18 F-NaF, a PET radiotracer of bone turnover, has shown potential as an imaging biomarker for assessing the response of bone metastases to therapy. This study aimed to evaluate the repeatability of 18 F-NaF PET-derived SUV imaging metrics in individual bone lesions from patients in a multicenter study. Methods: Thirty-five castration-resistant prostate cancer patients with multiple metastases underwent 2 whole-body (test-retest) 18 F-NaF PET/CT scans 3 ± 2 d apart from 1 of 3 imaging sites. A total of 411 bone lesions larger than 1.5 cm 3 were automatically segmented using an SUV threshold of 15 g/mL. Two levels of analysis were performed: lesion-level, in which measures were extracted from individual-lesion regions of interest (ROI), and patient-level, in which all lesions within a patient were grouped into a patient ROI for analysis. Uptake was quantified with SUV max , SUV mean , and SUV total . Test-retest repeatability was assessed using BlandAltman analysis, intraclass correlation coefficient (ICC), coefficient of variation, critical percentage difference, and repeatability coefficient. The 95% limit of agreement (LOA) of the ratio between test and retest measurements was calculated. Results: At the lesion level, the coefficient of variation for SUV max , SUV mean , and SUV total was 14.1%, 6.6%, and 25.5%, respectively. At the patient level, it was slightly smaller: 12.0%, 5.3%, and 18.5%, respectively. ICC was excellent (.0.95) for all SUV metrics. Lesion-level 95% LOA for SUV max, SUV mean , and SUV total was (0.76, 1.32), (0.88, 1.14), and (0.63, 1.71), respectively. Patient-level 95% LOA was slightly narrower, at (0.79, 1.26), (0.89, 1.10), and (0.70, 1.44), respectively. We observed significant differences in the variance and sample mean of lesion-level and patient-level measurements between imaging sites. Conclusion: The repeatability of SUV max , SUV mean , and SUV total for 18 F-NaF PET/CT was similar between lesion-and patient-level ROIs. We found significant differences in lesion-level and patient-level distributions between sites. These results can be used to establish 18 F-NaF PET-based criteria for assessing treatment response at the lesion and patient levels. 18 F-NaF PET demonstrates repeatability levels useful for clinically quantifying the response of bone lesions to therapy.

Purpose [F]Sodium fluoride (NaF) positron emission tomography (PET)/computed tomography (CT) is a promising radiotracer for quantitative assessment of bone metastases. This study assesses changes in early NaF PET/CT response measures in metastatic prostate cancer for correlation to clinical outcomes. Patients and Methods Fifty-six patients with metastatic castration-resistant prostate cancer (mCRPC) with osseous metastases had NaF PET/CT scans performed at baseline and after three cycles of chemotherapy (n = 16) or androgen receptor pathway inhibitors (n = 40). A novel technology, Quantitative Total Bone Imaging, was used for analysis. Global imaging metrics, including maximum standardized uptake value (SUV) and total functional burden (SUV), were extracted from composite lesion-level statistics for each patient and tracked throughout treatment. Progression-free survival (PFS) was calculated as a composite end point of progressive events using conventional imaging and/or physician discretion of clinical benefit; NaF imaging was not used for clinical evaluation. Cox proportional hazards regression analyses were conducted between imaging metrics and PFS. Results Functional burden (SUV) assessed midtreatment was the strongest univariable PFS predictor (hazard ratio, 1.97; 95% CI, 1.44 to 2.71; P < .001). Classification of patients based on changes in functional burden showed stronger correlation to PFS than did the change in number of lesions. Various global imaging metrics outperformed baseline clinical markers in predicting outcome, including SUV and SUV. No differences in imaging response or PFS correlates were found for different treatment cohorts. Conclusion Quantitative total bone imaging enables comprehensive disease quantification on NaF PET/CT imaging, showing strong correlation to clinical outcomes. Total functional burden assessed after three cycles of hormonal therapy or chemotherapy was predictive of PFS for men with mCRPC. This supports ongoing development of NaF PET/CT-based imaging biomarkers in mCRPC to bone.

