Development of pancreatic cancer is predictable well in advance using contrast-enhanced CT: a case–cohort study

Gonoi, Wataru; Hayashi, Taiyu; Okuma, Hidemi; Akahane, Masaaki; Nakai, Yousuke; Mizuno, Suguru; Tateishi, Ryosuke; Isayama, Hiroyuki; Koike, Kazuhiko; Ohtomo, Kuni

doi:10.1007/s00330-017-4895-8

Cited by 39 publications

(41 citation statements)

References 35 publications

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“…This finding, if repeated in a larger sample, could argue in favor of pancreatic fat being a predisposing condition to cancer rather than a result of malignant transformation. This notion is supported by a recent study that reported on the inhomogeneous pancreas parenchyma as a predictive factor for pancreatic carcinogenesis, long before the diagnosis and independent of the tumor site [30].…”

Section: Discussionsupporting

confidence: 58%

“…While accurate assessment of fatty pancreas is only possible via histopathological examination of the tissue, the accumulating evidence suggests that imaging modalities can be used to accurately estimate pancreas fat [20,[28][29][30][31]. Among the available imaging modalities, ultrasound may not be able to adequately visualize the pancreas, with fibrosis and fat both appear as hyperechogenic signals [31,45].…”

Section: Discussionmentioning

confidence: 99%

“…CT does, however, have limitations including undefined cut-off points for pancreatic steatosis, exposure to radiation, and the inability to diagnose mild degrees of focal fatty replacement. Nevertheless, several studies have shown the ability of CT to clinically evaluate pancreatic fat [29][30][31].…”

Section: Discussionmentioning

confidence: 99%

“…Noninvasive imaging modalities can measure fat in tissues. In the past, imaging techniques were employed to estimate fatty pancreas based on computed tomography (CT) measurements of differences between pancreatic and splenic attenuation [11,[28][29][30]. Based on histopathological analysis, fatty pancreas was found to be associated with PDAC [28].…”

Section: Introductionmentioning

confidence: 99%

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Pancreatic Fat Infiltration Is Associated with a Higher Risk of Pancreatic Ductal Adenocarcinoma

et al. 2020

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Background: Pancreatic ductal adenocarcinoma (PDAC) has a poor survival rate, partly due to delayed diagnosis. Identifying high-risk individuals could lead to early detection and improve survival. A number of risk factors such as alcohol consumption and metabolic syndrome are associated with fatty infiltration of the pancreas. Experimental models show that a fatty pancreas promotes tissue inflammation and fibrosis, which could promote PDAC. Methods: We conducted a case-control study in a single-university tertiary hospital. Sixty-eight PDAC cases with recent non-contrast computed tomography (CT) and 235 controls were studied. The controls had no history of malignancy and underwent CT colonography for cancer screening in the same period. Pancreatic fat was estimated by calculating pancreatic (P) attenuation, corrected to splenic (S) attenuation, measured in three 1.0-cm² regions of the pancreas. The P.S100 value calculated was used to estimate fatty infiltration of the pancreas (FIP), with a lower P.S100 representing a higher FIP. Results: The PDAC patients had a lower BMI and a higher rate of type 2 diabetes mellitus. The P.S100 was lower in cases than in controls (86.452 vs. 92.414, p = 4.016e-06), suggesting that FIP is higher with PDAC. The risk of developing PDAC steadily increased significantly for the quartiles with a higher FIP compared to the low FIP quartile. No correlation between BMI and FIP (r = –0.1031179; 95% confidence interval [CI] –0.22267106 to 0.01949092) was found. Adjusting for confounders (age, sex, BMI, and DM), the risk of developing PDAC according to the FIP was estimated to be 3.75 (95% CI 1.9234408–7.993337; p = 0.000171). FIP was stable before and after the diagnosis of PDAC in 9 cases with prior CT scans when no pancreatic tumor was identifiable. Conclusion: Fatty pancreas is associated with an increased risk of pancreatic cancer. Once confirmed in larger-scale studies, these findings could help to identify at-risk individuals, particularly in high-risk groups such as chronic alcohol consumers

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Section: Discussionsupporting

confidence: 58%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Pancreatic Fat Infiltration Is Associated with a Higher Risk of Pancreatic Ductal Adenocarcinoma

et al. 2020

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“…It is now generally accepted that the detection of small PC ≤ 10 mm including CIS is indispensable to improve the prognosis of PC. However, there are no reports regarding the characteristic CT findings in patients with small PC (≤10 mm) [ 6 , 7 , 8 , 9 , 13 , 14 , 15 , 16 , 17 ]. In this study, we attempted to identify the specific CT findings of small PC by focusing on abnormalities in MPD and pancreatic parenchyma in patients with small PC including CIS.…”

