Although differentiation between central chondroid tumors is important, their parallelism makes it a diagnostic conundrum for clinicians and radiologists. The objective of this study was to evaluate the efficiency of quantitative single photon emission computed tomography (SPECT)/computed tomography (CT) in differentiating grade I chondrosarcomas from enchondromas. We reviewed SPECT/CT images of patients with enchondromas and grade I chondrosarcomas arising in the long bones. Volume, mean standardized uptake value (SUVmean), and maximum standardized uptake value (SUVmax) of tumors were calculated from SPECT/CT images. In addition, clinical characteristics and radiological information were assessed. Of a total of 34 patients, 14 had chondrosarcomas. Chondrosarcoma group had significantly larger volume, and higher SUVmean and SUVmax of tumors than enchondroma group. There was no significant difference in age and tumor size between two groups. Areas under the receiver-operating characteristic curve (AUCs) for tumor volume, SUVmean, and SUVmax were 0.727, 0.757, and 0.875. In pairwise analyses, SUVmax had larger AUC than SUVmean (p = 0.0216). With a cut-off value of 15.6 for SUVmax, its sensitivity and specificity were 86% and 75% for differentiating between enchondroma and grade I chondrosarcoma. Quantitative SPECT/CT is a potential method to differentiate grade I chondroarcomas from enchondromas in patients with central chondroid tumors.

We evaluated the suitability of 18F-fluorodeoxythymidine (18F-FLT) positron emission tomography (PET)/computed tomography (CT) for assessment of the early response to induction therapy and its value for predicting clinical outcome in patients with acute myeloid leukemia (AML). Adult patients who had histologically confirmed AML and received induction therapy were enrolled. All patients underwent 18F-FLT PET/CT after completion of induction. PET/CT images were visually and quantitatively assessed. Cases with intensely increased bone marrow uptake in more than one third of the long bones and throughout the central skeleton were interpreted as PET-positive for resistant disease (RD). PET results were compared to the clinical response and outcome. In visual PET analysis of 10 eligible patients (7 male, 3 female; median age 58 years), 5 patients were interpreted as being PET-positive and 5 as PET-negative. Standardized uptake values were significantly different between PET-positive and PET-negative groups. Eight of 10 patients achieved clinical complete remission (CR)/CR with incomplete blood count recovery (CRi). Five CR/CRi patients had PET-negative findings, but 3 CR patients had PET-positive findings. Both of the RD patients had PET-positive findings. During follow-up, 2 CR patients with PET-positive findings relapsed, or were strongly suspected of relapse, 4 months after consolidation. 18F-FLT PET/CT after induction therapy showed good sensitivity and negative-predictive value for evaluating RD in patients with AML. This preliminary study suggests that 18F-FLT PET/CT may be valuable as a noninvasive tool for early assessment of the response to treatment and may provide prognostic value for survival in patients with AML.

This study was performed to assess the value of SPECT/CT radiomics parameters in differentiating enchondroma and atypical cartilaginous tumors (ACTs) located in the long bones. Quantitative HDP SPECT/CT data of 49 patients with enchondromas or ACTs in the long bones were retrospectively reviewed. Patients were randomly split into training (n = 32) and test (n = 17) data, and SPECT/CT radiomics parameters were extracted. In training data, LASSO was employed for feature reduction. Selected parameters were compared with classic quantitative parameters for the prediction of diagnosis. Significant parameters from training data were again tested in the test data. A total of 12 (37.5%) and 6 (35.2%) patients were diagnosed as ACTs in training and test data, respectively. LASSO regression selected two radiomics features, zone-length non-uniformity for zone (ZLNU_GLZLM) and coarseness for neighborhood grey-level difference (Coarseness_NGLDM). Multivariate analysis revealed higher ZLNU_GLZLM as the only significant independent factor for the prediction of ACTs, with sensitivity and specificity of 85.0% and 58.3%, respectively, with a cut-off value of 191.26. In test data, higher ZLNU_GLZLM was again associated with the diagnosis of ACTs, with sensitivity and specificity of 83.3% and 90.9%, respectively. HDP SPECT/CT radiomics may provide added value for differentiating between enchondromas and ACTs.

Objectives: This study aimed to evaluate the consistency of Centiloid (CL) values calculated using three commercially available software platforms: BTXBrain (v1.1.2), MIM (v7.3.7), and SCALE PET (v2.0.1). Methods: A total of 239 patients who underwent amyloid PET/CT with either F-18 flutemetamol (FMM) or F-18 florbetaben (FBB) were retrospectively analyzed. CL values were calculated using BTXBrain, MIM, and SCALE PET. Linear regression, Passing–Bablok regression, and Bland–Altman analysis were performed to assess the agreement between CL values. Subgroup analyses were conducted for each radiotracer. CL values were compared according to visual interpretation status. Results: Strong correlations were observed between CL values derived from the three software platforms (R² > 0.95). However, Passing–Bablok regression revealed significant proportional bias, with CL values from BTXBrain being lower than others, and CL values from SCALE PET being higher than others as CL values increased. Bland–Altman plots visualized the proportional bias, particularly between BTXBrain and SCALE PET. Subgroup analyses by radiotracer showed similar results. CL values in visually positive scans were significantly higher than those in visually negative scans across all platforms. Conclusions: The three commercial software programs demonstrated high consistency in CL quantification. However, a notable systematic bias was observed. Further evaluation of various scanner effects and CL calculation methods is warranted to improve the consistency and reproducibility of CL quantification in clinical practice.