Detection Of Bone Metastases Research Articles

Comparative diagnostic performance of 68Ga-PSMA-11 PET/CT and 68Ga-PSMA-11 PET/MRI in detecting biochemical recurrent bone metastasis in prostate cancer: a systematic review and meta-analysis.

The comparative diagnostic performance of 68Gallium (Ga)-PSMA-11 PET/CT and 68Ga-PSMA-11 PET/MRI in detecting bone metastases in prostate cancer (PCa) remains unclear. To systematically evaluate the early detection rate of biochemical recurrent (BCR) bone metastasis in PCa utilizing 68Ga-PSMA-11 PET/CT and 68Ga-PSMA-11 PET/MRI. We searched PubMed, Embase, and Web of Science for relevant articles up to April 2023 and extracted studies that examined the positivity rate of both 68Ga-PSMA-11 PET/CT and 68Ga-PSMA-11 PET/MRI in the context of the BCR bone metastasis of PCa patients. Random-effects model was used to compare positivity rates for two imaging modalities. Heterogeneity among studies was assessed using the I2 statistic. To evaluate the methodological quality of studies, we employed Quality Assessment of Diagnostic Performance Studies method. The study protocol was registered in PROSPERO (CRD42023454118). A total of 1670 publications were originally identified; 58 studies, encompassing a cohort of 8037 patients, met the inclusion criteria. Regarding the evaluation of BCR bone metastasis, results suggest no statistically significant difference in the utilization of 68Ga-PSMA-11 PET/CT versus 68Ga-PSMA-11 PET/MRI in 58 non-head-to-head studies (0.21, 95% CI=0.19-0.24 and 0.17, 95% CI=0.11-0.23; P = 0.19) and four head-to-head studies (0.16, 95% CI=0.08-0.27 and 0.16, 95% CI=0.08-0.27; P = 1.00). Meta-regression showed the study design of influenced the heterogeneity in the PET/MRI group (P < 0.01); but analysis of PET/CT did not identify the potential reason for heterogeneity. There was no statistically significant difference in identifying BCR bone metastasis in PCa patients between 68Ga-PSMA-11 PET/CT and 68Ga-PSMA-11 PET/MRI.

Comparison of 68Ga-DOTANOC and 18F-FDOPA PET/CT for Detection of Recurrent or Metastatic Paragangliomas.

Purpose To evaluate the diagnostic performance of gallium 68 (68Ga)-DOTA-NaI3-octreotide (68Ga-DOTANOC) and fluorine 18 (18F)-fluoro-l-3,4-dihydroxyphenylalanine (18F-FDOPA) PET/CT in detecting recurrent or metastatic paragangliomas. Materials and Methods This single-center retrospective study included patients with paragangliomas who underwent both 68Ga-DOTANOC PET/CT and 18F-FDOPA PET/CT between August 2021 and December 2023. The diagnostic performance of these two tracers in detecting recurrent or metastatic tumors was compared using several metrics, including sensitivity, negative predictive value, and accuracy. Results This study included 36 patients (median age, 52 years [range, 14-78 years]; 16 female, 20 male). Of these, nine underwent initial 68Ga-DOTANOC and 18F-FDOPA PET/CT examinations before treatment, and the remaining 27 underwent posttreatment examinations. Twenty-two of those 27 patients had recurrence or metastasis. According to lesion-level analysis, 68Ga-DOTANOC had higher sensitivity, negative predictive value, and accuracy for diagnosis of bone metastases than did 18F-FDOPA PET/CT (97% vs 78% [P < .001], 85% vs 42% [P = .02], and 97% vs 81% [P < .001], respectively). 18F-FDOPA PET/CT had higher sensitivity, negative predictive value, and accuracy for the diagnosis of liver metastases than did 68Ga-DOTANOC PET/CT (73% vs 15% [P < .001], 68% vs 41% [P = .04], and 83% vs 46% [P < .001], respectively). According to patient-level analysis, the sensitivity of 18F-FDOPA PET/CT for diagnosing liver metastases was higher than that of 68Ga-DOTANOC PET/CT (88% vs 25%; P = .04). Conclusion In patients with recurrent or metastatic paragangliomas, 68Ga-DOTANOC PET/CT showed better performance than 18F-FDOPA PET/CT in detecting bone metastases, and 18F-FDOPA PET/CT performed better in detecting liver metastases. Keywords: 68Ga-DOTANOC, 18F-FDOPA, Pheochromocytoma, Paraganglioma Published under a CC BY 4.0 license.

Diagnostic Ability of Quantitative Parameters of Whole-Body Bone SPECT/CT Using a Full-Ring 360° Cadmium-Zinc-Telluride Camera for Detecting Bone Metastasis in Patients with Prostate Cancer.

