Assessment of Pancreatic Physiological and Pathological Characteristics Based on Spectral CT
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: The post-processing generated after scanning is converted into energy spectrum image data (SBI).
- Who it may be relevant to
- Registry conditions: Diagnose Disease. Basic parameters: 18 years — 80 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- China
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
Assessment of Pancreatic Physiological and Pathological Characteristics Based on Spectral CT Feature Parameters: A Related Study
Overview
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.
Interventions
- Other The post-processing generated after scanning is converted into energy spectrum image data (SBI)
It will not open special sequences for patients, will not increase the cost of diagnosis and treatment, will not increase radiation exposure during enhanced CT scanning, and will not affect the normal diagnosis and treatment process of patients throughout the process.
Primary outcome measures
- spectral imaging data(SBI) [Time frame: 21/3/2025]
- ROI area（mm2） [Time frame: 21/3/2025]
Secondary outcome measures (1)
- single-energy CT value [Time frame: 21/3/2025]
Eligibility criteria
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
- Previous pancreatic surgery with incomplete pancreatic tissue.
- Severe systemic diseases that result in severe organ dysfunction
- Excessive pancreatic atrophy or other reasons cannot accurately delineate ROI
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: Yes
Study design
- Observational model
- Case-control
Study locations
China · 1 center
- Shengjing Hospital of China Medical University — Shenyang
Identifiers
NCT: NCT06510036 · ShengjingH-shen