Notice bibliographique
Résumé
Central MessageAs segmentectomy becomes a more prevalent operation in the future, thoracic surgeons should be especially adept at right upper lobe segmentectomy.See Article page 288. As segmentectomy becomes a more prevalent operation in the future, thoracic surgeons should be especially adept at right upper lobe segmentectomy. See Article page 288. In this issue of JTCVS Techniques, Nakazawa and colleagues1Nakazawa S. Shimizu K. Kawatani N. Obayashi K. Ohtaki Y. Nagashima T. et al.Right upper lobe segmentectomy guided by simplified anatomic models.J Thorac Cardiovasc Surg Tech. 2020; 4: 288-297Google Scholar present a guide to right upper lobe segmental resection. “A guide to what?” you may ask, and you would not be the only one. Segmental resections of the right upper lobe are not common operations. Most of us are comfortable performing the simple segmentectomies that are S6 and S2 and multisegments of the left upper lobe. However, when we venture in the complex world of anatomical uncertainty that is the right upper lobe or the lower lobes, then many of us will quickly fall back to a lobectomy. In this work, the authors shed light on a new and imminent reality of lung cancer surgery. Lung cancer screening will result in smaller lesions that present to surgery. This in turn requires thoracic surgeons to be adept at segmentectomy. Since the prevalence of lung tumors is greatest in the right upper lobe, it follows that thoracic surgeons should be especially adept at right upper lobe segmentectomy. Easier said than done—since as presented here, even when simplified to the barest bones, we are left with 14 patterns of anatomical variations to the bronchovascular structures of the right upper lobe. Granted, there exists extensive literature on the adjuncts of segmental resection, such as 3-dimensional planning, indocyanine green dye marking, and inflation methods, to name a few. The majority of those rely on technological advancements to delineate the intersegmental plane and do not require much of a thought process or analytical work on the part of the surgeon. The method presented by Nakazawa and colleagues involves a careful review of the 3-dimensional anatomy and a didactic process whereby the surgeon needs to decide into which of the 14 patterns the patient's anatomy falls. Once that decision is made, the operation follows predetermined principles to execute the segmentectomy. The added value of this particular method, although not formally assessed in this manuscript, lies in the surgeon becoming very familiar and comfortable with all the anatomical variations. Think of it as following a geo-positional system map blindly versus interacting with the map to find the best path out of 14 different routes. With time, surgeons will become familiar enough with the anatomy to a point where performing and teaching segmentectomy will become as easy for us as performing a lobectomy. The skeptic will argue that this is a lot of work for an average of 13 cases per year, which is what is presented in this paper. Remember, however, that this is a paper from the future. The advent of lung cancer screening will increase this number exponentially, and the onus is upon us to be ready. Right upper lobe segmentectomy guided by simplified anatomic modelsJTCVS TechniquesVol. 4PreviewTo standardize the technical strategy for right upper lobe (RUL) segmentectomy, we previously developed simplified 3-dimensional (3D) anatomic models that classify the RUL anatomy into 14 patterns according to the branching pattern of bronchi and veins. We aimed to study the surgical outcome of RUL segmentectomy guided by these simplified anatomic models. Full-Text PDF Open Access
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».