Can CT Replace MRI in Preoperative Assessment of the Circumferential Resection Margin in Rectal Cancer?
Notice bibliographique
Résumé
UNLABELLED: The surgical circumferential resection margin in total mesorectal excision surgery is defined by the relationship of the tumor to the mesorectal fascia. Patients with anticipated tumor invasion of the mesorectal fascia receive neoadjuvant therapy to downstage/downsize the tumor and to obtain tumor-free resection margins.Tumor relationship to the mesorectal fascia is accurately determined by MRI. Compared with MRI, multidetector-row computed tomography is more widely available, faster, less costly, and provides the ability to simultaneously assess the liver, peritoneum, and retroperitoneum for metastases. PURPOSE: The objective of this study was to compare the accuracy of multidetector-row CT with conventional MRI in diagnosis of rectal cancer invasion of the mesorectal fascial envelope. MATERIALS AND METHODS: During a 2-year period, all patients were enrolled in this study who had biopsy-proven rectal carcinoma and were referred, as a part of the routine preoperative staging workup, for a CT scan of the abdomen and pelvis and also an MRI of the pelvis.All examinations were reviewed independently by 2 radiologists who were blinded from one another, from the findings of the other modality, and from clinical information. Both observers were dedicated abdominal radiologists who are experienced in reading pelvic CT and MRI. Categorical agreement between MRI and multidetector-row CT for all the evaluated parameters of the tumor position, mesorectal fascia, and lymph nodes, as well as the interobserver agreement between CT and MRI, was determined by the intraclass correlation weighted kappa statistic to measure the data set's consistency. RESULTS: Among the study's 92 patients, the tumor characteristics suggested by multidetector-row CT agreed with those of MRI, with a weighted kappa ranging from 0.488 to 0.748 for the first reader and 0.577 to 0.800 for the second reader. Interobserver agreement ranged from 0.506 to 0.746.Agreement regarding mesorectal fascia characteristics differed significantly between multidetector-row CT and MRI, depending on the level of assessment. In the distal rectum, agreement was 0.207 for the first reader and 0.385 for the second reader. In the mid rectum, agreement was 0.420 and 0.527, respectively, and in the proximal rectum agreement was 0.508 and 0.520. Interobserver agreement was 0.737 at the distal level and 0.700 at the mid and proximal levels. Agreement regarding measurement of the distance from the tumor to the mesorectal fascia was 0.425 for the first reader and 0.723 for the second reader, with interobserver agreement of 0.766. Agreement in assessment of the number of lymph nodes ranged from 0.743 to 0.787 for the first reader and 0.754 to 0.840 for the second reader. Interobserver agreement ranged from 0.779 to 0.841. Agreement in assessment of the size of the lymph nodes ranged from 0.540 to 0.830 for the first reader and 0.850 to 0.940 for the second reader. Interobserver agreement ranged from 0.900 to 0.920. Agreement in assessment of the distance from nodes to the mesorectal fascia was 0.320 for the first reader and 0.401 for the second reader, with interobserver agreement of 0.950. CONCLUSION: The results of this study differ from previously published data by demonstrating substantial agreement between readers in multidetector-row CT assessment of the tumor, mesorectal fascia, and lymph nodes. With the exceptions of mesorectal fascia in the distal rectum and the distance from the nodes to mesorectal fascia, other evaluated parameters were assessed with moderate and substantial agreement between multidetector-row CT and MRI. However, our findings suggest that multidetector-row CT does not correlate well enough with MRI findings to replace it in rectal cancer staging.
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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 | 0,001 |
| 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 | 0,000 | 0,000 |
| 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 ».