Three‐dimensional complementary breast ultrasound (3D CBUS): Improving 3D spatial resolution uniformity with orthogonal images
Notice bibliographique
Résumé
Abstract Background With increasing evidence supporting three‐dimensional (3D) automated breast (AB) ultrasound (US) for supplemental screening of breast cancer in increased‐risk populations, including those with dense breasts and in limited‐resource settings, there is an interest in developing more robust, cost‐effective, and high‐resolution 3DUS imaging techniques. Compared with specialized ABUS systems, our previously developed point‐of‐care 3D ABUS system addresses these needs and is compatible with any conventional US transducer, which offers a cost‐effective solution and improved availability in clinical practice. While conventional US transducers have high in‐plane resolution (axial and lateral), their out‐of‐plane resolution is constrained by the poor intrinsic elevational US resolution. Consequently, any oblique view plane in an acquired 3DUS image will contain high in‐plane and poor out‐of‐plane resolution components, diminishing spatial resolution uniformity and overall diagnostic utility. Purpose To develop and validate a novel 3D complementary breast ultrasound (CBUS) approach to improve 3DUS spatial resolution uniformity using a conventional US transducer by acquiring and generating orthogonal 3DUS images. Methods We previously developed a cost‐effective, portable, dedicated 3D ABUS system consisting of a wearable base, a compression assembly, and a mechanically driven scanner for automated 3DUS image acquisition, compatible with any commercial linear US transducer. For this system, we have proposed 3D CBUS approach which involves acquiring and registering orthogonal 3DUS images ( and ) with an aim of overcoming the poor resolution uniformity in the scanning direction in 3D US images. The voxel intensity values in the 3D CBUS image are computed with a spherical‐weighted algorithm from the original orthogonal 3DUS images. Experimental validation was performed with 2DUS frame densities of 2, 4, 6 frames mm−1 using an agar‐based phantom with a speed of sound of 1540 ms−1 and an embedded nylon bead. Lateral and axial full‐width at half‐maximum (FWHMLAT and FWHMAX) values were calculated from cross‐sections taken at polar view planes ranging from 0° to 90° for 3DUS and 3D CBUS images of a bead phantom in focal zone and far field regions. Kendall's Tau‐b correlation coefficients were calculated between FWHM measurements and cross‐section angle for all frame density settings at a significance level of . Volumetric 3D segmentations were performed for 3DUS and 3D CBUS images of an inclusion phantom to confirm volumetric reconstruction accuracy. For statistical analysis, a repeated measures ANOVA with the Greenhouse‐Geisser correction was performed at a significance level of . Results Experimental validation of the orthogonal 3DUS images show complementary trends of increasing and decreasing FWHMLAT from in‐plane to out‐of‐plane (0° and 90° and vice versa) views. This is exemplified with the scan taken at 4 frames mm−1 in the focal zone, where FWHMLAT ranges from 3.51 to 1.10 mm for and 1.02–3.02 mm for , spanning 0°–90°, respectively. When combined in the 3D CBUS image, the FWHMLAT exhibits greater uniformity across view angles by mitigating poor out‐of‐plane resolution using its complementary in‐plane component, with corresponding FWHMLAT values of 1.27 and 1.46 mm. While visual enhancements were seen in the 3D CBUS image, no statistically significant differences were found in volumetric measurements of the spherical inclusions in the 3DUS and 3D CBUS images. Conclusion The out‐of‐plane resolution in the orthogonal 3DUS images is improved upon their combination into a single 3D CBUS image. These results demonstrate that the proposed 3D CBUS generation approach can improve 3D spatial resolution uniformity, while employing a commercial US transducer. The proposed 3D CBUS method shows potential utility for improving image resolution uniformity in 3D ABUS images, with the goal of improving point‐of‐care breast cancer supplemental screening and diagnostic applications, particularly in women with dense breasts and limited resource settings.
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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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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 ».