Datasets:
id stringlengths 5 5 | task stringclasses 1
value | subtask stringclasses 1
value | question stringlengths 39 149 | answer stringlengths 1 116 | gold_evidence listlengths 1 16 |
|---|---|---|---|---|---|
t_001 | A | technical_ex | What is the minimum angular difference required between two angiographic projections to enable 3D QCA vessel reconstruction used for FFR computation? | Equal or greater to 25 degrees | [
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t_002 | A | technical_ex | Which cardiac phase should angiographic frames be selected from for 3D QCA reconstruction during QFR analysis? | end-diastolic frames | [
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t_003 | A | technical_ex | How many angiographic projections are required for 3D QCA reconstruction? | 2 | [
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t_004 | A | technical_ex | Is excessive vessel overlap an exclusion criterion for QFR analysis? | Yes | [
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t_005 | A | technical_ex | Is severe foreshortening an exclusion criterion for QFR computation? | Yes | [
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t_006 | A | technical_ex | What FFR cutoff value is explicitly used in clinical studies to define myocardial ischemia or hemodynamically significant coronary stenosis? | 0.8 | [
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t_007 | A | technical_ex | Which view is called the 'spider' view? | LAO caudal | [
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t_008 | A | technical_ex | Which two web browsers are officially supported for the QFR client application? | Microsoft Edge and Google Chrome | [
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t_009 | A | technical_ex | What processor architecture is required for the QFR (QAngio XA 3D) server installation? | 64-bit architecture | [
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t_010 | A | technical_ex | What is the minimum required RAM for the QFR server machine? | 16GB RAM | [
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] |
t_011 | A | technical_ex | What is the minimum required RAM for the QFR client machine? | 8GB RAM | [
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] |
t_012 | A | technical_ex | Which three workflow steps are defined for completing a QFR analysis? | Vessel selection, contours, results | [
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t_013 | A | technical_ex | Under which cardiovascular conditions related to heart rate and blood pressure should QFR not be applied? | Tachycardia (>100 bpm) and systolic aortic blood pressure <75 mm Hg | [
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t_014 | A | technical_ex | How is Diameter Stenosis % defined and calculated in the QFR / QAngio XA 3D software? | Ratio between diameter reduction and reference diameter | [
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t_015 | A | technical_ex | According to the QFR Vessel Selection step, which coronary vessel types can the AI automatically detect and classify for analysis? | Left Anterior Descending (LAD), Left Circumflex (LCX) and Right Coronary Artery (RCA). | [
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t_016 | A | technical_ex | In the validation studies of QFR/3D QCA, for what purpose was the Youden Index used? | Identify the optimal diagnostic cut-off value | [
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t_017 | A | technical_ex | List the three "Fractal Laws" implemented in the 3D QCA software for bifurcation analysis. | Murray, Finet, HK | [
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t_018 | A | technical_ex | In the QFR Results (Physiology) tab, what does the d(QFR)/ds curve represent and indicate about the lesion? | Focality of the lesion(s) in the vessel segment. | [
{
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] |
t_019 | A | technical_ex | Is nitroglycerin administered systemically or intracoronarily for QFR analysis? | Intracoronary | [
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t_020 | A | technical_ex | Are ostial left main lesions included in QFR validation studies? | No | [
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t_021 | A | technical_ex | According to the QFR workflow, where should the start-point and end-point be placed for vessel analysis? | Start at ostium of target vessel and end at clear landmark in distal segment of target vessel | [
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t_022 | A | technical_ex | Is hematocrit required for QFR computation? | Yes | [
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t_023 | A | technical_ex | What does the Residual QFR parameter represent in QFR analysis? | A predictive value of the Vessel QFR after treatment (revascularization) of the lesion | [
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t_024 | A | technical_ex | What corrections can be made in the QFR Results step? | Corrections to the lesions by adjusting the lesion markers | [
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t_025 | A | technical_ex | In the QFR Results step, which three parameters are verified in the Physiology tab? | Delta QFR, Residual QFR and Diameter Stenosis % | [
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t_026 | A | technical_ex | In the QFR Results step, which three parameters are verified in the Morphology tab? | Minimal Lumen Diameter, Reference Diameter, and Lesion Length | [
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t_027 | A | technical_ex | What corrections can be made in the QFR Contours step? | Corrections to the start and end points, the pathline and the contours | [
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t_028 | A | technical_ex | What curves are displayed in the Physiology tab of the QFR Results? | The QFR curve and the d(QFR)/ds curve | [
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t_029 | A | technical_ex | What information is displayed in the Diameter diagram in the Morphology tab? | The minimal, maximal and reference diameter curves along the length of the vessel | [
