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Inter- and intra-observer variability of computed tomography-based parenchymal- and ductal diameters in chronic pancreatitis: a multi-observer international study

Abdominal Radiology volume 48, pages 306–317 (2023)Cite this article

Abstract

Purpose

The need for incorporation of quantitative imaging biomarkers of pancreatic parenchymal and ductal structures has been highlighted in recent proposals for new scoring systems in chronic pancreatitis (CP). To quantify inter- and intra-observer variability in CT-based measurements of ductal- and gland diameters in CP patients.

Materials and Methods

Prospectively acquired pancreatic CT examinations from 50 CP patients were reviewed by 12 radiologists and four pancreatologists from 10 institutions. Assessment entailed measuring maximum diameter in the axial plane of four structures: (1) pancreatic head (PDhead), (2) pancreatic body (PDbody), (3) main pancreatic duct in the pancreatic head (MPDhead), and (4) body (MPDbody). Agreement was assessed by the 95% limits of agreement with the mean (LOAM), representing how much a single measurement for a specific subject may plausibly deviate from the mean of all measurements on the specific subject. Bland–Altman limits of agreement (LoA) were generated for intra-observer pairs.

Results

The 16 observers completed 6400 caliper placements comprising a first and second measurement session. The widest inter-observer LOAM was seen with PDhead (± 9.1 mm), followed by PDbody (± 5.1 mm), MPDhead (± 3.2 mm), and MPDbody (± 2.6 mm), whereas the mean intra-observer LoA width was ± 7.3, ± 5.1, ± 3.7, and ± 2.4 mm, respectively.

Conclusion

Substantial intra- and inter-observer variability was observed in pancreatic two-point measurements. This was especially pronounced for parenchymal and duct diameters of the pancreatic head. These findings challenge the implementation of two-point measurements as the foundation for quantitative imaging scoring systems in CP.

Graphical abstract

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Abbreviations

CT:

Computed tomography

CP:

Chronic pancreatitis

ICC:

Intraclass correlation coefficient

LoA:

Limits of agreement

DICOM:

Digital Imaging and Communications in Medicine

PDhead:

Largest parenchymal diameter of the pancreatic head

PDbody:

Largest parenchymal diameter of the pancreatic body

MPDhead:

Largest main pancreatic duct diameter in the pancreatic head

MPDbody:

Largest main pancreatic duct diameter in the pancreatic body

MRI:

Magnetic resonance imaging

SBPC:

Scandinavian Baltic Pancreatic Club

LOAM:

Limits of agreement with the mean

References

  1. Muniraj, T., Aslanian, H. R., Farrell, J. & Jamidar, P. A. Chronic pancreatitis, a comprehensive review and update. Part I: epidemiology, etiology, risk factors, genetics, pathophysiology, and clinical features. Dis. Mon. 60, 530–550 (2014).

  2. Conwell, D. L. et al. American Pancreatic Association Practice Guidelines in Chronic Pancreatitis: evidence-based report on diagnostic guidelines. Pancreas 43, 1143–1162 (2014).

    Article  Google Scholar 

  3. Frøkjær, J. B. et al. Guidelines for the Diagnostic Cross Sectional Imaging and Severity Scoring of Chronic Pancreatitis. Pancreatology 18, 764–773 (2018).

    Article  Google Scholar 

  4. Tirkes, T. et al. Reporting Standards for Chronic Pancreatitis by Using CT, MRI, and MR Cholangiopancreatography: The Consortium for the Study of Chronic Pancreatitis, Diabetes, and Pancreatic Cancer. Radiology 290, 207–215 (2019).

    Article  Google Scholar 

  5. Dasyam, A. K., Shah, Z. K., Tirkes, T., Dasyam, N. & Borhani, A. A. Cross-sectional imaging-based severity scoring of chronic pancreatitis: why it is necessary and how it can be done. Abdom Radiol (NY) 45, 1447–1457 (2020).

    Article  Google Scholar 

  6. Sarner, M. & Cotton, P. B. Classification of pancreatitis. Gut 25, 756–759 (1984).

    Article  CAS  Google Scholar 

  7. Whitcomb, D. C. et al. Chronic pancreatitis: An international draft consensus proposal for a new mechanistic definition. Pancreatology 16, 218–224 (2016).

    Article  Google Scholar 

  8. Kumar, H., DeSouza, S. V. & Petrov, M. S. Automated pancreas segmentation from computed tomography and magnetic resonance images: A systematic review. Comput. Methods Programs Biomed. 178, 319–328 (2019).

    Article  Google Scholar 

  9. Steinkohl, E. et al. Progression of parenchymal and ductal findings in patients with chronic pancreatitis: A 4-year follow-up MRI study. Eur. J. Radiol. 125, 108868 (2020).

