Study Design. Case-control study. Objective. The objective of this study was to identify the best laboratory and imaging factors to predict bone biopsy culture positivity in the setting of vertebral discitis/osteomyelitis (VDO). Summary of Background Data. Good predictors of bone biopsy culture positivity in the setting of VDO are unknown. Methods. Retrospective review was performed for 46 patients who underwent CT-guided bone biopsy for the evaluation of clinically confirmed VDO. Erythrocyte sedimentation rate, C-reactive protein (CRP), mean CT attenuation of the biopsied bone, and the change in the CT attenuation of the bone compared to unaffected vertebral bone (delta CT attenuation) were measured. Receiver-operator characteristic curve analyses were performed to identify the optimal threshold value for each variable. A multivariable logistic regression model was used to predict the probability of a positive bone culture using delta CT attenuation and CRPx100% fold above normal. Results. For one of the 46 VDO patients, bone cultures were not obtained. Approximately 35.6% (16/45) of bone cultures were positive. The most significant predictors of bone culture positivity were CRP x100% fold above normal (P = 0.011) and delta CT attenuation (P = <0.001). Optimized predictive thresholds were calculated to be CRP 4-fold above normal reference value (90.9% sensitivity, 73.7% specificity), or if the CT attenuation of the affected vertebral body was >25.9 HU lower relative to unaffected bone (93.8% sensitivity, 75.0% specificity). Conclusion. Delta CT attenuation, as well as CRP level over four times the upper limits of normal, were the strongest predictors for bone culture positivity in patients with VDO. Level of Evidence: 3

Purpose The objective of this study was to evaluate the accuracy of using CT attenuation and SUVs to differentiate enostoses from untreated and treated osteoblastic metastases on the attenuation-correction CT component of 18F-FDG PET/CTs. Methods We retrospectively reviewed 18F-FDG PET/CT studies of 117 patients (169 lesions), of which 65 had imaging of enostoses, and 52 had imaging showing the transition of lesions from untreated to treated osteoblastic metastases. We measured the mean CT attenuations and the SUVmax and SUVmean of each lesion. Receiver operating characteristic curve analyses were used to evaluate the accuracy of each metric in distinguishing enostoses from untreated and treated osteoblastic metastases. Results For differentiating enostoses from untreated osteoblastic metastases, mean CT attenuation achieved an area under the receiver operating characteristic curve (AUC) of 90.8%, with an optimized threshold of 795 HU. SUVmax achieved an AUC of 94.9%, with an optimized threshold of 2.2. For differentiating enostoses from treated osteoblastic metastases, the AUCs for every metric decreased, with mean CT attenuation being the best at 82.7%. A joint predictive model combining both CT attenuation and SUV increased the AUC to 88.3%, and performance was significantly better than SUVmax or SUVmean alone (P = 0.029 and P = 0.049, respectively). Conclusions CT attenuation and SUV can reliably distinguish between enostoses and metastases on 18F-FDG PET/CT. However, the accuracy of these metrics decreases when used to differentiate enostoses from treated metastases. A joint prediction model combining CT attenuation with SUV can improve accuracy.

Introduction Bone biopsies are often used to direct antibiotic choice in patients with suspected osteomyelitis. The aim of this study was to identify the best predictors of positive bone biopsy cultures. Methods A retrospective review of 845 patients who underwent computed tomography (CT)‐guided non‐spine bone biopsies at a tertiary academic healthcare institution. Thirty‐seven patients (4.4%) had biopsies performed for suspected osteomyelitis. Laboratory markers, as well as imaging features, were measured. t‐Tests and Fisher’s exact tests were used to compare clinical and demographic variables between patients with positive bone cultures and patients with negative bone cultures. Multivariable logistic regression was used to identify the best predictors of bone culture positivity. Results All patients had negative blood cultures; however, only eight patients (21.6%) had positive bone cultures, with Staphyloccocus the most common organism. Multivariable logistic regression analysis showed that an open wound (OR = 14.00, 95% CI (1.74, 112.4), p = 0.013) and any fluid aspirated at the time of biopsy (OR = 10.50, 95% CI (1.21, 91.01), p = 0.033) were the best predictors of bone culture positivity. The area under the curve (AUC) for this multivariable model was 0.784 with sensitivity and specificity of 0.778 and 0.778, respectively. Interestingly, and contrary to popular belief, open wounds with exposed bone did not always yield positive bone cultures, and when cultures were positive, were not polymicrobial. Conclusions Aspiration of fluid at the time of biopsy and the presence of an open wound are the best predictors of positive bone cultures.