This study aimed to assess the diagnostic capability of quantitative parameters from whole-body bone single-photon emission computed tomography/computed tomography (SPECT/CT) in detecting bone metastases in prostate cancer patients; Methods: We retrospectively analyzed 82 prostate cancer patients who underwent staging bone scintigraphy with a full-ring 360° Cadmium-Zinc-Telluride (CZT) SPECT/CT system. From the SPECT/CT images, we measured the maximum (SUVmax) and mean (SUVmean) standardized uptake values at six normal bone sites (skull, humerus, thoracic spine, lumbar spine, iliac bone, and femur), and the SUVmax for both metastatic and benign bone lesions. Ratios of lesion SUVmax-to-maximum and mean uptake values at the skull, humerus, and femur were computed for each lesion; Results: SUVmax and SUVmean at the skull and femur exhibited significantly lower variance compared to those at the thoracic spine, lumbar spine, and iliac bone, and revealed no significant differences between patients with and without bone metastasis. In receiver operating characteristic curve analysis for detecting bone metastasis among 482 metastatic lesions, 132 benign bone lesions, and 477 normal bone sites, the lesion-to-femur mean uptake ratio demonstrated the highest area under the curve value (0.955) among SPECT/CT parameters. Using a cut-off value of 5.38, the lesion-to-femur mean uptake ratio achieved a sensitivity of 94.8% and a specificity of 86.5%; Conclusions: The bone lesion-to-femur mean uptake ratio was the most effective quantitative bone SPECT/CT parameter for detecting bone metastasis in prostate cancer patients. Quantitative analysis of bone SPECT/CT images could thus play a crucial role in diagnosing bone metastasis.

Whole-body PET/MRI to detect bone metastases: comparison of the diagnostic performance of the sequences.

Whole-body positron emission tomography/magnetic resonance imaging (WB-PET/MRI) is increasingly used in the initial evaluation of oncology patients. The purpose of this study was to compare the diagnostic performance of WB MRI sequences, attenuation-corrected raw data positron-emission tomography (AC PET), and PET/MRI fused images to detect bone metastases. We included 765 consecutive oncologic patients who received WB-PET/MRI from between January 2017 and September 2023. The presence of bone metastases was assessed using the individual sequences by two radiologists. Interobserver agreement was calculated. A receiver operating characteristic (ROC) analysis was performed to assess the performance of each individual sequence and fused images. Interobserver agreement for the detection of bone metastases on all sequences ranged from good to very good. The reading of the combination of MRI sequences with PET images showed statistically significantly better performance than the reading of individual MRI sequences and PET component only. Contrast enhanced T1 W Volume-interpolated breath-hold examination (CE T1W VIBE) sequence superior to PET for the detection of bone metastasis, but the statistical significance was not as high as with T1W-PET and CE T1W-PET fused images. The highest performance was achieved by the fused CE T1W-PET images with sensitivity of 100%, specificity of 92%, PPV of 96%, and NPV of 100%. The combination of these CE T1W VIBE sequences with PET images have the highest diagnostic performance in detecting bone metastases in oncologic patients. This sequence should be integrated in WB-PET/MRI acquisitions for initial staging of cancer.

Radiomics analysis of thoracic vertebral bone marrow microenvironment changes before bone metastasis of breast cancer based on chest CT

BackgroundBone metastasis from breast cancer significantly elevates patient morbidity and mortality, making early detection crucial for improving outcomes. This study utilizes radiomics to analyze changes in the thoracic vertebral bone marrow microenvironment from chest computerized tomography (CT) images prior to bone metastasis in breast cancer, and constructs a model to predict metastasis. Methods: This study retrospectively gathered data from breast cancer patients who were diagnosed and continuously monitored for five years from January 2013 to September 2023. Radiomic features were extracted from the bone marrow of thoracic vertebrae on non-contrast chest CT scans. Multiple machine learning algorithms were utilized to construct various radiomics models for predicting the risk of bone metastasis, and the model with optimal performance was integrated with clinical features to develop a nomogram. The effectiveness of this combined model was assessed through receiver operating characteristic (ROC) analysis as well as decision curve analysis (DCA). Results: The study included a total of 106 patients diagnosed with breast cancer, among whom 37 developed bone metastases within five years. The radiomics model’s area under the curve (AUC) for the test set, calculated using logistic regression, is 0.929, demonstrating superior predictive performance compared to alternative machine learning models. Furthermore, DCA demonstrated the potential of radiomics models in clinical application, with a greater clinical benefit in predicting bone metastasis than clinical model and nomogram. Conclusion: CT-based radiomics can capture subtle changes in the thoracic vertebral bone marrow before breast cancer bone metastasis, offering a predictive tool for early detection of bone metastasis in breast cancer.

MFP-YOLO: a multi-scale feature perception network for CT bone metastasis detection.

Bone metastasis is one of the most common forms of metastasis in the late stages of malignancy. The early detection of bone metastases can help clinicians develop appropriate treatment plans. CT images are essential for diagnosing and assessing bone metastases in clinical practice. However, early bone metastasis lesions occupy a small part of the image and display variable sizes as the condition progresses, which adds complexity to the detection. To improve diagnostic efficiency, this paper proposes a novel algorithm-MFP-YOLO. Building on the YOLOv5 algorithm, this approach introduces a feature extraction module capable of capturing global information and designs a new content-aware feature pyramid structure to improve the network's capability in processing lesions of varying sizes. Moreover, this paper innovatively applies a transformer-structure decoder to bone metastasis detection. A dataset comprising 3921 CT images was created specifically for this task. The proposed method outperforms the baseline model with a 5.5% increase in precision and a 7.7% boost in recall. The experimental results indicate that this method can meet the needs of bone metastasis detection tasks in real scenarios and provide assistance for medical diagnosis.

