Assessment of Pancreatic Physiological and Pathological Characteristics Based on Spectral CT

Recruiting

• Conditions: Diagnose Disease
• Interventions: Other: The post-processing generated after scanning is converted into energy spectrum image data (SBI)

• Registration Number: NCT06510036
• Lead Sponsor: Yu Shi

Brief Summary

Patients who visited our hospital for various reasons from January 2024, underwent CT scans involving the pancreas, and were eligible for spectral post-processing reconstruction were included in the study. This research collected spectral CT data related to the pancreas at different phases, as well as physiological and pathological states for these patients. Quantitative analysis was conducted on post-processed data under different physiological and pathological states, including parameters such as pancreatic iodine uptake features, attenuation interval slopes, and extracellular volume size. In conjunction with general patient status, biochemical tests, and postoperative pathological results, the study aimed to identify correlations between parameters, develop models, and conduct research by comparing traditional CT data, which could be matched with spectral CT from the PACS database since its establishment.

Detailed Description

Dual-Energy CT (DECT) is a widely recognized technology, especially in its applications for the abdominal and pelvic regions. Pancreatology is an ideal application of the many advantages offered by dual-energy post-processing. DECT can characterize specific tissues or materials/elements, generate virtual unenhanced and monochromatic images, and quantify iodine uptake; these unique capabilities make DECT a perfect technology for supporting tumor detection and characterization as well as treatment monitoring, while also reducing radiation and iodine doses and improving metal artifacts. The pancreas' special endocrine function makes pancreatic tissue highly sensitive to individual variations. Researchers have studied the accumulation of pancreatic fat in patients with obesity and metabolic syndrome, suggesting that obesity, increased age, male gender, hypertension, dyslipidemia, alcohol, and hyperferritinemia can cause ectopic fat accumulation in the pancreas, described analogously to "fatty liver" as "fatty pancreas." Age is also an important factor leading to exocrine dysfunction of the pancreas. Studies on the pancreatic features of patients with type II diabetes have indicated that this condition can severely affect pancreatic atrophy/ irregular morphology and fat deposition. Overall, precise characterization of pancreatic tissue is a crucial part of evaluating diagnoses related to pancreatic diseases. Compared to traditional CT, spectral CT provides ample data that can better assist in diagnosing pancreatic diseases.

However, it corresponds that the pancreas itself is very sensitive to certain non-pancreatic primary diseases, even some special abnormal physiological states (such as obesity). When investigators evaluate the special changes of primary pancreatic diseases, it's challenging to exclude the impacts of these factors completely. For some data abnormalities, it's sometimes unclear whether they are caused solely by primary diseases, or not only by primary diseases, nor is it certain whether the effects of primary diseases and these other states on the data are synergistic or antagonistic. Therefore, collecting and researching pancreatic-related spectral data from patients with non-pancreatic primary diseases coming for consultation is a premise for us to use spectral CT feature parameters to assess the relationship between pancreatic physiological and pathological characteristics.

Study Timeline

• Study Start: 2021-01-21
• Study First Submitted: 2024-06-12
• Study First Submitted QC: 2024-07-18
• Study First Posted: 2024-07-19
• Status Verified: 2024-12
• Last Update Submitted: 2024-12-02
• Last Update Posted: 2024-12-04
• Primary Completion: 2027-06-21
• Study Completion: 2028-06-21

Recruitment & Eligibility

• Status: RECRUITING
• Sex: All
• Target Recruitment: 1500

Inclusion Criteria

1.Since March 2024, I have been visiting our hospital for various reasons and have undergone CT scans involving the pancreas (using energy spectrum CT)

Exclusion Criteria

1. Previous pancreatic surgery with incomplete pancreatic tissue.
2. Severe systemic diseases that result in severe organ dysfunction
3. Excessive pancreatic atrophy or other reasons cannot accurately delineate ROI

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Arm && Interventions

Group	Intervention	Description
test group	The post-processing generated after scanning is converted into energy spectrum image data (SBI)	Post processing patient data using energy spectrum CT
control group	The post-processing generated after scanning is converted into energy spectrum image data (SBI)	Collect traditional CT data that can correspond to spectral CT since the establishment of PACS database to form a comparison

Primary Outcome Measures

Name	Time	Method
ROI area（mm2）	21/3/2025	Using Philips Intellispace Portal software to delineate the Region of Interest (ROI)
spectral imaging data(SBI)	21/3/2025	Using Philips Intellispace Portal software to reconstruct spectral imaging data images

Secondary Outcome Measures

Name	Time	Method
single-energy CT value	21/3/2025	Measure the single-energy CT value(Hu)

Trial Locations

Locations (1)

Shengjing Hospital of China Medical University; 🇨🇳 Shenyang, Liaoning, China