Automation of the Hematopoietic CFC Assay for Human Cord Blood, Bone Marrow and Mobilized Peripheral Blood Samples
Notice bibliographique
Résumé
Abstract Abstract 3001 The hematopoietic colony-forming-cell (CFC) assay is a valuable tool to assess the potency of cell products (umbilical cord blood, apheresis products, bone marrow) for hematopoietic stem cell transplantation and for toxicity screening in therapeutic drug development. However, the manual colony enumeration that has been required is subjective and time consuming even for experienced users. This subjectivity limits the accuracy of the assay and contributes to a high degree of inter-laboratory variability. To reduce this variability, STEMCELL Technologies has developed an imaging and analysis system (STEMvision™) for automation of CFC assay colony enumeration. We have previously shown results validating the instrument for use in cord blood (CB) cell assays (Wognum et al. 37th Annual Meeting of the European Group for Blood and Marrow Transplantation, Hamburg, Germany 2011). Here we additionally present recent results comparing automated and manual colony counting for human mobilized peripheral blood (mPB), and bone marrow (BM). Samples of CB, mPB, and BM mononuclear cells were inoculated into semi-solid culture media (Methocult™ H4034, H4434, and H4435) and plated into special meniscus-free culture plates (SmartDish™). After 14 days in culture, automated colony counts were obtained from each sample using algorithms specifically optimized for each type of product (CB, mPB, and BM). The same cultures were then manually enumerated by 2–5 operators using the standard microscope method (microscope counts) and by enumerating colonies on the STEMvision™ images (image counts). For the each of the cell products (hCB, mPB, BM), the automated total colony counts were highly correlated to the average manual total colony counts. The table below compares the total manual image counts to the automated counts. Linear regression of the data shows that in addition to being highly correlated (r2 >0.90), the two counting methods give nearly identical results on average (the line of identity has a slope of 1). The efficacy of automated classification of colonies as erythroid or myeloid+mixed was evaluated by comparing the proportion of myeloid counts (myeloid / total) in each sample for image and automated counts. The % agreement was determined as as the differential between the myeloid proportions of the manual image and automated counts. The table below shows that on average, the agreement was greater than 90%. Variability of colony counting was also significantly reduced with the STEMvision™ instrument. We found that for multiple independent measurements of a given sample, the coefficient of variance (CV) of the normalized counts was 11% for the microscope counts (2–5 different operators), 7.9% for the image counts (2–5 different operators) and 4.4% for the automated counts (2–5 different instruments). The low CV for the automated counts was not operator dependent: for 6 samples analyzed by 6 operators using a single instrument, the CV for normalized total colony counts was 4.3%. Automated colony counting with the STEMvision™ instrument has thus been shown to be highly correlated to manual scoring methods for the most common hematopoietic stem cell transplantation products(CB, mPB, and BM). In addition, automation of the assay analysis significantly reduced the variability across multiple operators relative to manual counting methods. As a result, STEMvision™ has the ability to improve standardization of the CFC assay analysis through reduced intra- and inter-lab variability. We have reported previously on the internal and independent multi-center validation of this automated system for CB products. Rigorous validation of for BM and mPB cell products is currently in progress. In addition to providing standardization, this instrument reduces the time required for the assay readout and provides a means of permanent archiving of colony assay images. In the future, the image analysis output will provide quantitative information related to colony morphology that is not easily obtained by manual analysis (eg. colony size, density, symmetry). Such information would enable automated assessment of hematopoietic toxicity. Disclosures: Egeler: Stemcell Technologies: Employment. Wognum:Stemcell Technologies: Employment. Grande:Stemcell Technologies: Employment. Yuan:Stemcell Technologies: Employment. Woodside:Stemcell Technologies: Employment. Thomas:Stemcell Technologies: Employment, Patents & Royalties.
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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 | 0,003 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,002 |
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 ».