    Article  Google Scholar 

  10. Kipp, J. P. et al. Normal pancreatic volume in adults is influenced by visceral fat, vertebral body width and age. Abdominal Radiology vol. 44 958–966 (2019).

    Article  Google Scholar 

  11. Lisitskaya, M. V. et al. Systematic approach for assessment of imaging features in chronic pancreatitis: a feasibility and validation study from the Scandinavian Baltic Pancreatic Club (SBPC) database. Abdom Radiol (NY) 45, 1468–1480 (2020).

    Article  Google Scholar 

  12. Razek, A. A. K. A., Elfar, E. & Abubacker, S. Interobserver agreement of computed tomography reporting standards for chronic pancreatitis. Abdom Radiol (NY) 44, 2459–2465 (2019).

    Article  Google Scholar 

  13. Olesen, S. S., Laukkarinen, J., Drewes, A. M. & Nojgaard, C. The Scandinavian Baltic Pancreatic Club (SBPC) Database: Design, Rationale and Characterisation of the Study Cohort. Pancreatology vol. 17 S58 (2017).

    Article  Google Scholar 

  14. Schneider, A., Löhr, J. M. & Singer, M. V. The M-ANNHEIM classification of chronic pancreatitis: introduction of a unifying classification system based on a review of previous classifications of the disease. J. Gastroenterol. 42, 101–119 (2007).

    Article  Google Scholar 

  15. Borgbjerg, J. Novel web-based tool for conducting observer performance studies in imaging research. (2016), accessed 25 August 2022, <https://epos.myesr.org/poster/esr/ecr2016/C-1635>.

  16. Borgbjerg, J. MULRECON: A Web-based Imaging Viewer for Visualization of Volumetric Images. Curr. Probl. Diagn. Radiol. 48, 531–534 (2019).

    Article  Google Scholar 

  17. Borgbjerg, J. Web-based imaging viewer for real-color volumetric reconstruction of human visible project and DICOM datasets. Clin. Anat. 34, 470–477 (2021).

    Article  Google Scholar 

  18. Christensen, H. S., Borgbjerg, J., Børty, L. & Bøgsted, M. On Jones et al.’s method for extending Bland-Altman plots to limits of agreement with the mean for multiple observers. BMC Med. Res. Methodol. 20, 304 (2020).

    Article  Google Scholar 

  19. McGraw, K. O. & Wong, S. P. Forming inferences about some intraclass correlation coefficients. Psychological Methods vol. 1 30–46 (1996).

    Article  Google Scholar 

  20. Cohen, J. Statistical Power Analysis for the Behavioral Sciences. (Routledge, 2013).

  21. deSouza, N. M. et al. Validated imaging biomarkers as decision-making tools in clinical trials and routine practice: current status and recommendations from the EIBALL* subcommittee of the European Society of Radiology (ESR). Insights Imaging 10, 87 (2019).

    Article  Google Scholar 

  22. Farzin, B. et al. Agreement studies in radiology research. Diagn. Interv. Imaging 98, 227–233 (2017).

    Article  CAS  Google Scholar 

  23. Trout, A. T. et al. Interobserver Agreement for CT and MRI Findings of Chronic Pancreatitis in Children: A Multicenter Ancillary Study Under the INSPPIRE Consortium. AJR Am. J. Roentgenol. 1–11 (2022).

  24. Trout, A. T. et al. Normal pancreatic parenchymal thickness by CT in healthy children. Pediatr. Radiol. 48, 1600–1605 (2018).

    Article  Google Scholar 

  25. Bankier, A. A., Levine, D., Halpern, E. F. & Kressel, H. Y. Consensus Interpretation in Imaging Research: Is There a Better Way? Radiology vol. 257 14–17 (2010).

    Article  Google Scholar 

  26. McNitt-Gray, M. F. et al. Determining the Variability of Lesion Size Measurements from CT Patient Data Sets Acquired under ‘No Change’ Conditions. Translational Oncology vol. 8 55–64 (2015).

    Article  Google Scholar 

  27. Bankier, A. A. et al. Recommendations for Measuring Pulmonary Nodules at CT: A Statement from the Fleischner Society. Radiology 285, 584–600 (2017).

    Article  Google Scholar 

  28. Anaizi, A., Hart, P. A. & Conwell, D. L. Diagnosing Chronic Pancreatitis. Dig. Dis. Sci. 62, 1713–1720 (2017).

    Article  CAS  Google Scholar 

Download references

Funding

This work did not receive any grant from funding agencies in the public, commercial, or not-for-profit sectors.