Lung cancer, the most commonly diagnosed cancer worldwide, usually presents as solid pulmonary nodules (SPNs) on early diagnostic images. Classification of malignant disease at this early timepoint is critical for improving the success of surgical resection and increasing 5-year survival rates. 18F-fluorodeoxyglucose (18F-FDG) PET/CT has demonstrated value for SPNs diagnosis with high sensitivity to detect malignant SPNs, but lower specificity in diagnosing malignant SPNs in populations with endemic infectious lung disease. This study aimed to determine whether quantitative heterogeneity derived from various texture features on dual time FDG PET/CT images (DTPI) can differentiate between malignant and benign SPNs in patients from granuloma-endemic regions. Machine learning methods were employed to find optimal discrimination between malignant and benign nodules. Machine learning models trained by texture features on DTPI images achieved significant improvements over standard clinical metrics and visual interpretation for discriminating benign from malignant SPNs, especially by texture features on delayed FDG PET/CT images.

PURPOSE We previously reported the safety and immunologic effects of a DNA vaccine (pTVG-HP [MVI-816]) encoding prostatic acid phosphatase (PAP) in patients with recurrent, nonmetastatic prostate cancer. The current trial evaluated the effects of this vaccine on metastatic progression. PATIENTS AND METHODS Ninety-nine patients with castration-sensitive prostate cancer and prostate-specific antigen (PSA) doubling time (DT) of less than 12 months were randomly assigned to treatment with either pTVG-HP co-administered intradermally with 200 μg granulocyte-macrophage colony-stimulating factor (GM-CSF) adjuvant or 200 μg GM-CSF alone six times at 14-day intervals and then quarterly for 2 years. The primary end point was 2-year metastasis-free survival (MFS). Secondary and exploratory end points were median MFS, changes in PSA DT, immunologic effects, and changes in quantitative 18F-sodium fluoride (NaF) positron emission tomography/computed tomography (PET/CT) imaging. RESULTS Two-year MFS was not different between study arms (41.8% vaccine v 42.3%; P = .97). Changes in PSA DT and median MFS were not different between study arms (18.9 v 18.3 months; hazard ratio [HR], 1.6; P = .13). Preplanned subset analysis identified longer MFS in vaccine-treated patients with rapid (< 3 months) pretreatment PSA DT (12.0 v 6.1 months; n = 21; HR, 4.4; P = .03). PAP-specific T cells were detected in both cohorts, including multifunctional PAP-specific T-helper 1–biased T cells. Changes in total activity (total standardized uptake value) on 18F-NaF PET/CT from months 3 to 6 increased 50% in patients treated with GM-CSF alone and decreased 23% in patients treated with pTVG-HP (n = 31; P = .07). CONCLUSION pTVG-HP treatment did not demonstrate an overall increase in 2-year MFS in patients with castration-sensitive prostate cancer, with the possible exception of a subgroup with rapidly progressive disease. Prespecified 18F-NaF PET/CT imaging conducted in a subset of patients suggests that vaccination had detectable effects on micrometastatic bone disease. Additional trials using pTVG-HP in combination with PD-1 blockade are under way.