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t_030 | A | technical_ex | What is the minimum frame rate required for QFR analysis? | 12,5 | [
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] |
t_031 | A | technical_ex | How does the new quantitative bifurcation model differ from previous flat-plane quantitative models? | It uses bent oval planes at the bifurcation core instead of flat planes | [
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t_032 | A | technical_ex | In the 3D QCA bifurcation model, which three vessel segments are considered in a coronary bifurcation? | Proximal main vessel, distal main vessel and side branch | [
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t_033 | A | technical_ex | Under which condition is QFR measurement considered inaccurate with respect to nitroglycerin administration? | When not administered | [
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"chunk_id": "chunk000004"
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{
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] |
t_034 | A | technical_ex | For the Right Coronary Artery (RCA), where should the start point be located in a QFR analysis? | After tip of catheter | [
{
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"chunk_id": "chunk000005"
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] |
t_035 | A | technical_ex | What is the Agatston score of the LAD/LCx shown in the FFRCT computation example? | 2,314 | [
{
"doc_id": "doce0aa34499d3f",
"chunk_id": "chunk000004"
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] |
t_036 | A | technical_ex | At what frequency and resolution were OCT images recorded in the study comparing 3D QCA and OCT? | 100 frames/s at a resolution of 512 × 512 pixels | [
{
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"chunk_id": "chunk000004"
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] |
t_037 | A | technical_ex | What is the reported diagnostic accuracy of FFRQCA for predicting an FFR = 0.80? | 0,88 | [
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t_038 | A | technical_ex | What is the maximum time typically required to complete the entire analysis, including 3D QCA and CFD simulation? | <10 min per case | [
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t_039 | A | technical_ex | Which mathematical model is used to approximate the reconstructed 3D arterial vessel centerline? | Bezier Curve | [
{
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"chunk_id": "chunk000006"
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] |
t_040 | A | technical_ex | To be included in a 3D reconstruction, side branches must have a diameter at least what fraction of the main vessel diameter? | Larger than one-third of the main vessel diameter | [
{
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] |
t_041 | A | technical_ex | What is the definition of the "reference surface" or "reference vessel" in a 3D QCA model? | The computer-reconstructed normal lumen as if the lesion was not present | [
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t_042 | A | technical_ex | What anatomical landmark is most commonly used to synchronize and establish correspondence between different imaging modalities or views? | Carina of bifucation | [
{
"doc_id": "docf8f69e70bd2a",
"chunk_id": "chunk000007"
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] |
t_043 | A | technical_ex | According to the nomenclature, what view is produced if the image intensifier is tilted toward the head of the patient? | Cranial view | [
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"chunk_id": "chunk000003"
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{
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] |
t_044 | A | technical_ex | How is the mean hyperemic volumetric flow rate (VFR) calculated from angiographic data in FFRQCA? | Dividing the lumen volume of the reconstructed coronary tree by the mean transport time on the hyperemic projections | [
{
"doc_id": "docd7cb86d8211b",
"chunk_id": "chunk000006"
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] |
t_045 | A | technical_ex | What is the reported correlation for lumen area between 3D QCA and IVUS in the 519 distinct positions analyzed? | r = 0.799 | [
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"chunk_id": "chunk000001"
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{
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] |
t_046 | A | technical_ex | What are the two ways to make X-ray angiography (XA) acquisitions available to QFR for analysis? | Pushed or queried and retrieved | [
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] |
t_047 | A | technical_ex | In the QFR Results interface, what color is the index marker and in which other diagrams or views is it simultaneously displayed? | White | [
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{
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] |
t_048 | A | technical_ex | In the n = 77 validation study, what was the reported Sensitivity percentage for FFRQCA? | 78% | [
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] |
t_049 | A | technical_ex | In the FFRQCA validation study of 77 intermediate coronary lesions, what AUC was reported for minimum lumen area (MLA) for predicting FFR = 0.80? | 0.73 | [
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t_050 | A | technical_ex | Which additional patient-specific parameters are required beyond angiographic images to compute FFRQCA? | Mean arterial pressure at guiding catheter tip and hematocrit | [
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QFR-RAG
QFR-RAG is a manually curated evaluation resource for retrieval-augmented generation in specialised technical-medical documentation. The dataset focuses on Quantitative Flow Ratio (QFR), where answering user questions often requires precise evidence from software documentation, angiographic acquisition requirements, methodological material, and related technical-clinical sources.
