The Efficacy of PET-CT in Detecting Bone Marrow Involvement in Patients with Newly Diagnosed Lymphoma: A Retrospective Study
Notice bibliographique
Résumé
Abstract Background: Patients diagnosed with Hodgkin lymphoma (HL) or non-Hodgkin lymphoma (NHL) undergo various investigations to determine disease stage. This includes Positron Emission Tomography with Computed Tomography (PET-CT) scan and bone marrow biopsy (BMB), which has historically been considered the gold standard for detecting involvement of the bone marrow (BM) by lymphoma. Recent studies have suggested that PET-CT scans can detect BM involvement in most patients with lymphoma. As such, there is growing interest into whether or not PET-CT scans may replace the need for BMB in staging patients with lymphoma. Objective: We conducted a retrospective chart review of patients newly diagnosed with lymphoma at our local cancer centre to evaluate the diagnostic performance of PET-CT scans in detecting BM involvement. Methods: Patients were eligible for inclusion if they were age 18 or older, had previously untreated HL or NHL diagnosed from January 2012 to August 2016, and underwent both BMB and PET-CT scan at time of staging. We collected the results of BM aspirate, flow cytometry, cytogenetics and biopsy. Patients were considered to have BM involvement if they had a positive BMB. PET-CT scans were retrospectively re-analyzed by two readers from the Division of Nuclear Medicine. Both were blinded to the patients' clinical information, including lymphoma diagnosis and BMB results. BM positivity by PET-CT scan was characterized as being either diffuse (relatively uniform increase in tracer uptake in the BM) or focal (localized increase in tracer uptake to one or more demarcated regions of BM). We performed sensitivity and specificity analyses of PET-CT scans. Results: The study included 110 patients: 102 patients with NHL and 8 with HL. The most common NHL subtype was diffuse large B-cell lymphoma (DLBCL) (n=40). For the entire cohort of patients with NHL, the sensitivity and specificity of PET-CT scan for diagnosing BM involvement were 78% (95% CI: 52-93%) and 86% (95% CI: 76-92%), respectively (Table 1). For patients with DLBCL, the sensitivity and specificity of PET-CT scan were 100% (95% CI: 52-100%) and 79% (95% CI: 63-91%), respectively. In this group, none of the patients with a negative PET-CT scan had a positive BMB. Five of the 7 patients with positive PET-CT scans but negative BMB had focal BM involvement on PET-CT scan. Conclusions: Although limited by small sample size, our data suggests that PET-CT scan is particularly adept at detecting BM involvement in patients with DLBCL and may detect focal BM involvement missed by BMB. The high sensitivity of PET-CT scan may lend support to clinicians foregoing BMB in patients with newly diagnosed lymphoma if imaging with PET-CT scan does not show involvement of the BM by lymphoma. Download : Download high-res image (120KB) Download : Download full-size image Disclosures No relevant conflicts of interest to declare.
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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 | 0,005 |
| 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 | 0,000 |
| Intégrité de la recherche | 0,001 | 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 ».