Computerized tomography scan in pre-diagnostic pancreatic ductal adenocarcinoma: stages of progression and potential benefits of early intervention: a retrospective study
Open accessAbstract
Background The frequency, nature and timeline of changes on thin-slice (≤3 mm) multi-detector computerized tomography (CT) scans in the pre-diagnostic phase of pancreatic ductal adenocarcinoma (PDAC) are unknown. It is unclear if identifying imaging changes in this phase will improve PDAC survival beyond lead time.Methods From a cohort of 128 subjects (Cohort A) with CT scans done 3-36 months before diagnosis of PDAC we developed a CTgram defining CT Stages (CTS) I through IV in the radiological progression of pre-diagnostic PDAC. We constructed Cohort B of PDAC resected at CTS I and II and compared survival in CTS I and II in Cohort A (n = 22 each; control natural history cohort) vs Cohort B (n = 33 and 72, respectively; early interception cohort).Results CTs were abnormal in 16% and 85% at 24-36 and 3-6 months respectively, before PDAC diagnosis. The PDAC CTgram stages, findings and median lead times (months) to clinical diagnosis were: CTS I: Abrupt duct cut-off/duct dilatation (-12.8); CTS II: Low density mass confined to pancreas (-9.5), CTS III: Peri-pancreatic infiltration (-5.8), CTS IV: Distant metastases (only at diagnosis). PDAC survival was better in cohort B than in cohort A despite inclusion of lead time in Cohort A: CTS I (36 vs 17.2 months, p = 0.03), CTS II (35.2 vs 15.3 months, p = 0.04).Conclusion Starting 12-18 months before PDAC diagnosis, progressive and increasingly frequent changes occur on CT scans. Resection of PDAC at the time of pre-diagnostic CT changes is likely to provide survival benefit beyond lead time.
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Detecting PDAC earlier improves survival beyond the effect of lead time, since smaller tumors are more often resectable.
“Early detection offers survival benefit beyond lead time, as tumors are smaller in volume and more likely to be resectable when detected earlier.2-4”
From Radiomics-based Machine-learning Models Can Detect Pancreatic Cancer on Prediagnostic Computed Tomography Scans at a Substantial Lead Time Before Clinical Diagnosis (2022) · cites this paper as [2]
The Discussion reports that earlier-detected tumors were smaller and more likely to be resectable, and says the study suggests a survival benefit beyond lead time. The Abstract Conclusion calls that benefit likely, while the Introduction says a definitive answer requires a prospective randomized trial. The claim presents the survival benefit as established rather than suggested. (LLM, conf=0.85)
Experimental — accuracy not yet measuredSuch signs do not specifically indicate early PDAC, as control subjects can show them too.
“Second, these findings are not specific for early PDAC because they are also seen in control subjects.2,11”
From Radiomics-based Machine-learning Models Can Detect Pancreatic Cancer on Prediagnostic Computed Tomography Scans at a Substantial Lead Time Before Clinical Diagnosis (2022) · cites this paper as [2]
The Results section ('Parameters assessed on CT'; page not available) compares pre-diagnostic PDAC scans with matched controls and says the controls had 'negligible findings.' This allows for some findings in controls, but does not support the unqualified suggestion that these signs are generally nonspecific for early PDAC; they were much more frequent in cases. (LLM, conf=0.80)
Experimental — accuracy not yet measuredBefore clinical diagnosis, CTs in PDAC patients can show subtle indirect signs of cancer (3-36 months earlier).
“In patients with PDAC, subtle indirect findings suggestive of cancer (eg, pancreatic duct cutoff or dilatation, focal pancreatic atrophy) can be present on CTs at the prediagnostic stage (ie, 3–36 months before clinical diagnosis).2,7,8”
From Radiomics-based Machine-learning Models Can Detect Pancreatic Cancer on Prediagnostic Computed Tomography Scans at a Substantial Lead Time Before Clinical Diagnosis (2022) · cites this paper as [2]
The Introduction describes CT scans obtained 3–36 months before PDAC diagnosis, and the Results identify pancreatic duct cutoff or dilatation as a prediagnostic finding. The paper’s listed CT findings do not include focal pancreatic atrophy, so it does not support that example in the citing sentence. (LLM, conf=0.86)
Experimental — accuracy not yet measuredSingh et al reconstructed the timeline of progression of CT changes in prediagnostic PDAC: on average, CT changes started around 12 months before diagnosis, with pancreatic duct cutoff without a mass being the earliest sign; a mass appeared on average 9 months prior, with peripancreatic involvement at 6 months, vascular involvement at 3 months, and metastases only at diagnosis.