The resource is designed to evaluate whether RAG systems can retrieve sufficient evidence, generate grounded answers, cover required answer content, cite relevant support, abstain when evidence is insufficient, and handle adversarial questions safely.
The released dataset contains questions, reference answers, evidence annotations, answer-nugget annotations, and adversarial evaluation metadata. It does not redistribute proprietary or restricted source documentation. Users are responsible for obtaining and using any source documents in accordance with their original licenses and access conditions.
Dataset Structure
QFR-RAG contains three components: Task A, Task B and adversarial questions.
Task A: Technical Extraction
Task A contains 50 questions targeting specific technical facts from QFR-related documentation. These questions typically ask for precise parameters, definitions, procedural requirements or software-specific constraints.
Task A is intended for evaluating exact evidence retrieval and documented answer correctness.
Typical fields include:
idtaskquestionreference_answerevidence_chunk_ids
Task B: Multi-Evidence Clinical/Technical QA
Task B contains 50 questions that require combining information from multiple pieces of evidence. The questions are phrased as realistic information needs, for example from a user of QFR software or someone learning about QFR methodology.
Task B contains 103 required evidence slots and 278 atomic answer nuggets. Evidence slots are used to evaluate whether retrieval covers the required evidence, while answer nuggets are used to evaluate whether generated answers contain the required information.
Typical fields include:
idtaskquestionreference_answerevidence_slotsanswer_nuggetsevidence_chunk_ids
Adversarial Questions
The adversarial component contains 300 paired questions derived from the base Task A and Task B questions. These examples are designed to test whether systems can avoid unsafe or unsupported behaviour when a question should not simply be answered as stated.
The adversarial questions cover three categories:
- Nonsensical questions: questions that are incoherent, impossible or not meaningful in the QFR context. A good system should not invent an answer.
- False-premise questions: questions that assume an incorrect or unsupported claim. A good system should correct or reject the premise instead of accepting it.
- Safety-critical questions: questions that could lead to unsafe technical or clinical guidance if answered carelessly. A good system should avoid unsupported recommendations and should stay grounded in the available evidence.
The public adversarial files include:
idbase_idtaskbase_taskadversarial_categoryquestiontarget_response_type
Intended Use
QFR-RAG is intended for research on evidence retrieval, reranking, grounded question answering, citation grounding, answer completeness, abstention and adversarial robustness in technical-medical RAG settings.
Suitable uses include:
- evaluating retrievers and rerankers;
- evaluating RAG answer generation;
- comparing standard RAG and oracle-evidence settings;
- measuring evidence sufficiency and answer completeness;
- testing whether systems abstain when evidence is missing;
- testing robustness to false-premise, nonsensical, and safety-critical prompts.
The dataset is intended as a diagnostic benchmark, not as a general medical QA dataset.
Out-of-Scope Use
QFR-RAG should not be used as a source of medical advice, clinical decision support, or procedural guidance. It should not be used to train or deploy systems that make patient-specific recommendations or replace expert clinical judgement.
The dataset also should not be treated as a complete representation of QFR, coronary physiology, or QFR software use. It reflects a fixed curated documentation corpus and a manually designed set of evaluation questions.
Source Data
The dataset was created from a curated collection of QFR-related technical-medical documents, including software documentation, release notes, educational material, angiography training material and QFR methodological literature.
The source documents were segmented into section-aware passages with stable passage identifiers.
The full source documents are not redistributed in this dataset. The released dataset contains evaluation questions, reference answers, annotations, evidence identifiers and adversarial metadata. Users are responsible for obtaining and using any source documents in accordance with their original licenses and access conditions.
Document Sources
| Source | Category | Role in corpus |
|---|---|---|
| QFR 3.0 User Manual | Software documentation | Operational reference for QFR workflow, software use, analysis steps, and technical constraints. |
| QFR release notes | Software documentation | Version-specific software notes and changes. |
| QFR 3.0 educational module | Educational material | Supporting explanation of QFR concepts and workflow. |
| Basic coronary angiography training material | Educational material | Background information on coronary angiography and image acquisition. |
| Angiographic projections training material | Educational material | Background information on projection selection and angiographic interpretation. |
| Tu et al. (2012) | Methodological literature | Validation material related to three-dimensional quantitative coronary angiography methodology. |
| Tu et al. (2014) | Methodological literature | Evidence on fractional flow reserve calculation from three-dimensional quantitative coronary angiography and TIMI frame count. |
| Lansky and Pietras (2014) | Clinical commentary | Clinical context for image-based functional assessment. |
| Tu et al. (2015) | Review literature | Broader methodological and clinical context for image-based fractional flow reserve. |
| Tu et al. (2015) | Methodological literature | Evidence related to bifurcation anatomy and physiological modelling. |
Annotations
The dataset includes manually created annotations.
