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To develop an approach for automatically analyzing bone metastases (BMs) on bone scintigrams based on deep learning technology. This research included a bone scan classification model, a regional segmentation model, an assessment model for tumor burden and a diagnostic report generation model. Two hundred eighty patients with BMs and 341 patients with non-BMs were involved. Eighty percent of cases were randomly extracted from two groups as training set. Remaining cases were as testing set. A deep residual convolutional neural network with different structures was used to determine whether metastatic bone lesions existed, regions of lesions were automatically segmented. Bone scan tumor burden index (BSTBI) was calculated; finally, diagnostic report could be automatically generated. The sensitivity, specificity and accuracy of classification model were compared with three physicians with different clinical experience. The Dice coefficient evaluated the effect of segmentation model and compared to the result of nnU-Net model. The correlation between BSTBI and blood alkaline phosphatase (ALP) level was analyzed to verify the efficiency of BSTBI. The performance of report generation model was evaluated by the accuracy of interpretation of report. In testing set, the sensitivity, specificity and accuracy of classification model were 92.59%, 85.51% and 88.62%, respectively. The accuracy showed no statistical difference with moderately and experienced physicians and obviously outperformed the inexperienced. The Dice coefficient of BMs area was 0.7387 in segmentation stage. Based on the whole model frame, our segmentation model outperformed the nnU-Net. BSTBI value changed as the BMs changed. There was a positive correlation between BSTBI and ALP level. The accuracy of report generation model was 78.05%. Deep learning based on automatic analysis frameworks for BMs can accurately identify BMs, preliminarily realize a fully automatic analysis process from raw data to report generation. BSTBI can be used as a quantitative evaluation indicator to assess the effect of therapy on BMs in different patients or in the same patient before and after treatment.

To assess efficacy and safety of imaging-guided radiofrequency ablation (RFA) of Osteoid Osteoma (OO) in both typical and atypical sites. Between January 2014 and March 2019, 102 consecutive percutaneous RFA were performed and retrospectively reviewed. The procedures were performed using a RFA bipolar ablation system (Covidien, exposed tip of 0.7-1cm), under Computed Tomography (CT) guidance or using a navigation system (Masmec) under CT and Cone Beam CT (CBCT) guidance. Patients were followed up over 24 months. Clinical success and recurrences were considered on the base of established criteria. In patients with clinical failure and/or imaging evidence of relapse, retreatment was considered. Administered power per-procedure was ≤8 W (mean temperature, 90°C). The pre-procedure average value of visual analog scale (VAS) was 8.33+/-0.91. Primary and secondary success rate 96.08% (98/102) and100% (102/102), respectively. No major complication was described. Technical success was proved in every patient by CT scan acquisition after needle positioning. Relapse and tumour location were significantly correlated (p-value = 0.0165). The mean dose-length product was 751.55 mGycm2. Advanced bone healing was noted in 68 lesions after 1y-follow up and in 86 lesions after 2y-follow up. Imaging-guided percutaneous RFA is a highly effective technique for OO, both in typical and atypical sites. CT or CBCT guidance, navigation systems and operator experience grant the technical success, which is the most crucial parameter affecting outcome.

Objective: To determine the values of the Sacroiliac Joint Index (SI Index) in normal population and patients with sacroiliitis (SI) and the correlation of normal values with age and gender. Study Design: Prospective longitudinal study. Place and Duration of Study: Nuclear Medical Centre, Armed Forces Institute of Pathology, Rawalpindi Pakistan, from Dec 2020 to Jul 2022. Methodology: A total of 140 patients (Group-I consisting of 129 cancer patients having no clinical or radiological evidence of SI referred for metastatic/staging workup and Group-II consisting of 11 patients with clinical, laboratory and radiological diagnosis of ankylosing spondylitis) who underwent whole body bone scintigraphy using Technetium Pertechnetate (Tc-99m) labelled Methylene Diphosphonate (MDP) were included. The SI Index was calculated for each patient using the sacroiliac joint (SIJ) to sacrum radiotracer uptake ratio using the ROI method. Results: The mean SI Index was 1.02±0.09, (range: 0.87-1.24) in normal individuals while 1.28±0.09 (range: 1.15-1.53) in patients with SI. A significant statistical difference was observed in both groups for the SI Index (p-<0.001). In addition, the SI Index was significantly associated with age (p=0.016) in the normal population. Conclusion: The SI Index quantification using bone scintigraphy is a sensitive and cost-effective method for detecting SI. In addition, the SI Index differs according to age, so a different cut-off value should be used for each group.