Author information

Authors and Affiliations

  1. Department of Radiology, Akershus University Hospital, 1478, Nordbyhagen, Norway

    Jens Borgbjerg & Anne Bethke

  2. Department of Radiology, Aalborg University Hospital, Hobrovej 18-22, PO. Box 365, 9000, Aalborg, Denmark

    Emily Steinkohl, Maria V. Lisitskaya, Gintare Naujokaite & Jens B. Frøkjær

  3. Department of Gastroenterology and Hepatology, Centre for Pancreatic Diseases, Aalborg University Hospital, Mølleparkvej 4, 9000, Aalborg, Denmark

    Emily Steinkohl, Søren S. Olesen, Maria V. Lisitskaya & Asbjørn M. Drewes

  4. Department of Clinical Medicine, Aalborg University, Søndre Skovvej 11, 9000, Aalborg, Denmark

    Emily Steinkohl, Søren S. Olesen, Asbjørn M. Drewes & Jens B. Frøkjær

  5. Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 550 N University Blvd, Ste 0663, Indianapolis, IN, 46202, USA

    Fatih Akisik & Jordan K. Swensson

  6. Department of Radiology, Lithuanian University of Health Sciences, Eivenių g. 2, 50161, Kaunas, Lithuania

    Edita Bieliuniene

  7. Department of Medicine, University of Bergen, Jonas Lies vei 65, 5021, Bergen, Norway

    Trond Engjom

  8. Department of Clinical Medicine, University of Bergen, Jonas Lies vei 87, 5021, Bergen, Norway

    Trond Engjom & Ingfrid S. Haldorsen

  9. Department of Radiology, Mohn Medical Imaging and Visualization Centre, Haukeland University Hospital, Ulriksdal 8, 5009, Bergen, Norway

    Ingfrid S. Haldorsen

  10. Division of Radiology, Department of Clinical Science, Intervention and Technology, Karolinska Institutet, O-huset 42, 14186, Stockholm, Sweden

    Nikolaos Kartalis

  11. Department of Radiology Huddinge, Karolinska University Hospital, O-huset 42, 14186, Stockholm, Sweden

    Nikolaos Kartalis

  12. Department of Gastroenterology and Gastrointestinal Surgery, Copenhagen University Hospital Hvidovre, Kettegård Allé 30, 2650, Hvidovre, Denmark

    Srdan Novovic

  13. Centre of Gastroenterology, Hepatology and Nutrition, Pauls Stradins Clinical University Hospital, Pilsoņu iela 13, Zemgales priekšpilsēta, Riga, 1002, Latvia

    Imanta Ozola-Zālīte

  14. Division of Gastroenterology, Hepatology, and Nutrition, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA

    Anna E. Phillips

  15. Department of Clinical Medicine, Faculty of Medicine, Aalborg University, Aalborg, Denmark

    Heidi S. Christensen

  16. Department of Haematology, Clinical Cancer Research Center, Aalborg University Hospital, Aalborg, Denmark

    Heidi S. Christensen

Authors
  1. Jens Borgbjerg
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  2. Emily Steinkohl
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  3. Søren S. Olesen
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  4. Fatih Akisik
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  5. Anne Bethke
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  7. Heidi S. Christensen
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  8. Trond Engjom
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  9. Ingfrid S. Haldorsen
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  10. Nikolaos Kartalis
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  11. Maria V. Lisitskaya
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  14. Imanta Ozola-Zālīte
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  15. Anna E. Phillips
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  16. Jordan K. Swensson
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  17. Asbjørn M. Drewes
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  18. Jens B. Frøkjær
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Contributions

All authors attest that they meet the current International Committee of Medical Journal Editors (ICMJE) criteria for Authorship and have made contributions to the paper as follows JB, ES, SSO, HSC, JBF: Conception and design of the study. JB, ES, SSO, FA, AB, EB, TE, ISH, NK, MVL, GN, SN, IO-Z, AEP, JKS, AMD, JBF: Acquisition of data. JB, ES, SSO, FA, AB, EB, HSC, TE, ISH, NK, MVL, GN, SN, IO-Z, AEP, JKS, AMD, JBF: Analysis and interpretation of data. JB, HSC, JBF: Drafting the article. JB, ES, SSO, FA, AB, EB, HSC, TE, ISH, NK, MVL, GN, SN, IO-Z, AEP, JKS, AMD, JBF: Revising the article. JB, ES, SSO, FA, AB, EB, HSC, TE, ISH, NK, MVL, GN, SN, IO-Z, AEP, JKS, AMD, JBF: Final approval.

Corresponding author

Correspondence to Jens B. Frøkjær.

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The authors declare that the work described has been carried out in accordance with the Declaration of Helsinki of the World Medical Association revised in 2013 for experiments involving humans. Informed consent and patient details The authors declare that this report does not contain any personal information that could lead to the identification of the patients.

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Borgbjerg, J., Steinkohl, E., Olesen, S.S. et al. Inter- and intra-observer variability of computed tomography-based parenchymal- and ductal diameters in chronic pancreatitis: a multi-observer international study. Abdom Radiol 48, 306–317 (2023). https://doi.org/10.1007/s00261-022-03667-2

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