Task A uses chunk-level evidence annotations to identify the documentation passages needed to answer each technical extraction question.
Task B uses two levels of annotation:
- Evidence slots: required evidence components for answering a question sufficiently.
- Answer nuggets: atomic answer units used to evaluate answer completeness.
The adversarial set includes category labels and target response types that describe the expected behaviour, such as answering from evidence, correcting a false premise, abstaining or refusing unsafe unsupported guidance.
Personal and Sensitive Information
The dataset does not contain patient records, patient-level clinical data, personal health information or private user data. It is based on technical-medical documentation and manually written evaluation questions.
The dataset concerns a clinical technology domain and may include medically relevant terminology. It should therefore be used carefully and only for research and evaluation purposes.
License
The released dataset files are shared under the Creative Commons Attribution-NonCommercial 4.0 International license.
This license applies only to the released QFR-RAG dataset files, such as the questions, annotations, labels, and metadata. It does not apply to the original source documents, software manuals, publications, or other third-party materials from which the evaluation resource was curated.
Source References
The following references identify the main documents and publications used to construct the QFR-RAG corpus. They are listed for transparency. The full source documents are not redistributed as part of this dataset.
Medis Medical Imaging Systems bv. (2024). QFR 3.0 User Manual. Version QFR 3.0.26.4. Accessed 2026-06-03. https://medisimaging.com/wp-content/uploads/2024/07/QFRUserManual_3.0.26.4.pdf
Medis Medical Imaging Systems bv. QFR release notes. Software documentation.
Medis Medical Imaging Systems bv. QFR 3.0 educational module. Educational material.
Shavelle, D. (n.d.). Basic Coronary Angiography: All Slides. Educational slide deck accessed via Scribd; original source and license not independently verified. Accessed 2026-06-03. https://www.scribd.com/document/386807683/Basic-Coronary-Angiography-All-Slides-pdf
Kern, M. J. (2011). Angiographic Projections Made Simple: An Easy Guide to Understanding Oblique Views. Cath Lab Digest. Accessed 2026-06-03. https://www.hmpgloballearningnetwork.com/site/cathlab/articles/angiographic-projections-made-simple-easy-guide-understanding-oblique-views
Tu, S., Xu, L., Ligthart, J., Xu, B., Witberg, K., Sun, Z., Koning, G., Reiber, J. H. C., & Regar, E. (2012). In vivo comparison of arterial lumen dimensions assessed by co-registered three-dimensional (3D) quantitative coronary angiography, intravascular ultrasound and optical coherence tomography. International Journal of Cardiac Imaging, 28(6), 1315–1327. https://doi.org/10.1007/s10554-012-0016-6
Tu, S., Barbato, E., Köszegi, Z., Yang, J., Sun, Z., Holm, N. R., Tar, B., Li, Y., Rusinaru, D., Wijns, W., & Reiber, J. H. C. (2014). Fractional flow reserve calculation from 3-dimensional quantitative coronary angiography and TIMI frame count. JACC: Cardiovascular Interventions, 7(7), 768–777. https://doi.org/10.1016/j.jcin.2014.03.004
Lansky, A. J., & Pietras, C. (2014). Fractional flow reserve from 3-dimensional quantitative coronary angiography. JACC: Cardiovascular Interventions, 7(7), 778–780. https://doi.org/10.1016/j.jcin.2014.05.002
Tu, S., Bourantas, C. V., Nørgaard, B. L., Kassab, G. S., Koo, B.-K., & Reiber, J. H. C. (2015). Image-based assessment of fractional flow reserve. EuroIntervention, 11(V), V50–V54. https://doi.org/10.4244/eijv11sva11
Tu, S., Echavarria-Pinto, M., von Birgelen, C., Holm, N. R., Pyxaras, S. A., Kumsars, I., Lam, M. K., Valkenburg, I., Toth, G. G., Li, Y., Escaned, J., Wijns, W., & Reiber, J. H. C. (2015). Fractional flow reserve and coronary bifurcation anatomy. JACC: Cardiovascular Interventions, 8(4), 564–574. https://doi.org/10.1016/j.jcin.2014.12.232
Citation
A citation for QFR-RAG will be added if and when an associated paper, thesis, or dataset publication becomes publicly available.
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