Phase 2 trial of PSMA PET CT versus planar bone scan and CT in prostate cancer patients progressing while on androgen deprivation therapy

For prostate cancer patients who experience biochemical progression during androgen deprivation therapy (ADT), prostate-specific membrane antigen positron emission tomography/computed tomography (PSMA PET/CT) has not been prospectively compared to planar bone scan plus CT. This was a single-arm, head-to-head, prospective phase II trial (NCT04928820) designed to enroll 102 men with prostate cancer who experienced biochemical progression (rising prostate-specific antigen [PSA] ≥ 1 ng/mL) during ADT. All patients received 68Ga-PSMA-11 PET/CT and 99mTc-MDP planar bone scans. Each scan was interpreted by three central independent readers. The primary endpoint was the per-patient bone metastasis detection rate of PSMA PET/CT versus planar bone scan and CT. Secondary endpoints compared the number of bone metastases detected per patient and the inter-reader agreement of each imaging modality. Twenty-two men were enrolled between July 2021 and June 2022. Due to slow accrual following approval of PSMA PET radiotracers in the U.S. and a lack of a statistical signal between the two imaging modalities on interim analysis, this trial was closed early on October 2022. Median PSA was 8.5 ng/mL (interquartile range: 1.6–77.6). There was 100% agreement between the two scans. Six patients (27%) had negative findings and 16 patients (73%) had positive findings on both scans. PSMA PET/CT and bone scan plus CT detected an equal number of bone lesions for 14 patients (64%), PSMA PET/CT detected more bone lesions for six patients (27%), and bone scan plus CT detected more bone lesions for two patients (9.1%) (p = 0.092). The inter-reader agreement rates of PSMA PET/CT and bone scan plus CT were 96% and 82%, respectively (p = 0.25). In men with biochemical progression during ADT, 68Ga-PSMA-11 PET/CT and 99mTc-MDP planar bone scan plus CT had identical bone metastasis detection rates. Bone scan plus CT can continue to serve as a cost-effective and readily accessible restaging modality in patients with biochemical progression. ClinicalTrials.gov NCT04928820. Registered 16/06/2021.

Association between 99mTc-PSMA SPECT/CT imaging and prostate-specific antigen (PSA) and alkaline phosphatase (ALP) levels post-endocrine therapy in patients with prostate cancer and bone metastases

AimTo investigate the association between positive lesions detected by 99mTc-PSMA SPECT/CT and blood levels of prostate-specific antigen (PSA) and alkaline phosphatase (ALP) in patients with prostate cancer (PCa) and bone metastasis undergoing endocrine therapy. MethodsA retrospective analysis was performed on 43 patients diagnosed with PCa bone metastasis who underwent endocrine therapy. PSA, ALP, whole body bone imaging and 99mTc-PSMA SPECT/CT imaging were collected from all patients (Among them, 17 cases were re-examined 99mTc-PSMA SPECT/CT imaging). According to the results of the first 99mTc-PSMA SPECT/CT imaging for detecting bone metastasis, all cases were divided into two groups: positive group and negative group. The relationship between 99mTc-PSMA imaging and PSA and ALP was analyzed by ROC curve. Fisher exact probability method was used to examine the changes in imaging radioactivity uptake, PSA, and ALP levels in 17 patients after treatment, and P < 0.05 was statistically significant. ResultsAll 43 patients had different degrees of radioactive concentrations on whole-body bone imaging. The first 99mTc-PSMA SPECT/CT imaging showed positive bone metastases in 31 cases and negative bone metastases in 12 cases. ROC curve analysis of PSA and ALP, AUC were 0.778 and 0.770, respectively. When PSA > 1.13 ng/mL, 99mTc-PSMA SPECT/CT imaging diagnostic sensitivity was 93.55%, and specificity was 66.67%. When ALP was >86U/L, the diagnostic sensitivity of 99mTc-PSMA SPECT/CT imaging was 64.52%, and the specificity was 83.33%. In 17 cases, the PSA level decreased in 7 and increased in 10. There were 10 cases of increased ALP and 7 cases of decreased ALP levels. In the second 99mTc-PSMA imaging lesion, there were 9 cases with decreased or no uptake, and 8 cases with increased uptake or number of lesions. The changes in 99mTc-PSMA uptake by Fisher’s exact probability method were statistically significant (P < 0.05, P = 0.006, and P = 0.006, respectively), and ALP level was not statistically significant (P = 0.563). Conclusion99mTc-PSMA SPECT/CT imaging can detect PCa bone metastases, which are related to PSA levels. When PSA > 1.13 ng/mL, the sensitivity of diagnosis and detection of positive bone metastases is higher, and when ALP is >86U/L, 99mTc-PSMA imaging has higher specificity.

