – volume: 33 start-page: 292 year: 2001 end-page: 297 ident: bb0080 article-title: The accuracy and interobserver reproducibility of endometrial dating publication-title: Pathology contributor: fullname: Ostor – volume: 74 start-page: 415 year: 2021 end-page: 420 ident: bb0025 article-title: Rocky road to digital diagnostics: Implementation issues and exhilarating experiences publication-title: J Clin Pathol contributor: fullname: van Diest – volume: 467 start-page: 137 year: 2015 end-page: 144 ident: bb0060 article-title: Digital slide viewing for primary reporting in gastrointestinal pathology: A validation study publication-title: Virchows Arch contributor: fullname: Houghton – volume: 68 start-page: 1063 year: 2016 end-page: 1072 ident: bb0055 article-title: Validation of digital pathology imaging for primary histopathological diagnosis publication-title: Histopathology contributor: fullname: Meskiri – volume: 29 start-page: 310 year: 2010 end-page: 314 ident: bb0075 article-title: Serous tubal intraepithelial carcinoma: Diagnostic reproducibility and its implications publication-title: Int J Gynecol Pathol contributor: fullname: Crum – volume: 73 start-page: 695 year: 2020 end-page: 696 ident: bb0005 article-title: Digital pathology and COVID-19 and future crises: Pathologists can safely diagnose cases from home using a consumer monitor and a mini PC publication-title: J Clin Pathol contributor: fullname: Montironi – volume: 25 start-page: 877 year: 2012 ident: 10.4103/jpi.jpi_5_21_bb0070 article-title: Reproducibility of endometrial intraepithelial neoplasia diagnosis is good, but influenced by the diagnostic style of pathologists publication-title: Mod Pathol doi: 10.1038/modpathol.2011.220 contributor: fullname: Usubutun – volume: 72 start-page: 662 year: 2018 ident: 10.4103/jpi.jpi_5_21_bb0045 article-title: Digital pathology for the primary diagnosis of breast histopathological specimens: An innovative validation and concordance study on digital pathology validation and training publication-title: Histopathology doi: 10.1111/his.13403 contributor: fullname: Williams – volume: 75 start-page: 621 year: 2019 ident: 10.4103/jpi.jpi_5_21_bb0030 article-title: Being fully digital: Perspective of a Dutch academic pathology laboratory publication-title: Histopathology doi: 10.1111/his.13953 contributor: fullname: Stathonikos – volume: 10 start-page: 31 year: 2019 ident: 10.4103/jpi.jpi_5_21_bb0035 article-title: The California telepathology service: UCLA’s experience in deploying a regional digital pathology subspecialty consultation network publication-title: J Pathol Inform doi: 10.4103/jpi.jpi_22_19 contributor: fullname: Chong – volume: 467 start-page: 137 year: 2015 ident: 10.4103/jpi.jpi_5_21_bb0060 article-title: Digital slide viewing for primary reporting in gastrointestinal pathology: A validation study publication-title: Virchows Arch doi: 10.1007/s00428-015-1780-1 contributor: fullname: Loughrey – volume: 33 start-page: 292 year: 2001 ident: 10.4103/jpi.jpi_5_21_bb0080 article-title: The accuracy and interobserver reproducibility of endometrial dating publication-title: Pathology doi: 10.1080/00313020126323 contributor: fullname: Duggan – volume: 73 start-page: 695 year: 2020 ident: 10.4103/jpi.jpi_5_21_bb0005 article-title: Digital pathology and COVID-19 and future crises: Pathologists can safely diagnose cases from home using a consumer monitor and a mini PC publication-title: J Clin Pathol doi: 10.1136/jclinpath-2020-206943 contributor: fullname: Cimadamore – volume: 68 start-page: 1063 year: 2016 ident: 10.4103/jpi.jpi_5_21_bb0055 article-title: Validation of digital pathology imaging for primary histopathological diagnosis publication-title: Histopathology doi: 10.1111/his.12879 contributor: fullname: Snead – volume: 1 start-page: 177 year: 2017 ident: 10.4103/jpi.jpi_5_21_bb0065 article-title: Diagnostic and treatment reproducibility of cervical intraepithelial neoplasia/squamous intraepithelial lesion and factors affecting the diagnosis publication-title: Turk Patoloji Derg contributor: fullname: Sağlam – volume: 33 start-page: 2115 year: 2020 ident: 10.4103/jpi.jpi_5_21_bb0015 article-title: Validation of a digital pathology system including remote review during the COVID-19 pandemic publication-title: Mod Pathol doi: 10.1038/s41379-020-0601-5 contributor: fullname: Hanna – volume: 42 start-page: 53 year: 2018 ident: 10.4103/jpi.jpi_5_21_bb0085 article-title: Diagnostic efficiency in digital pathology: A comparison of optical versus digital assessment in 510 surgical pathology cases publication-title: Am J Surg Pathol doi: 10.1097/PAS.0000000000000930 contributor: fullname: Mills – volume: 29 start-page: 310 year: 2010 ident: 10.4103/jpi.jpi_5_21_bb0075 article-title: Serous tubal intraepithelial carcinoma: Diagnostic reproducibility and its implications publication-title: Int J Gynecol Pathol doi: 10.1097/PGP.0b013e3181c713a8 contributor: fullname: Carlson – volume: 26 start-page: 261 year: 2020 ident: 10.4103/jpi.jpi_5_21_bb0040 article-title: Diagnostic validity of static telepathology supporting hospitals without local pathologists in low-income countries publication-title: J Telemed Telecare doi: 10.1177/1357633X18818745 contributor: fullname: Voelker – volume: 40 start-page: 17 year: 2018 ident: 10.4103/jpi.jpi_5_21_bb0050 article-title: Validation of digital pathology for primary histopathological diagnosis of routine, inflammatory dermatopathology cases publication-title: Am J Dermatopathol doi: 10.1097/DAD.0000000000000888 contributor: fullname: Lee – volume: 74 start-page: 129 year: 2021 ident: 10.4103/jpi.jpi_5_21_bb0010 article-title: Role of digital pathology in diagnostic histopathology in the response to COVID-19: Results from a survey of experience in a UK tertiary referral hospital publication-title: J Clin Pathol doi: 10.1136/jclinpath-2020-206786 contributor: fullname: Browning – volume: 74 start-page: 415 year: 2021 ident: 10.4103/jpi.jpi_5_21_bb0025 article-title: Rocky road to digital diagnostics: Implementation issues and exhilarating experiences publication-title: J Clin Pathol doi: 10.1136/jclinpath-2020-206715 contributor: fullname: Stathonikos – volume: 144 start-page: 1311 year: 2020 ident: 10.4103/jpi.jpi_5_21_bb0020 article-title: Rapid validation of telepathology by an academic neuropathology practice during the COVID-19 pandemic publication-title: Arch Pathol Lab Med doi: 10.5858/arpa.2020-0372-SA contributor: fullname: Henriksen |
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SubjectTerms | Accuracy Contaminants Digital imaging Digital pathology Dropouts Image analysis Operations Original Pathology Scanner Scanners Whole-slide imaging |
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Title | Measuring digital pathology throughput and tissue dropouts |
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