| --- |
| license: other |
| license_name: raidium-metriceval-dua-1.0 |
| license_link: LICENSE |
| gated: true |
| language: |
| - en |
| task_categories: |
| - text-ranking |
| - summarization |
| annotations_creators: |
| - expert-generated |
| size_categories: |
| - n<1K |
| tags: |
| - radiology |
| - medical |
| - clinical |
| - ct |
| - computed-tomography |
| - report-generation |
| - evaluation |
| - nlg-evaluation |
| - meta-evaluation |
| - llm-as-a-judge |
| - human-feedback |
| - preference-ranking |
| - inter-annotator-agreement |
| - benchmark |
| - expert-annotation |
| pretty_name: MetricEval-BodyCT |
| configs: |
| - config_name: studies |
| data_files: |
| - split: test |
| path: data/studies.parquet |
| default: true |
| - config_name: annotations |
| data_files: |
| - split: test |
| path: data/annotations.parquet |
| extra_gated_heading: Access requires agreeing to the Data Use Agreement |
| extra_gated_description: Requests are reviewed manually; please allow a few business days. |
| extra_gated_prompt: | |
| This dataset has two files under different terms — see the LICENSE file for the operative text. |
| |
| - `annotations.parquet` (the radiologist labels) is licensed **CC-BY-4.0**. |
| - `studies.parquet` contains de-identified radiology **report text** derived from Segmed's |
| de-identified data pilot. It is **restricted**. By requesting access you agree that you will: |
| 1. use it solely for non-commercial research on radiology report generation and its evaluation; |
| 2. make no attempt to re-identify any individual, provider, institution, or site; |
| 3. not redistribute the report text, or any derivative containing it, in whole or in part; |
| 4. not use it to train or fine-tune models for clinical deployment without a separate agreement; |
| 5. cite this dataset in any resulting publication. |
|
|
| Access is personal and non-transferable, and may be revoked at any time. The data is provided |
| "as is", with no warranty. It is not a medical device and must not be used to inform patient care. |
| extra_gated_fields: |
| Full name: text |
| Institution / affiliation: text |
| Country: country |
| Intended research use: text |
| I will not attempt re-identification: checkbox |
| I will not redistribute the report text: checkbox |
| I agree to the Data Use Agreement: checkbox |
| extra_gated_button_content: Request access |
| --- |
| |
| # MetricEval-BodyCT |
|
|
| This repository is a **body CT benchmark for evaluating radiology report-generation metrics** against |
| radiologists' judgment. |
|
|
| It covers 100 CT studies (50 chest and 50 abdomen/pelvis), with three candidate reports each. Every |
| candidate was independently annotated by multiple board-certified radiologists. The reference reports |
| are de-identified radiology reports from multiple US centers, provided by Segmed and redistributed |
| under the Data Use Agreement in `LICENSE`. The candidate reports are synthetic perturbations of those |
| references: deliberately injected errors, false clinical statements, hallucinations, etc. |
|
|
|
|
| ## 1. Evaluation protocol |
|
|
| Write your metric's scores to a CSV (300 rows, one per candidate), where **higher must mean better**. Then run: |
| ```bash |
| python3 eval.py --scores your_metric_scores.csv --out results_your_metric.json --label YourMetric |
| ``` |
|
|
| An example input file, `example_scores.csv`, is included in this repository: |
|
|
| ```csv |
| study_id,candidate_label,score |
| abdomen_0108ee4fedcc,a,0.617761 |
| abdomen_0108ee4fedcc,b,0.717391 |
| abdomen_0108ee4fedcc,c,0.745223 |
| ... |
| ``` |
|
|
| An example of output |
| ``` |
| endpoint tau_b 95% CI blocks |
| -------------------------- -------- ------------------ ------- |
| n_errors -0.361 [-0.432, -0.291] 97 |
| n_significant -0.213 [-0.288, -0.142] 72 |
| rank_accuracy -0.310 [-0.371, -0.252] 99 |
| rank_answers_indication -0.209 [-0.275, -0.145] 94 |
| cat_hallucinated -0.212 [-0.281, -0.142] 97 |
| cat_missed -0.172 [-0.308, -0.038] 33 |
| cat_other -0.075 [-0.387, +0.245] 6 |
| cat_wrong_certainty -0.051 [-0.148, +0.050] 40 |
| cat_wrong_characterization -0.270 [-0.453, -0.095] 13 |
| cat_wrong_comparison -0.312 [-0.540, +0.069] 8 |
| cat_wrong_location -0.369 [-0.494, -0.231] 20 |
| cat_wrong_measurement -0.235 [-0.401, -0.054] 18 |
| cat_wrong_severity -0.317 [-0.435, -0.197] 29 |