Objective(s): Nuclear medicine technologists in Japan often perform additional single-photon emission computed tomography (SPECT) with or without computed tomography (CT) after whole-body imaging for bone scintigraphy. In this study, we wanted to identify the bone scanning protocols used in Japan, together with the current clinical practices. Methods: The study was conducted between October and December 2017. We created a web survey that was hosted by the Japanese Society of Radiological Technology. The questionnaire included 12 items regarding the demographics of the responders, their scan protocols, and the imaging added to, or omitted from, routine protocols. Results: In total, 228 eligible responses were collected from participants with a mean of 11.6±8.4 years’ experience in nuclear medicine examination. All responders reported using routine scan protocols that included whole-body imaging. However, only 2%, 4%, 20%, and 14% of the responders also acquired single-field SPECT, single-field SPECT/CT, multi-field SPECT, and multi-field SPECT/CT, respectively.  Conclusion: Our survey results indicate that nuclear medicine practice in Japan is beginning to shift from planar whole-body imaging with additional spot planar images to additional SPECT or SPECT/CT. Further study is required to examine the optimal protocols for bone scintigraphy.

The therapy response of osseous metastases (OM) is commonly monitored by bone scintigraphies (BS). The aim of this study was to compare visual evaluation of changes in tracer uptake with quantitation in absolute units in OMs; 52 OMs from 19 patients who underwent BS with SPECT/CT at time points one and two (TP1/2) were analyzed retrospectively, with an average of 10.3 months between TP1 and 2. Tracer uptake in lesions was visually compared by two independent readers in both planar scintigraphies and SPECT/CT across both TPs and classified as regressive, stable, or progressive. Quantitative analysis was performed by measuring peak standardized uptake values (SUV). Based on quantitation, lesions were similarly classified as regressive (>30 % decrease), progressive (>30 % increase), or stable (rest). If available, uptake in reference regions in the lower thoracic or lumbar spine was used for normalization. In OMs at TP1 and TP2, mean SUVpeak (±SD) was found to be 20.4 (±20.8) and 16.4 (±11.5), respectively. For the reference region, mean SUVmean was 5.6 (±1.9) and 4.9 (±2.2). Agreement between quantitative and visual assessment was only moderate, with an average Cohen's kappa of 0.42 for planar scintigraphy and 0.62 for SPECT/CT. Discrepancies occurred in between 11 and 22 of the 52 lesions, depending on the reader and whether planar or SPECT imaging was considered. Compared to measuring uptake in absolute units, visual evaluation of skeletal scintigraphies for change in tumor metabolism yields inconsistent results in roughly one third of the cases.

Purpose The radionuclide bone scan is the cornerstone of skeletal nuclear medicine imaging. Bone scintigraphy is a highly sensitive diagnostic nuclear medicine imaging technique that uses a radiotracer to evaluate the distribution of active bone formation in the skeleton related to malignant and benign disease, as well as physiological processes. Methods The European Association of Nuclear Medicine (EANM) has written and approved these guidelines to promote the use of nuclear medicine procedures of high quality. Conclusion The present guidelines offer assistance to nuclear medicine practitioners in optimizing the diagnostic procedure and interpreting bone scintigraphy. These guidelines describe the protocols that are currently accepted and used routinely, but do not include all existing procedures. They should therefore not be taken as exclusive of other nuclear medicine modalities that can be used to obtain comparable results. It is important to remember that the resources and facilities available for patient care may vary.

We aimed to compare C-choline positron emission tomography/computed tomography (PET/CT) with conventional imaging, including pelvic magnetic resonance imaging (MRI), contrast-enhanced chest, abdomen, and pelvic computed tomography (CT), and bone scintigraphy, for prostate cancer restaging. Thirty patients (median prostate-specific antigen [PSA: 11.8 ng/mL]) with suspected recurrent prostate cancer following definitive treatment underwent C-choline PET/CT and conventional imaging, including pelvic MRI, contrast-enhanced chest, abdomen, and pelvic CT, and bone scintigraphy. The results were compared with regard to patient- and lesion-based diagnostic performance for local recurrence, and for lymph node and bony metastases using receiver operating characteristic (ROC) analysis and McNemar's test. Documented local recurrence and node and bony metastases were present in 11 (36.7%), 10 (33.3%), and 17 (56.7%) cases, respectively, of the enrolled patients. Patient-based sensitivity / specificity / accuracy / area under the ROC curve for C-choline-PET/CT for diagnosing local recurrence were 90.9% / 94.7% / 93.3% / 0.975 and for conventional imaging were 90.9% / 100% / 96.7% / 1.0. Those who underwent  C-choline-PET/CT for node metastasis were 90.0% / 95.0% / 93.3% / 0.925 and for conventional imaging were 70.0% / 95.0% / 86.7% / 0.905. Those who underwent  C-choline-PET/CT for bone metastasis were 94.1% / 92.3% / 93.3% / 0.991 and who underwent conventional imaging were 94.1% / 84.6% / 90.0% / 0.982. No significant differences were observed among them. The lesion-based detection rate of C-choline PET/CT for local recurrences and node and bone metastases as compared to conventional imaging was 92.9% (13/14) vs. 92.9% (13/14); 87.1% (27/31) vs. 54.8% (17/31); and 96.9% (219/226) vs. 90.3% (204/226) respectively, with significant differences noted for detection of node and bone lesions (p=0.0044 and p=0.00030, respectively). C-choline-PET/CT is more accurate in the detection of recurrent prostate cancer nodes and bony metastatic lesions compared to conventional imaging and has the advantage of restaging the disease in a single step.

