Maybe this answer is not suitable for you?
In my doctoral thesis from 1995 I compared even moderate quality pre-operative ultrasonographic images to cuts through surgical specimens of kidneys with a treated Wilms tumour. Very good results, proving that an experienced ultrasonographer can provide excellent reliable anatomic information to the surgeon! The same is true in abdominal neuroblastoma.
Many years ago I performed a study on the CT-visibility of artificial thin lamellae of variable thicknes by means of ROC-curves (A receiver operating characteristic curve, or ROC curve, is a graphical plot that illustrates the diagnostic ability of a binary classifier system as its discrimination threshold is varied).
Is this method possibly of help to you?
I am NOT a doctor. With the help of AI, this info is collected. Hope it helps you.
Yes, there are several scales, checklists, and other methods available to assess the quality and transparency of research that utilizes patient data, including imaging data. These tools aim to evaluate various aspects of research methodology, data reporting, and transparency. Here are a few examples:
1. STARD (Standards for Reporting Diagnostic Accuracy Studies): STARD is a checklist designed to assess the reporting quality of diagnostic accuracy studies. While it is not specific to patient data or imaging, it can be applicable to studies that use imaging data for diagnostic purposes.
2. QUADAS (Quality Assessment of Diagnostic Accuracy Studies): QUADAS is a tool specifically developed to assess the quality of diagnostic accuracy studies. It focuses on the methodological aspects of the study design, patient selection, index test, reference standard, and flow of participants.
3. CONSORT (Consolidated Standards of Reporting Trials): CONSORT is a widely used guideline for reporting randomized controlled trials (RCTs). While not specific to patient data or imaging, it provides a comprehensive checklist for assessing the transparency and quality of trial reporting.
4. TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis): TRIPOD is a guideline specifically designed for reporting prediction model studies. It provides a checklist for assessing the transparency, quality, and risk of bias in studies that develop or validate prediction models using patient data.
5. QIBA (Quantitative Imaging Biomarkers Alliance): QIBA, an initiative by the Radiological Society of North America (RSNA), aims to improve the reliability of quantitative imaging biomarkers. While not strictly a checklist, QIBA provides a framework and guidelines for assessing and improving the quality and standardization of quantitative imaging.
- Badges
- Science topic
- Similar topics
- Mathematics
- Statistics
- Statistical Software
- R