| ``` |
|
|
| Results are also persisted as a JSON file. |
|
|
| Each endpoint is a different entry point into the radiologists' judgment: |
| | endpoint | what it is | inter-rater ceiling (95% CI) | |
| |---|---|---| |
| | `n_errors` | **primary** — their total error count | **-0.694** [-0.751, -0.634] | |
| | `n_significant` | their count of clinically significant errors | **-0.471** [-0.564, -0.383] | |
| | `rank_accuracy` | their ranking of the whole report's fidelity to the reference | **-0.645** [-0.746, -0.538] | |
| | `rank_answers_indication` | their ranking of how well the *impression* answers the clinical indication | **-0.701** [-0.774, -0.618] | |
| | `cat_hallucinated` | findings asserted by the candidate that the reference does not support | **-0.821** [-0.867, -0.773] | |
| | `cat_missed` | findings present in the reference and absent from the candidate | **-0.690** [-0.820, -0.532] | |
| | `cat_wrong_location` | a real finding placed at the wrong anatomic site | **-0.890** [-0.982, -0.786] | |
| | `cat_wrong_severity` | a real finding graded more or less severe than the reference | **-0.879** [-0.975, -0.765] | |
| | `cat_wrong_characterization` | a real finding described with the wrong morphology | **-0.922** [-1.000, -0.769] | |
| | `cat_wrong_measurement` | a size, count or distance that disagrees with the reference | **-0.874** [-0.978, -0.700] | |
| | `cat_wrong_certainty` | hedging that over- or under-states how definite the reference is | **-0.658** [-0.792, -0.517] | |
| | `cat_wrong_comparison` | a change from a prior study invented, dropped or reversed | **-1.000** [-1.000, -1.000] | |
| | `cat_other` | an error the rater logged outside the categories above | *too few blocks* | |
|
|
| ## 2. Error records |
|
|
| Each rater, for each candidate, logged every error they found and then ranked the three candidates. |
| `annotations.errors` is a nested column holding the individual errors; an empty list means the rater |
| reviewed that candidate and confirmed it error-free. |
|
|
| | field | description | |
| |---|---| |
| | `error_id` | stable id, so a specific error can be cited | |
| | `category` | one of the 9 categories — see *Dataset statistics* for the taxonomy | |
| | `significance` | `significant` \| `insignificant` | |
| | `anchor_line` | 1-based line of `candidate_<label>` the error sits on, or `None` | |
| | `note` | optional free text, on 82 / 1582 errors (median 10 characters) | |
|
|
| Because the published report text is the numbered view the radiologist saw, `anchor_line` resolves to |
| a line by direct indexing: |
|
|
| ```python |
| line = study_row[f"candidate_{ann_row['candidate_label']}"].split("\n")[error["anchor_line"] - 1] |
| ``` |
|
|
|
|
| ## 3. Dataset statistics |
|
|
| - **100 studies** — 50 `chest_ct`, 50 `abdomen_ct`, one per patient |
| - **300 candidate reports** — 3 per study |
| - **600 independent expert reads** — 2 radiologists × 300 candidates |
| - **1582 error records** |
| - mean: 2.64, median: 3, min:0, max:10 |
| - 460 (29.1%) clinically significant |
| - 1495 (94.5%) localized to a line |
| - 82 (5.2%) carrying a free-text note |
| - 62 of the 600 reads confirmed error-free |
|
|
| The error taxonomy and the distribution of categories: |
| | category | definition | n | |
| |---|---|---| |
| | `hallucinated` | finding asserted that is absent from the reference | 903 (57.1%) | |
| | `wrong_certainty` | hedging error; over- or under-call of confidence | 229 (14.5%) | |
| | `missed` | omission of a reference finding | 135 (8.5%) | |
| | `wrong_severity` | wrong severity or extent | 87 (5.5%) | |
| | `wrong_location` | wrong site or laterality | 57 (3.6%) | |
| | `wrong_comparison` | false, missing, or wrong-direction comparison to a prior study | 56 (3.5%) | |
| | `wrong_measurement` | wrong numeric measurement or count | 52 (3.3%) | |
| | `wrong_characterization` | wrong descriptor or characterization | 37 (2.3%) | |
| | `other` | catch-all; see `note` | 26 (1.6%) | |
|
|
|
|
| ## Citation |
|
|
| ```bibtex |
| @misc{radmatch2026, |
| title = {RadMatch: Auditable Radiology Report Evaluation via Finding-Level Matching}, |
| author = {Corbi\`ere, Charles and Machado, L\'eo and Charley, Aubin and Caillard, Baptiste |
| and Le Floch, Korentin and Manceron, Pierre and Dancette, Corentin}, |
| year = {2026}, |
| } |
| ``` |
|
|