Camurati-Engelmann disease (CED) or progressive diaphyseal dysplasia is a rare autosomal dominant hereditary disorder, characterized by simmetrical progressive sclerosis of long bones cortical diaphysis. This disease is caused by mutation in the TGF?1 gene [1,2]. Considering the rarity of this disorder (to date around 300 affected individuals have been reported) [3], we would like to share Bosnian and Herzegovina patient diagnosis with CED. To the best of our knowledge, no case of CED has been reported in Bosnia and Herzegovina till date. We evaluated a 10-year-old girl had history pain in the left leg and difficult movement since age of four. During the time, neuromuscular disease was suspected, but not confirmed. Symmetrical enhanced uptake seen on technetium hydroxymethylene diphosphonate (99m Tc-HDP) bone scintigraphy at diaphyses of longitudinal bones and cortical thickening of long bones seen at radiograms. Those finding pointed to Camurati-Engelmann diagnosed misdiagnosed for the long time.

Purpose Bone scintigraphy with 99m Tc-labeled diphosphonates can identify prostate cancer bone metastases with high sensitivity, but relatively low specificity, because benign conditions such as osteoarthritis can also trigger osteoblastic reactions. We aimed to investigate the diagnostic performance of 99m Tc-2,3-dicarboxy propane-1,1-diphosphonate ( 99m Tc-DPD) uptake quantification by single-photon emission computed tomography coupled with computed tomography (SPECT/CT) for distinguishing prostate cancer bone metastases from spinal and pelvic osteoarthritic lesions. Methods We retrospectively assessed 26 bone scans from 26 patients with known prostate cancer bone metastases and 13 control patients with benign spinal and pelvic osteoarthritic changes without known neoplastic disease. Quantitative SPECT/CT (xSPECT, Siemens Symbia Intevo, Erlangen, Germany) was performed and standardized uptake values (SUVs) were quantified with measurements of SUV max and SUV mean (g/mL) in all bone metastases for the prostate cancer group and in spinal and pelvic osteoarthritic changes for the control group. We used receiver operating characteristics (ROC) curves to determine the optimum SUV max cutoff value to distinguish between bone metastases and benign spinal and pelvic lesions. Results In total, 264 prostate cancer bone metastases were analyzed, showing a mean SUV max and SUV mean of 34.6 ± 24.6 and 20.8 ± 14.7 g/mL, respectively. In 24 spinal and pelvic osteoarthritic lesions, mean SUV max and SUV mean were 14.2 ± 3.8 and 8.9 ± 2.2 g/mL, respectively. SUV max and SUV mean were both significantly different between the bone metastases and osteoarthritic groups ( p  ≤ 0.0001). Using a SUV max cutoff of 19.5 g/mL for prostate cancer bone metastases in the spine and pelvis, sensitivity, specificity, positive and negative predictive values were 87, 92, 99 and 49%, respectively. Conclusion This study showed significant differences in quantitative 99m Tc-DPD uptake on bone SPECT/CT between prostate cancer bone metastases and spinal and pelvic osteoarthritic changes, with higher SUV max and SUV mean in metastases. Using a SUV max cutoff of 19.5 g/mL, high specificity and positive predictive value for metastases identification in the spine and pelvis were found, thus increasing accuracy of bone scintigraphy.

Bone scintigraphy is recognized as an efficient diagnostic method for whole-body screening for bone metastases. At the moment, whole-body bone scan image analysis is primarily dependent on manual reading by nuclear medicine doctors. However, manual analysis needs substantial experience and is both stressful and time-consuming. To address the aforementioned issues, this work proposed a machine-learning technique that uses phases to detect Bone scintigraphy. The first phase in the proposed model is the feature extraction and it was conducted based on integrating the Mobile Vision Transformer (MobileViT) model in our framework to capture highly complex representations from raw medical imagery using two primary components including ViT and lightweight CNN featuring a limited number of parameters. In addition, the second phase is named feature selection, and it is dependent on the Arithmetic Optimization Algorithm (AOA) being used to improve the Growth Optimizer (GO). We evaluate the performance of the proposed FS model, named GOAOA using a set of 18 UCI datasets. Additionally, the applicability of Bone scintigraphy for real-world application is evaluated using 2800 bone scan images (1400 normal and 1400 abnormal). The results and statistical analysis revealed that the proposed GOAOA algorithm as an FS technique outperforms the other FS algorithms employed in this study.