Evaluation of 68Ga-FAPI PET/CT and 18F-FDG PET/CT for the diagnosis of recurrent colorectal cancers

ObjectiveThe present study aimed to compare the diagnostic value of gallium-68-labeled fibroblast activation protein inhibitor positron emission tomography/computed tomography (68Ga-FAPI PET/CT) and fluorine-18-labeled fluorodeoxyglucose PET/CT (18F-FDG PET/CT) for detecting recurrent colorectal cancers (CRCs). Materials and MethodsFifty-six patients (age: 18–80 years, 31 men and 25 women) with suspected recurrent CRC were enrolled and underwent 18F-FDG PET/CT and 68Ga-FAPI PET/CT sequentially within 1 week. The maximum standard uptake value (SUVmax), tumor-to-background ratio (TBR), and diagnostic accuracy were estimated and compared between the two modalities by using Student’s t-test. The Wilcoxon signed-rank test was used to compare peritoneal carcinoma index (PCI) scores between the two imaging modalities. Results68Ga-FAPI PET/CT showed higher sensitivity for detecting recurrence (93 % vs. 79 %); lymph node metastasis (89 % vs. 78 %), particularly peritoneal lymph node metastasis (92 % vs. 63 %); and metastatic implantation on the intestinal wall (100 % vs. 25 %) compared to 18F-FDG PET/CT. However, 68Ga-FAPI PET/CT showed lower sensitivity for detecting bone metastasis (67 % vs. 100 %). The mean SUVmax values of peritoneal metastases and metastatic implantation on the intestinal wall were 4.28 ± 2.70 and 7.58 ± 1.66 for 18F-FDG PET/CT and 5.66 ± 1.97 and 6.70 ± 0.25 for 68Ga-FAPI PET/CT, respectively. Furthermore, 68Ga-FAPI PET/CT showed significantly higher TBR for peritoneal metastatic lesions (4.22 ± 1.47 vs. 1.41 ± 0.89, p < 0.0001) and metastatic implantation on the intestinal wall (5.63 ± 1.24 vs. 2.20 ± 0.5, p = 0.02) compared to 18F-FDG PET/CT. For the same patient, 68Ga-FAPI PET/CT yielded a more accurate PCI score and a greater area under the curve value for the receiver operating characteristic curve (p < 0.01) than 18F-FDG PET/CT. Conclusion68Ga-FAPI PET/CT was superior to 18F-FDG PET/CT for detecting recurrence and peritoneal metastases. Hence, we propose the combination of these two modalities for better clinical diagnosis and management of patients with CRC.

Artificial Intelligence in Detection, Management, and Prognosis of Bone Metastasis: A Systematic Review.

Metastasis commonly occur in the bone tissue. Artificial intelligence (AI) has become increasingly prevalent in the medical sector as support in decision-making, diagnosis, and treatment processes. The objective of this systematic review was to assess the reliability of AI systems in clinical, radiological, and pathological aspects of bone metastases. We included studies that evaluated the use of AI applications in patients affected by bone metastases. Two reviewers performed a digital search on 31 December 2023 on PubMed, Scopus, and Cochrane library and extracted authors, AI method, interest area, main modalities used, and main objectives from the included studies. We included 59 studies that analyzed the contribution of computational intelligence in diagnosing or forecasting outcomes in patients with bone metastasis. Six studies were specific for spine metastasis. The study involved nuclear medicine (44.1%), clinical research (28.8%), radiology (20.4%), or molecular biology (6.8%). When a primary tumor was reported, prostate cancer was the most common, followed by lung, breast, and kidney. Appropriately trained AI models may be very useful in merging information to achieve an overall improved diagnostic accuracy and treatment for metastasis in the bone. Nevertheless, there are still concerns with the use of AI systems in medical settings. Ethical considerations and legal issues must be addressed to facilitate the safe and regulated adoption of AI technologies. The limitations of the study comprise a stronger emphasis on early detection rather than tumor management and prognosis as well as a high heterogeneity for type of tumor, AI technology and radiological techniques, pathology, or laboratory samples involved.

Enhancing precision in bone metastasis diagnosis for lobular breast cancer: reassessing the role of 18 F-FDG PET/CT.

Detection of osseous metastases by imaging can be challenging in patients with invasive lobular breast cancer (ILC). ILC may demonstrate low metabolic rate due to lower tumor cell density, decreased proliferation rate, diffuse infiltration of surrounding tissue, and low level of GLUT-1 expression. The aim of this study is to assess the diagnostic accuracy of 18 F-FDG PET/CT in identifying bone metastases in ILC patients. Out of 52 individuals diagnosed with lobular breast cancer and underwent 18 F-FDG PET/CT for evaluation of metastases, 21 patients were included in our study population after applying inclusion and exclusion criteria. The radiological and clinical follow-up of at least 6 months served as the reference standard comparator. Bone metastases were confirmed in six patients. 18 F-FDG PET/CT was true positive in two and false negative in four patients. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of 18 F-FDG PET/CT were 33.33, 93.33, 66.67, 77.78, and 76.19%, respectively (95% confidence interval). The tendency of ILC osseous metastases to be more sclerotic explains the low diagnostic accuracy of 18 F-FDG PET/CT in detection of bone metastases, making it a less suited method of evaluation. The results of the present study indicate that 18 F-FDG PET/CT has a low diagnostic accuracy in detecting bone metastases in lobular breast cancer and, by inference, new functional modalities can be explored in these patients. The findings contribute valuable insights to optimize the integration of molecular imaging into the diagnostic algorithm for this specific breast cancer subtype.

