Total Kidney Volume Measurements in ADPKD by 3D and Ellipsoid Ultrasound in Comparison with Magnetic Resonance Imaging
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Total kidney volume is a validated prognostic biomarker for autosomal dominant polycystic kidney disease. Total kidney volume by magnetic resonance imaging (MRI) and manual segmentation is considered the "reference standard," but it is time consuming and not readily accessible. By contrast, three-dimensional (3D) ultrasound provides a promising technology for total kidney volume measurements with unknown potential. Here, we report a comparative study of total kidney volume measurements by 3D ultrasound versus the conventional methods by ultrasound ellipsoid and MRI ellipsoid. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: This single-center prospective study included 142 patients who completed a standardized 3D ultrasound and MRI. Total kidney volumes by 3D ultrasound and ultrasound ellipsoid were compared with those by MRI. We assessed the agreement of total kidney volume measurements by Bland-Altman plots and misclassification of the Mayo Clinic imaging classes between the different imaging methods, and we assessed prediction of Mayo Clinic imaging classes 1C-1E by average ultrasound kidney length >16.5 cm. RESULTS: Compared with MRI manual segmentation, MRI ellipsoid, 3D ultrasound, and ultrasound ellipsoid underestimated total kidney volume (mean difference: -3%, -9%, and -11%, respectively), with Mayo Clinic imaging classes misclassified in 11%, 21%, and 22% of patients, respectively; most misclassified cases by MRI ellipsoid (11 of 16), 3D ultrasound (23 of 30), and ultrasound ellipsoid (26 of 31) were placed into a lower Mayo Clinic imaging class. Predictions of the high-risk Mayo Clinic imaging classes (1C-1E) by MRI ellipsoid, 3D ultrasound, and ultrasound ellipsoid all yielded high positive predictive value (96%, 95%, and 98%, respectively) and specificity (96%, 96%, and 99%, respectively). However, both negative predictive value (90%, 88%, and 95%, respectively) and sensitivity (88%, 85%, and 94%, respectively) were lower for 3D ultrasound and ultrasound ellipsoid compared with MRI ellipsoid. An average ultrasound kidney length >16.5 cm was highly predictive of Mayo Clinic imaging classes 1C-1E only in patients aged ≤45 years. CONCLUSIONS: Total kidney volume measurements in autosomal dominant polycystic kidney disease by 3D ultrasound and ultrasound ellipsoid displayed similar bias and variability and are less accurate than MRI ellipsoid. Prediction of high-risk Mayo Clinic imaging classes (1C-1E) by all three methods provides high positive predictive value, but ultrasound ellipsoid is simpler to use and more readily available.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".