“In a recent study, Singh et al72 reconstructed the timeline of progression of computed tomography (CT) changes in prediagnostic PDAC. They showed that, on average, CT changes started around 12 months before diagnosis, with pancreatic duct cutoff without a mass being the earliest sign. A mass appeared, on average, 9 months prior, with peripancreatic involvement at 6 months, vascular involvement at”
From Artificial Intelligence and Early Detection of Pancreatic Cancer: 2020 Summative Review (2021) · cites this paper as [72]
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Experimental — accuracy not yet measuredThe sensitivity of CT scan findings suspicious for PDAC at −18 months was only 15%; even 6 months before diagnosis, it was only ~50%; at 3 months, it was 85%.
“The sensitivity of CT scan findings suspicious for PDAC at −18 months was only 15%. Even 6 months before diagnosis, it was only ~50%. At 3 months, it was 85%.”
From Artificial Intelligence and Early Detection of Pancreatic Cancer: 2020 Summative Review (2021) · cites this paper as [72]
The Results (‘Parameters assessed on CT’) report 45.7% in the 12–6-month window and 86.4% in the 6–3-month window, supporting the approximate 6- and 3-month figures. They do not support 15% at 18 months: the reported figures are 32% at 24–18 months and 44% at 18–12 months. The figure near 15% (16%) applies to 36–24 months before diagnosis. (LLM, conf=0.91)
Experimental — accuracy not yet measured
In this high-risk group, CT at diabetes onset could raise the share of PDACs that are resectable to three times the current rate.
“A computed tomography (CT) scan performed at the onset of new-onset diabetes in such a high-risk group has the potential to increase the proportion of resectable PDACs to 3 times higher than the current resectability rate.2”
PDAC may progress quickly from imaging-invisible disease to stage IV.
“This is a major challenge because the cancer can rapidly advance from being subclinical on imaging to stage IV.2,11”
Finding PDAC before cachexia worsens performance status raises the chance that eligible patients can undergo resection.
“Second, early detection before the decline in performance status from cancer-induced cachexia increases the prospect of surgical resection in eligible patients.2,5”
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Self-citationVeligotskіу, M. M., Arutyunov, S. E., Veligotskyі, O. M., & Kholod, Y. A. (2023) · Український радіологічний та онкологічний журнал · doi:10.46879/ukroj.4.2023.378-390 · Cited by 1 · see citing works
Role of artificial intelligence in early detection and screening for pancreatic adenocarcinoma
Lin, K. W., Ang, T. L., & Li, J. W. (2022) · Artificial Intelligence in Medical Imaging · doi:10.35711/aimi.v3.i2.21
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Alnoury, M., Mehdi, H. R., & Zaheer, A. (2024) · Seminars in Roentgenology · doi:10.1053/j.ro.2024.11.004
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TCIA full and low dose CT images and volumetric normal pancreas segmentations
Suman, G., Panda, A., Korfiatis, P. D., Garg, D. S., Polley, E., Singh, D., Chari, S., & Goenka, A. (2024) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.13362749
Self-citation
- Authors
- Singh, D. P., Sheedy, S., Goenka, A. H., Wells, M., Lee, N. J., Barlow, J., Sharma, A., Kandlakunta, H., Chandra, S., Garg, S. K., Majumder, S., Levy, M. J., Takahashi, N., & Chari, S. T.
- Affiliations
- Mayo Clinic (US)
- Staten Island University Hospital (US)
- The University of Texas MD Anderson Cancer Center (US)
- Corresponding author
- Chari, Suresh T.
- ORCID
- Venue
- Pancreatology
- Publisher
- Elsevier BV
- Published
- 2020-10
- Volume
- 20
- Issue
- 7
- Pages
- 1495-1501
- ISSN
- 1424-3903 (ISSN-L)
- PMC
- PMC13250856
- OpenAlex
- W3048409291
- Cited by
- 62
- References
- 15
- Citations by year
- 2026: 7 · 2025: 12 · 2024: 13 · 2023: 7 · 2022: 13 · 2021: 10
- FWCI
- 2.71
- Type
- journal article
- Language
- en
- Open access
- Locations
- Pancreatology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (publishedVersion)
- Funders
- National Institutes of Health U01 Consortium (U01DK108288)
- Mayo Clinic (U01DK108328)
- University of Texas MD Anderson Cancer Center
- Pancreatic Cancer Action Network
- Kenner Family Research Fund
- Prokopanko Gift to the Mayo Foundation
- Topics
- Health Sciences › Medicine › Oncology › Pancreatic and Hepatic Oncology Research
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › MRI in cancer diagnosis
- Health Sciences › Medicine › Surgery › Pancreatitis Pathology and Treatment
- Keywords
- pancreatic ductal adenocarcinoma, multidetector computed tomography, radiographic progression, lead time, survival, pancreatic duct dilatation, metastasis
- MeSH terms
- Aged, Aged, 80 and over, Female, Humans, Male, Middle Aged, Neoplasm Staging, Pancreatic Neoplasms, Predictive Value of Tests, Prognosis, Retrospective Studies, Tomography, X-Ray Computed, Cohort Studies, Survival Analysis, Disease Progression, Carcinoma, Pancreatic Ductal, Early Diagnosis, Multidetector Computed Tomography
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