Clinical characteristics and prognosis analysis of gastric cancer patients with bone metastasis

Objectives: To investigate the clinical characteristics and prognosis of bone metastasis of gastric cancer, analyze the influencing factors of bone metastasis and the effects of different treatment methods, and provide a basis for early detection and treatment optimization of bone metastasis of gastric cancer. Methods: A total of 142 gastric cancer patients with bone metastasis admitted to the First Hospital of Lanzhou University from January 2011 to December 2021 were enrolled, including 60 cases of simple bone metastasis and 82 cases of bone metastasis combined with extraosseous metastasis. 142 patients with stage Ⅲgastric cancer without distant metastasis and 142 gastric cancer patients with visceral metastasis admitted to this hospital during the same period were also enrolled for comparison. Logistic regression analysis was used to determine the influencing factors of bone metastasis, and the Cox proportional hazards regression model was used to evaluate the influencing factors of overall survival (OS) of patients with bone metastasis. Results: Among the 142 patients with bone metastasis, poorly differentiated adenocarcinoma was the main type (123 cases), and 45 patients had simultaneous bone metastasis. Rib metastasis (100 cases), spine metastasis (88 cases), and pelvis metastasis (84 cases) were more common. A total of 110 patients had multiple bone metastasis, and 82 patients had extraosseous metastasis. Results of the stage Ⅲ gastric cancer group, the visceral metastasis group, the bone metastasis group, and the bone metastasis with extraosseous metastasis group were compared. There were significant differences in age, degree of differentiation, Borrmann type, alkaline phosphatase, lactate dehydrogenase, serum calcium, alanine aminotransferase, aspartate aminotransferase, creatine kinase isoenzyme, lymphocyte, hemoglobin, platelet, CEA, CA19-9, and CA724 (all P<0.05). Multivariate logistic regression analysis showed that Borrmann type was an independent protective factor of bone metastasis of gastric cancer (type 3: OR=0.07, 95%CI: 0.01-0.64, P=0.018). Alkaline phosphatase (OR=2.54, 95% CI: 1.07-6.01, P=0.034), serum calcium (OR=2.71, 95% CI: 1.15-6.41, P=0.023), creatine kinase isoenzyme (OR=16.33, 95% CI: 1.83-145.58, P=0.012), platelet (OR=10.08, 95% CI:1.89-53.85, P=0.007), and CA19-9 (OR=2.40, 95% CI: 1.14-5.05, P=0.021) were independent risk factors of bone metastasis of gastric cancer. The median OS of the stage Ⅲ gastric cancer group, the visceral metastasis group, the bone metastasis group, and the bone metastasis with extrabony group were 47, 13, 18, and 6 months, respectively, and the difference was statistically significant (P<0.001). The median OS of patients with bone metastasis only who underwent primary tumor surgery was 33 months, better than 6 months of patients without surgery (P=0.048). Multivariate Cox regression analysis showed that extraosseous metastasis (HR=2.45, 95% CI: 1.56-3.85, P<0.001) and decreased hemoglobin (HR=1.54, 95%CI: 1.02-2.34, P=0.042) were independent risk factors of OS of gastric cancer patients with bone metastasis. Conclusions: The prognosis of gastric cancer patients with bone metastasis alone is significantly better than that of other stage Ⅳ patients. For such patients, surgery on the primary site combined with chemotherapy after full evaluation may prolong the survival time.

Abstract PO5-05-13: Clinical utility of whole body low dose computed tomography for detecting bone metastasis in breast cancer patients: A cross sectional study

Abstract Clinical utility of Whole Body Low Dose CT scan for detecting bone metastasis in Breast cancer patients: A cross sectional study Background: Skeletal scintigraphy (Bone scan) is the imaging of choice to detect bone metastasis in locally advanced and metastatic breast cancer patients. Nuclear medicine facilities are however limited in their availability. As an alternative diagnostic modality to bone scan, we studied the diagnostic capability of Whole-Body Low Dose CT (WBLDCT) scan for detection of bone metastasis in these patients. Materials and Method: This cross-sectional study was conducted from November 2021 to May 2023 at a tertiary healthcare center in India with an aim to study the clinical applicability of whole-body low dose computed tomography scan for detecting bone metastasis in patients with breast cancer. Breast cancer patients with primary tumor measuring 5cm or more, pathologically proven axillary lymph node metastasis, Stage III/IV disease, symptoms attributable to metastasis and suspected disease recurrence were included. All patients underwent WBLDCT and Bone scan within a period of about 2 weeks. WBLDCT was done during the same time as conventional dose CT scan was being done as part of metastatic workup. WBLDCT acquisition protocol was set in CT scan machine by modulating the technical parameters like Care dose 4D-automated, Care kV semi, rotation time &amp; noise index. The image analysis was performed by Radiologist and Nuclear medicine experts in a blinded fashion. Data was recorded in MS Excel sheet. Sensitivity, specificity, positive and negative predicative value, and concordance rates were calculated using SPSS software ver 25.0. Agreement amongst WBLDCT and Bone scan was calculated using Inter-rater agreement. p value &amp;lt; 0.05 was taken as significant. Results: 110 patients were enrolled in this study. The mean age of participants was 48.5 years and three fourth had stage III disease at presentation. Estrogen receptor positive disease was seen in 43.64% participants while 30% were triple negative. Her2neu positive disease was seen in 27.27% patients. Bone scan couldn’t be done in 03 patients who deferred treatment (these had no bone metastasis on WBLDCT). Both bone scan and WBLDCT detected bone metastasis in 19 patients. Bone scan picked up additional metastasis in three patients which were missed on WBLDCT. WBLDCT detected bone metastasis additionally in three patients which were not detected on Bone scan. Multiple lesions were most seen in vertebrae in 38.5% and 28.6% on bone scan and WBLDCT respectively. The sensitivity and specificity of WBLDCT for detection of bone metastasis was 86.36% and 96.47% respectively. The concordance rate between Bone scan and WBLDCT scan was 94.39% with an Inter-rater Kappa(k) quotient for agreement of 0.828 (p&amp;lt; 0.0001). Conclusion: WBLDCT scan has comparable diagnostic capability to skeletal scintigraphy in detecting bone metastasis in breast cancer and may be a useful alternative specially in resource limited settings. Table 1: Sensitivity, specificity, positive predictive value and negative predictive value of WBLDCT for detection of metastasis Variables Values Sensitivity (95% CI) 86.36% Specificity (95% CI) 96.47% AUC (95% CI) 0.91 Positive Predictive Value (95% CI) 86.36% Negative Predictive Value (95% CI) 96.47% Diagnostic accuracy 94.39% Inter-rater agreement (kappa) 0.828 Citation Format: Lipton Mitra, Suhani Suhani, Ankur Goyal, Rakesh Kumar, Mohit Joshi, Hemanga Bhattacharjee, Haresh KP, Raju Sharma, Rajinder Parshad. Clinical utility of whole body low dose computed tomography for detecting bone metastasis in breast cancer patients: A cross sectional study [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-05-13.

