Overestimation of cerebral aneurysm wall thickness by black blood MRI?
Notice bibliographique
Résumé
Recently, Park et al (1) reported unruptured saccular cerebral aneurysm (USCA) wall thicknesses on the order of 0.5 mm using a black blood double-inversion (BBDI) protocol having an in-plane resolution of 0.5 mm and slice thickness of 3 mm. Early in their discussion of the results the authors concede that their measurements were greater than the “20–500 micron” (p. 1181) wall thicknesses reported by specimen-based studies and attribute this to “different state of the aneurysms between [their] study (in vivo and unruptured state) and previous studies (ex vivo and ruptured state) (p. 1182).” Later, in discussing the potential limitations of their study, they add that their measured wall thicknesses were “similar to the pixel size of the BBDI; therefore, there might have been measurement errors (p. 1183).” In fact, there is a good chance those measurement errors, rather than differences in the states of the aneurysms, are at the root of the discrepancy between the MRI- and specimen-based thickness measurements. Referring to fig. 8 of our recent study on wall thickness (2) overestimation, an aneurysmal wall having a true thickness of, say, 250 μm would, at 0.5 mm acquired resolution, appear to have a thickness closer to 0.7 mm. That the authors report 0.5–0.6 mm wall thickness suggests that ours is likely the worst-case scenario, since it ignores the potentially salutary influence of surrounding tissue, and of operator judgment in manual segmentation vs. our automated edge detection. Nevertheless, it seems likely that the BBDI protocol used by the authors has served to overestimate the USCA wall thickness by more than they imply. Moreover, as we (2) and others (3) have also shown, such overestimation can be exacerbated by thick slice acquisitions when anatomical complexity and wall curvature may introduce obliqueness between the wall and slice plane, such as might be the case for smaller aneurysms. This effect only gets worse if slice thickness is sacrificed for higher in-plane resolution. As such, the authors are correct to conclude, “near isotropic resolution with 1024 matrices may be necessary for evaluation of the entire USCA wall (p. 1183).” However, what they fail to mention is that this will require at least an order-of-magnitude reduction in voxel volume compared to their current acquisition. While not wishing to discourage the noninvasive measurement of cerebral aneurysm wall thickness, we feel that a stronger message regarding the potential for severe overestimation due to partial volume effects is warranted in light of the spatial resolutions currently achievable, even at 3 Tesla (4). We do encourage the authors and others to carry out ex vivo imaging studies to demonstrate the true capabilities and limitations of MRI for resolving the walls of USCA. David A. Steinman PhD [email protected]*, Luca Antiga PhD , Bruce A. Wasserman MD , * Biomedical Simulation Laboratory Department of Mechanical & Industrial Engineering University of Toronto Toronto, ON, Canada, Biomedical Engineering Department Mario Negri Institute for Pharmacological Research Ranica (BG), Italy, Department of Radiology Johns Hopkins School of Medicine Baltimore, Maryland, USA.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,014 | 0,063 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,002 |
| Communication savante | 0,002 | 0,004 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».