Objective Lung cancer usually presents as a solitary pulmonary nodule (SPN) on diagnostic imaging during the early stages of the disease. Since the early diagnosis of lung cancer is very important for treatment, the accurate diagnosis of SPNs has much importance. The aim of this study was to evaluate the discriminant power of dual time point imaging (DTPI) PET/CT in the differentiation of malignant and benign FDG-avid solitary pulmonary nodules by using neighborhood gray-tone difference matrix (NGTDM) texture features. Methods Retrospective analysis was carried out on 116 patients with SPNs (35 benign and 81 malignant) who had DTPI 18 F-FDG PET/CT between January 2005 and May 2015. Both PET and CT images were acquired at 1 h and 3 h after injection. The SUV max and NGTDM texture features (coarseness, contrast, and busyness) of each nodule were calculated on dual time point images. Patients were randomly divided into training and validation datasets. Receiver operating characteristic (ROC) curve analysis was performed on all texture features in the training dataset to calculate the optimal threshold for differentiating malignant SPNs from benign SPNs. For all the lesions in the testing dataset, two visual interpretation scores were determined by two nuclear medicine physicians based on the PET/CT images with and without reference to the texture features. Results In the training dataset, the AUCs of delayed busyness, delayed coarseness, early busyness, and early SUV max were 0.87, 0.85, 0.75 and 0.75, respectively. In the validation dataset, the AUCs of visual interpretations with and without texture features were 0.89 and 0.80, respectively. Conclusion Compared to SUV max or visual interpretation, NGTDM texture features derived from DTPI PET/CT images can be used as good predictors of SPN malignancy. Improvement in discriminating benign from malignant nodules using SUVmax and visual interpretation can be achieved by adding busyness extracted from delayed PET/CT images. Electronic supplementary material The online version of this article (10.1186/s40644-019-0243-3) contains supplementary material, which is available to authorized users.

An important step to allow for the accurate quantitative assessment of 18 F-Sodium fluoride (NaF) PET/CT images is to reduce the number of false positive metastases arising from benign diseases. NaF PET/CT is one of the most sensitive imaging modalities for the detection of bone metastases (Even-Sapir et al 2006). NaF PET has higher sensitivity and specificity for bone lesion detection than current clinical standard of 99m Tc-methylene diphosphonate (MDP) planar bone scans. NaF PET detects 30% more lesions with 5% fewer false positives than MDP (Even-Sapir et al 2006). However, the specificity of NaF PET is still only 70%, due to the non-tumor specific

Accurate registration over multiple scans is necessary to assess treatment response of bone diseases (e.g. metastatic bone lesions). This study aimed to develop and evaluate an articulated registration algorithm for the whole-body skeleton registration in human patients. In articulated registration, whole-body skeletons are registered by auto-segmenting into individual bones using atlas-based segmentation, and then rigidly aligning them. Sixteen patients (weight = 80-117 kg, height = 168-191 cm) with advanced prostate cancer underwent the pre- and mid-treatment PET/CT scans over a course of cancer therapy. Skeletons were extracted from the CT images by thresholding (HU>150). Skeletons were registered using the articulated, rigid, and deformable registration algorithms to account for position and postural variability between scans. The inter-observers agreement in the atlas creation, the agreement between the manually and atlas-based segmented bones, and the registration performances of all three registration algorithms were all assessed using the Dice similarity index-DSIobserved, DSIatlas, and DSIregister. Hausdorff distance (dHausdorff) of the registered skeletons was also used for registration evaluation. Nearly negligible inter-observers variability was found in the bone atlases creation as the DSIobserver was 96 ± 2%. Atlas-based and manual segmented bones were in excellent agreement with DSIatlas of 90 ± 3%. Articulated (DSIregsiter = 75 ± 2%, dHausdorff = 0.37 ± 0.08 cm) and deformable registration algorithms (DSIregister = 77 ± 3%, dHausdorff = 0.34 ± 0.08 cm) considerably outperformed the rigid registration algorithm (DSIregsiter = 59 ± 9%, dHausdorff = 0.69 ± 0.20 cm) in the skeleton registration as the rigid registration algorithm failed to capture the skeleton flexibility in the joints. Despite superior skeleton registration performance, deformable registration algorithm failed to preserve the local rigidity of bones as over 60% of the skeletons were deformed. Articulated registration is superior to rigid and deformable registrations by capturing global flexibility while preserving local rigidity inherent in skeleton registration. Therefore, articulated registration can be employed to accurately register the whole-body human skeletons, and it enables the treatment response assessment of various bone diseases.

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