Development and validation of an early diagnosis model for bone metastasis in non-small cell lung cancer based on serological characteristics of the bone metastasis mechanism

Bone metastasis significantly impact the prognosis of non-small cell lung cancer (NSCLC) patients, reducing their quality of life and shortening their survival. Currently, there are no effective tools for the diagnosis and risk assessment of early bone metastasis in NSCLC patients. This study employed machine learning to analyze serum indicators that are closely associated with bone metastasis, aiming to construct a model for the timely detection and prognostic evaluation of bone metastasis in NSCLC patients. The derivation cohort consisted of 664 individuals with stage IV NSCLC, diagnosed between 2015 and 2018. The variables considered in this study included age, sex, and 18 specific serum indicators that have been linked to the occurrence of bone metastasis in NSCLC. Variable selection used multivariate logistic regression analysis and Lasso regression analysis. Six machine learning methods were utilized to develop a bone metastasis diagnostic model, assessed with Area Under the Curve (AUC), Decision Curve Analysis (DCA), sensitivity, specificity, and validation cohorts. External validation used 113 NSCLC patients from the Medical Alliance (2019-2020). Furthermore, a prospective validation study was conducted on a cohort of 316 patients (2019-2020) who were devoid of bone metastasis, and followed-up for at least two years to assess the predictive capabilities of this model. The model's prognostic value was evaluated using Kaplan-Meier survival curves. Through variable selection, 11 serum indictors were identified as independent predictive factors for NSCLC bone metastasis. Six machine learning models were developed using age, sex, and these serum indicators. A random forest (RF) model demonstrated strong performance during the training and internal validation cohorts, achieving an AUC of 0.98 (95% CI 0.95-0.99) for internal validation. External validation further confirmed the RF model's effectiveness, yielding an AUC of 0.97 (95% CI 0.94-0.99). The calibration curves demonstrated a high level of concordance between the anticipated risk and the observed risk of the RF model. Prospective validation revealed that the RF model could predict the occurrence of bone metastasis approximately 10.27±3.58 months in advance, according to the results of the SPECT. An online computing platform (https://bonemetastasis.shinyapps.io/shiny_cls_1model/) for this RF model is publicly available and free-to-use by doctors and patients. This study innovatively employs age, gender, and 11 serological markers closely related to the mechanism of bone metastasis to construct an RF model, providing a reliable tool for the early screening and prognostic assessment of bone metastasis in NSCLC patients. However, as an exploratory study, the findings require further validation through large-scale, multicenter prospective studies. This work is supported by the National Natural Science Foundation of China (NO.81974315); Shanghai Municipal Science and Technology Commission Medical Innovation Research Project (NO.20Y11903300); Shanghai Municipal Health Commission Health Industry Clinical Research Youth Program (NO.20204Y034).

Moving Beyond Isothiocyanates: A Look at the Stability of Conjugation Links Toward Radiolysis in 89Zr-Labeled Immunoconjugates.

Zirconium-89 is the most widely used radioisotope for immunoPET because its physical half-life (78.2 h) suits the one of antibodies. Desferrioxamine B (DFO) is the standard chelator for the complexation of zirconium(IV), and its bifunctional version, containing a phenylisothiocyanate function, is the most commonly used for the conjugation of DFO to proteins. However, preliminary results have shown that the thiourea link obtained from the conjugation of isothiocyanate and lysines is sensitive to the ionizing radiation generated by the radioisotope, leading to the rupture of the link and the release of the chelator/radiometal complex. This radiolysis phenomenon could produce nonspecific signal and prevent the detection of bone metastasis, as free zirconium accumulates into the bones. The aim of this work was to study the stability of a selection of conjugation linkers in 89Zr-labeled immunoconjugates. We have synthesized several DFO-based bifunctional chelators appended with an isothiocyanate moiety, a bicyclononyne, or a squaramate ester. Two antibodies (trastuzumab and rituximab) were conjugated and radiolabeled with zirconium-89. The effect of increasing activities of zirconium-89 on the integrity of the bioconjugate bearing thiourea links was evaluated as well as the impact of the presence of a radioprotectant. The stability of the radiolabeled antibodies was studied over 7 days in PBS and human plasma. Radioconjugates' integrity was evaluated using iTLC and size-exclusion chromatography. This study shows that the nature of the linker between the chelator and biomolecule can have a strong impact on the stability of the 89Zr-labeled conjugates, as well as on the aggregation of the conjugates.