Section: Introductionmentioning

confidence: 99%

Partial Pancreatic Parenchymal Atrophy Is a New Specific Finding to Diagnose Small Pancreatic Cancer (≤10 mm) Including Carcinoma in Situ: Comparison with Localized Benign Main Pancreatic Duct Stenosis Patients

et al. 2020

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Background: This study aimed to evaluate and identify the specific CT findings by focusing on abnormalities in the main pancreatic duct (MPD) and pancreatic parenchyma in patients with small pancreatic cancer (PC) including carcinoma in situ (CIS). Methods: Nine CT findings indicating abnormalities of MPD and pancreatic parenchyma were selected as candidate findings for the presence of small PC ≤ 10 mm. The proportions of patients positive for each finding were compared between small PC and benign MPD stenosis groups. Interobserver agreement between two independent image reviewers was evaluated using kappa statistics. Results: The final analysis included 24 patients with small PC (including 11 CIS patients) and 28 patients with benign MPD stenosis. The proportion of patients exhibiting partial pancreatic parenchymal atrophy (PPA) corresponding to the distribution of MPD stenosis (45.8% vs. 7.1%, p < 0.01), upstream PPA arising from the site of MPD stenosis (33.3% vs. 3.6%, p = 0.01), and MPD abrupt stenosis (45.8% vs. 14.3%, p = 0.03) was significantly higher in the small PC group than in the benign MPD stenosis group. Conclusions: The presence of partial PPA, upstream PPA, and MPD abrupt stenosis on a CT image was highly suggestive of the presence of small PCs including CIS.

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Two‐stage deep learning model for fully automated pancreas segmentation on computed tomography: Comparison with intra‐reader and inter‐reader reliability at full and reduced radiation dose on an external dataset

et al. 2021

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To develop a two-stage three-dimensional (3D) convolutional neural networks (CNNs) for fully automated volumetric segmentation of pancreas on computed tomography (CT) and to further evaluate its performance in the context of intra-reader and inter-reader reliability at full dose and reduced radiation dose CTs on a public dataset. Methods: A dataset of 1994 abdomen CT scans (portal venous phase, slice thickness ≤ 3.75-mm, multiple CT vendors) was curated by two radiologists (R1 and R2) to exclude cases with pancreatic pathology, suboptimal image quality, and image artifacts (n = 77). Remaining 1917 CTs were equally allocated between R1 and R2 for volumetric pancreas segmentation [ground truth (GT)]. This internal dataset was randomly divided into training (n = 1380), validation (n = 248), and test (n = 289) sets for the development of a two-stage 3D CNN model based on a modified U-net architecture for automated volumetric pancreas segmentation. Model's performance for pancreas segmentation and the differences in model-predicted pancreatic volumes vs GT volumes were compared on the test set. Subsequently, an external dataset from The Cancer Imaging Archive (TCIA) that had CT scans acquired at standard radiation dose and same scans reconstructed at a simulated 25% radiation dose was curated (n = 41). Volumetric pancreas segmentation was done on this TCIA dataset by R1 and R2 independently on the full dose and then at the reduced radiation dose CT images. Intra-reader and inter-reader reliability, model's segmentation performance, and reliability between model-predicted pancreatic volumes at full vs reduced dose were measured. Finally, model's performance was tested on the benchmarking National Institute of Health (NIH)-Pancreas CT (PCT) dataset. Results: Three-dimensional CNN had mean (SD) Dice similarity coefficient (DSC): 0.91 (0.03) and average Hausdorff distance of 0.15 (0.09) mm on the test set. Model's performance was equivalent between males and females (P = 0.08) and across different CT slice thicknesses (P > 0.05) based on noninferiority statistical testing. There was no difference in model-predicted and GT pancreatic volumes [mean predicted volume 99 cc (31cc); GT volume 101 cc (33 cc), P = 0.33]. Mean pancreatic volume difference was À2.7 cc (percent difference: À2.4% of GT volume) with excellent correlation between model-predicted and GT volumes [concordance correlation coefficient (CCC)=0.97]. In the external TCIA dataset, the model had higher reliability than R1 and R2 on full vs reduced dose CT scans [model mean (SD) DSC: 0.96 (0.02), CCC = 0.995 vs R1 DSC: 0.83 (0.07), CCC = 0.89, and R2 DSC:0.87 (0.04), CCC = 0.97]. The DSC and volume concordance correlations for R1 vs R2 (inter-reader reliability) were 0.85 (0.07), CCC = 0.90 at full dose and 0.83 (0.07), CCC = 0.96 at reduced dose datasets. There was good reliability between model and R1 at both full and reduced dose CT [full dose: DSC: 0.81 (0.07), CCC = 0.83 and reduced dose DSC:0.81 (0.08), CCC = 0.87]. Likewise, there was good reliability betw...

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Development of pancreatic cancer is predictable well in advance using contrast-enhanced CT: a case–cohort study

Cited by 39 publications

References 35 publications

Pancreatic Fat Infiltration Is Associated with a Higher Risk of Pancreatic Ductal Adenocarcinoma

Pancreatic Fat Infiltration Is Associated with a Higher Risk of Pancreatic Ductal Adenocarcinoma

Partial Pancreatic Parenchymal Atrophy Is a New Specific Finding to Diagnose Small Pancreatic Cancer (≤10 mm) Including Carcinoma in Situ: Comparison with Localized Benign Main Pancreatic Duct Stenosis Patients

Two‐stage deep learning model for fully automated pancreas segmentation on computed tomography: Comparison with intra‐reader and inter‐reader reliability at full and reduced radiation dose on an external dataset

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