QUANTIFYING OSTEOSARCOPENIA IN A PRECLINICAL MODEL OF METASTATIC CANCER USING IMAGING BIOMARKERS
Notice bibliographique
Résumé
Growing evidence shows a strong relationship between sarcopenia (generalized loss of skeletal muscle mass, strength, and function) and osteopenia (low bone mineral density) in many diseases, however to date the integrated study of osteosarcopenia has been limited. This study aimed to quantify osteosarcopenia and the relationships between bone and muscle-based imaging biomarkers in a preclinical model of osteolytic metastasis. Seven six-week-old athymic female rats (Hsd:RH-Foxn1rnu, Envigo) were studied. Institutional approval was obtained and ARRIVE guidelines were followed. Four animals were inoculated with luciferase-transfected HeLa human cervical cancer cells via intracardiac injection (day 0) and three rats served as healthy controls. Animals were imaged using in vivo μMR (NanoScan PET/MR, Mediso, T1 GRE 3D axial with Gd contrast, 0.18\0.18\1mm voxels) and μCT (NanoScan SPECT/CT/PET, Mediso, 69μm isotropic voxels) at one day prior to and 21 days post cell injection. In vivo bioluminescence imaging (day 15, day 21), in vivo μCT, animal body weight, and general animal observations were used to assess tumour burden. Animals were euthanized on day 21. Excised vertebrae were μCT imaged (μCT100, Scanco, 34.4μm isotropic voxels). In vivo μCT and μMR images were cropped at L2/L3 and L4/L5 intervertebral disc midpoints and fused using manual and automatic registration (BRAINS registration module, 3D Slicer 4.11.20210226). Psoas muscles were manually segmented from fused μCT/μMR images and psoas muscle volume (normalized by L2 vertebral volume) and mean attenuation (as an indicator of muscle composition1) measured. Bone mineral density (BMD) of the L2 vertebrae was measured from ex vivo μCT images. T-tests compared biomarkers of non-metastatic and metastatic cohorts and Pearson's correlation was evaluated between the biomarkers. Three of four injected rats developed osteolytic bone tumours. Non-metastatic animals had higher BMD (p=0.00081) and change in normalized psoas volume (p=0.0051) compared to metastatic animals (figure 1a,b). Non-metastatic animals had lower change in normalized psoas attenuation (p=0.042) (figure 1c). A strong positive relationship was found between change in normalized psoas volume and BMD (R=0.95, p=0.00085) (figure 2a). Significant negative correlations were found between change in psoas attenuation and BMD (R=−0.87, p=0.011) and change in normalized psoas volume and change in psoas attenuation (R=−0.88, p=0.0086) (figure 2b,c). The presence of osteosarcopenia was indicated by the relative loss of bone and muscle mass in metastatic animals. The rat which did not develop cancer despite inoculation had bone and muscle biomarkers reflecting its healthy status. Expected differences in BMD and change in normalized psoas volume between non-metastatic and metastatic animals were accompanied by differences in change in psoas attenuation (suggestive of fatty infiltration of muscle). However, surprisingly, our results suggest that non-metastatic animals had more fatty infiltration than metastatic animals. Additional samples and histology will confirm changes in muscle composition and better link the current imaging biomarkers to physical changes in muscle. These imaging-based biomarkers quantifying osteosarcopenia in preclinical models of skeletal metastases can ultimately be used to study disease progression and treatment response. For any figures or tables, please contact the authors directly.
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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) | 0,001 | 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 ».