Can 18F-FES PET Improve the Evaluation of 18F-FDG PET in Patients With Metastatic Invasive Lobular Carcinoma?

Invasive lobular carcinoma (ILC) exhibits a low affinity for 18F-FDG. The estrogen receptor (ER) is commonly expressed in ILCs, suggesting a potential benefit of targeting with the ER probe 18F-FES in this patient population. The objective of this study was to evaluate the diagnostic performance of 18F-FES imaging in patients with metastatic ILC and compare it with that of 18F-FDG. We conducted a retrospective analysis of 20 ILC patients who underwent concurrent 18F-FES and 18F-FDG PET/CT examinations in our center. 18F-FES and 18F-FDG imaging were analyzed to determine the total count of tracer-avid lesions in nonbone sites and their corresponding organ systems, assess the extent of anatomical regions involved in bone metastases, and measure the SUVmax values for both tracers. Among 20 ILC patients, 65 nonbone lesions were found to be distributed in 13 patients, and 16 patients were diagnosed with bone metastasis, which was distributed in 54 skeletal anatomical regions. The detection rate of 18F-FDG in nonbone lesions was higher than that of 18F-FES (57 vs 37, P < 0.001). 18F-FES demonstrated a superior ability to detect nonbone lesions in 4 patients, whereas 18F-FDG was superior in 5 patients (P > 0.05). Among 9/16 patients with bone metastasis, 18F-FES demonstrated a significant advantage in the detection of bone lesions compared with 18F-FDG (P = 0.05). Furthermore, patients with only 18F-FES-positive lesions (12/12) were administered endocrine regimens, whereas patients lacking 18F-FES uptake (2/3) predominantly received chemotherapy. 18F-FES is more effective than 18F-FDG in detecting bone metastasis in ILC, but it does not demonstrate a significant advantage in nonbone lesions. Additionally, the results of examination with 18F-FES have the potential to guide patient treatment plans.

Comparison of the relative diagnostic performance of 68Ga-DOTA-IBA and 18F-NaF for the detection of bone metastasis.

We aimed to compare the relative diagnostic efficacy of 68Ga-Labeled DOTA-ibandronic acid (68Ga-DOTA-IBA) to that of18F-NaF PET/CT as a mean of detecting bone metastases in patients with a range of cancer types. This study retrospectively enrolled patients with bone metastases associated with various underlying malignancies. All patients underwent both 68Ga-DOTA-IBA and 18F-NaF PET/CT scans. Histopathology and follow-up CT or MRI imaging results were used as reference criteria, with a minimum follow-up period of 3 months. The maximum Standardized Uptake Value (SUVmax) and number of bone metastases were recorded. The Target-Background Ratio (TBR) was calculated along with the detection rate, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of 68Ga-DOTA-IBA and 18F-NaF PET/CT imaging for overall and partial primary solid tumor bone metastases. Pearson chi-square test, McNemar test, and Kappa test was conducted to assess the correlation and consistency of diagnostic efficiency between the two imaging agents. Receiver Operating Characteristic curve (ROC curve) was performed to compare diagnostic performance and the area under the curve of the two imaging agents, determining optimal critical values for SUVmax and TBR in diagnosing bone metastasis. Differences in SUVmax and TBR values between the two imaging agents for detecting bone metastases were analyzed using the Wilcoxon signed rank test. The difference was statistically significant when P < 0.05. A total of 24 patients (13 women and 11 men) were included in this study, with a mean age of 52 (interquartile range, 49-64 years). The detection rate, sensitivity, specificity, PPV, NPV, accuracy, and AUC of 68Ga-DOTA-IBA and 18F-NaF PET/CT for bone metastases were 81%, 90%, 62%, 95%, 43%, 88%, 0.763, and 89%, 99%, 59%, 95%, 89%, 95%, 0.789, respectively. There was no significant difference between the two imaging methods (P < 0.01), and there was a significant correlation (X2=168.43, P < 0.001) and a strong consistency (Kappa=0.774,P < 0.001) between the diagnostic results of the two imaging agents. The SUVmax values of lesions measured by 68Ga-DOTA-IBA and 18F-NaF imaging in 22 patients with bone metastasis were 5.1 ± 5.4 and 19.6 ± 15.1, respectively, with statistically significant differences (P<0.05). The TBR values of the two imaging methods were 5.0 ± 5.0 and 6.7 ± 6.4, respectively, with statistically significant differences (P<0.05). The AUC of the SUVmax of 68Ga-DOTA-IBA and 18F-NaF curves were 0.824 and 0.862, respectively, with no statistically significant difference (P=0.490). No significant difference was found in the AUC of the TBR of 68Ga-DOTA-IBA and 18F-NaF (0.832 vs 0.890; P=0.248). Subgroup analysis showed significant correlation between the two imaging agents in the diagnosis of bone metastases in lung cancer and breast cancer, with consistent diagnostic results. However, in the diagnosis of bone metastases in prostate cancer, there was a significant difference (P<0.001) and lack of consistency (P=0.109). The diagnostic efficacy of 68Ga-DOTA-IBA for bone metastasis lesions is comparable to that of 18F-NaF. This finding holds significant clinical importance in terms of diagnosis of bone metastasis and selecting treatment plans for patients with malignant tumors.

Theranostic Agent Targeting Bone Metastasis: A Novel [68Ga]Ga/[177Lu]Lu-DOTA-HBED-bisphosphonate.

Bone metastasis in cancer patients is a major disease advancement for various types of cancer. Previously, [68Ga]Ga-HBED-CC-bisphosphonate ([68Ga]Ga-P15-041) showed excellent bone uptake and efficient detection of bone metastasis in patients. To accommodate different α- or β--emitting metals for radionuclide therapy, a novel DOTA-HBED-CC-bisphosphonate (P15-073, 1) was prepared and the corresponding [68Ga]Ga-1 and [177Lu]Lu-1 were successfully synthesized in high yields and purity. Gallium-68 conjugation to HBED-CC at room temperature and lutetium-177 conjugation to DOTA at 95 °C were verified in model compounds through secondary mass confirmation. These bisphosphonates, [68Ga]Ga-1 and [177Lu]Lu-1, displayed high binding affinity to hydroxyapatite in vitro. After an iv injection, it showed excellent uptake in the spine of normal mice, and micro-PET/CT imaging of nude mice model of bone metastasis showed high bone uptake in tumor tissue. The results indicated that [68Ga]Ga/[177Lu]Lu-1 holds promise as a theranostic radioligand agent for managing cancer bone metastases.

Comparison of ex vivo bioluminescence imaging, Alu-qPCR and histology for the quantification of spontaneous lung and bone metastases in subcutaneous xenograft mouse models

Bioluminescence imaging (BLI) is a non-invasive state-of-the-art-method for longitudinal tracking of tumor cells in mice. The technique is commonly used to determine bone metastatic burden in vivo and also suitable ex vivo to detect even smallest bone micro-metastases in spontaneous metastasis xenograft models. However, it is unclear to which extent ex vivo BLI correlates with alternative methods for metastasis quantification. Here, we compared ex vivo BLI, human DNA-based Alu-qPCR, and histology for the quantification of bone vs. lung metastases, which are amongst the most common sites of metastasis in prostate cancer (PCa) patients and spontaneous PCa xenograft models. Data from 93 immunodeficient mice were considered, each of which were subcutaneously injected with luciferase/RGB-labeled human PCa PC-3 cells. The primary tumors were resected at ~ 0.75 cm³ and mice were sacrificed ~ 3 weeks after surgery and immediately examined by ex vivo BLI. Afterwards, the right lungs and hind limbs with the higher BLI signal (BLIHi bone) were processed for histology, whereas the left lung lobes and hind limbs with the lower BLI signal (BLILo bone) were prepared for Alu-qPCR. Our data demonstrate remarkable differences in the correlation coefficients of the different methods for lung metastasis detection (r ~ 0.8) vs. bone metastasis detection (r ~ 0.4). However, the BLI values of the BLIHi and BLILo bones correlated very strongly (r ~ 0.9), indicating that the method per se was reliable under identical limitations; the overall level of metastasis to contralateral bones was astonishingly similar. Instead, the level of lung metastasis only weakly to moderately correlated with the level of bone metastasis formation. Summarized, we observed a considerable discrepancy between ex vivo BLI and histology/Alu-qPCR in the quantification of bone metastases, which was not observed in the case of lung metastases. Future studies using ex vivo BLI for bone metastasis quantification should combine multiple methods to accurately determine metastatic load in bone samples.

Verification of image quality improvement of low-count bone scintigraphy using deep learning.

To improve image quality for low-count bone scintigraphy using deep learning and evaluate their clinical applicability. Six hundred patients (training, 500; validation, 50; evaluation, 50) were included in this study. Low-count original images (75%, 50%, 25%, 10%, and 5% counts) were generated from reference images (100% counts) using Poisson resampling. Output (DL-filtered) images were obtained after training with U-Net using reference images as teacher data. Gaussian-filtered images were generated for comparison. Peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) to the reference image were calculated to determine image quality. Artificial neural network (ANN) value, bone scan index (BSI), and number of hotspots (Hs) were computed using BONENAVI analysis to assess diagnostic performance. Accuracy of bone metastasis detection and area under the curve (AUC) were calculated. PSNR and SSIM for DL-filtered images were highest in all count percentages. BONENAVI analysis values for DL-filtered images did not differ significantly, regardless of the presence or absence of bone metastases. BONENAVI analysis values for original and Gaussian-filtered images differed significantly at ≦25% counts in patients without bone metastases. In patients with bone metastases, BSI and Hs for original and Gaussian-filtered images differed significantly at ≦10% counts, whereas ANN values did not. The accuracy of bone metastasis detection was highest for DL-filtered images in all count percentages; the AUC did not differ significantly. The deep learning method improved image quality and bone metastasis detection accuracy for low-count bone scintigraphy, suggesting its clinical applicability.