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- Eriksson, Sophie, et al.
(författare)
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Successful radioimmunotherapy of established syngeneic rat colon carcinoma with 211At-mAb.
- 2013
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Ingår i: EJNMMI research. - 2191-219X. ; 3:1
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Most carcinomas are prone to metastasize despite successful treatment of the primary tumor. One way to address this clinical challenge may be targeted therapy with alpha-emitting radionuclides such as astatine-211 (211At). Radioimmunotherapy utilizing alpha-particle emitting radionuclides is considered especially suitable for the treatment of small cell clusters and single cells, although lesions of different sizes may also be present in the patient. The aim of this study was primarily to evaluate the toxicity and secondarily in vivo efficacy of a 211At-labeled monoclonal antibody (mAb) directed against colon carcinoma with tumor diameters of approximately 10 mm. METHODS: Eighteen rats with subperitoneal syngeneic colon carcinoma were allocated to three groups of six animals together with three healthy rats in each group. The groups were injected intravenously with either 150 mug of unlabeled mAbs (controls) or 2.5 or 5 MBq 211At-mAbs directed towards the Lewis Y antigen expressed on the cell membrane of several carcinomas. Tumor volume, body weight, and blood cell counts were monitored for 100 days after treatment. RESULTS: Local tumors were non-palpable in five out of six rats after treatment with both activities of 211At-mAbs, compared to one out of six in the control group. At the study end, half of the animals in each group given 211At-BR96 and one animal in the control group were free from disease. Radioimmunotherapy resulted in dose-dependent, transient weight loss and myelotoxicity. Survival was significantly better in the groups receiving targeted alpha therapy than in those receiving unlabeled mAbs. CONCLUSIONS: This study demonstrates the possibility of treating small, solid colon carcinoma tumors with alpha-emitting radionuclides such as 211At bound to mAbs, with tolerable toxicity.
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| 2. |
- Kaboteh, Reza, et al.
(författare)
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Bone Scan Index: a prognostic imaging biomarker for high-risk prostate cancer patients receiving primary hormonal therapy.
- 2013
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Ingår i: EJNMMI research. - 2191-219X. ; 3:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: The objective of this study was to explore the prognostic value of the Bone Scan Index (BSI) obtained at the time of diagnosis in a group of high-risk prostate cancer patients receiving primary hormonal therapy. Methods: This was a retrospective study based on 130 consecutive prostate cancer patients at high risk, based on clinical stage (T2c/T3/T4), Gleason score (8 to 10) and prostate-specific antigen (PSA) (> 20 ng/mL), who had undergone whole-body bone scans < 3 months after diagnosis and who received primary hormonal therapy. BSI was calculated using an automated method. Cox proportional-hazards regression models were used to investigate the association between clinical stage, Gleason score, PSA, BSI and survival. Discrimination between prognostic models was assessed using the concordance index (C-index). Results: In a multivariate analysis, Gleason score (p = 0.01) and BSI (p < 0.001) were associated with survival, but clinical stage (p = 0.29) and PSA (p = 0.57) were not prognostic. The C-index increased from 0.66 to 0.71 when adding BSI to a model including clinical stage, Gleason score and PSA. The 5-year probability of survival was 55% for patients without metastases, 42% for patients with BSI < 1, 31% for patients with BSI = 1 to 5, and 0% for patients with BSI > 5. Conclusions: BSI can be used as a complement to PSA to risk-stratify high-risk prostate cancer patients at the time of diagnosis. This imaging biomarker, reflecting the extent of metastatic disease, can be of value both in clinical trials and in patient management when deciding on treatment.
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| 3. |
- Kaboteh, Reza, et al.
(författare)
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Progression of bone metastases in patients with prostate cancer - automated detection of new lesions and calculation of bone scan index
- 2013
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Ingår i: EJNMMI Research. - 2191-219X. ; 3:1
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: The objective of this study was firstly to develop and evaluate an automated method for the detection of new lesions and changes in bone scan index (BSI) in serial bone scans and secondly to evaluate the prognostic value of the method in a group of patients receiving chemotherapy.METHODS: The automated method for detection of new lesions was evaluated in a group of 266 patients using the classifications by three experienced bone scan readers as a gold standard. The prognostic value of the method was assessed in a group of 31 metastatic hormone-refractory prostate cancer patients who were receiving docetaxel. Cox proportional hazards were used to investigate the association between percentage change in BSI, number of new lesions and overall survival. Kaplan-Meier estimates of the survival function were used to indicate a significant difference between patients with an increase/decrease in BSI or those with two or more new lesions or less than two new lesions.RESULTS: The automated method detected progression defined as two or more new lesions with a sensitivity of 93% and a specificity of 87%. In the treatment group, both BSI changes and the number of new metastases were significantly associated with survival. Two-year survival for patients with increasing and decreasing BSI from baseline to follow-up scans were 18% and 57% (p = 0.03), respectively. Two-year survival for patients fulfilling and not fulfilling the criterion of two or more new lesions was 35% and 38% (n.s.), respectively.CONCLUSIONS: An automated method can be used to calculate the number of new lesions and changes in BSI in serial bone scans. These imaging biomarkers contained prognostic information in a small group of patients with prostate cancer receiving chemotherapy.
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| 6. |
- Nakajima, K., et al.
(författare)
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Enhanced diagnostic accuracy for quantitative bone scan using an artificial neural network system: A Japanese multi-center database project
- 2013
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Ingår i: EJNMMI Research. - 2191-219X. ; 3:1
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Tidskriftsartikel (refereegranskat)abstract
- Background Artificial neural network (ANN)-based bone scan index (BSI), a marker of the amount of bone metastasis, has been shown to enhance diagnostic accuracy and reproducibility but is potentially affected by training databases. The aims of this study were to revise the software using a large number of Japanese databases and to validate its diagnostic accuracy compared with the original Swedish training database. Methods The BSI was calculated with EXINIbone (EB; EXINI Diagnostics) using the Swedish training database (n = 789). The software using Japanese training databases from a single institution (BONENAVI version 1, BN1, n = 904) and the revised version from nine institutions (version 2, BN2, n = 1,532) were compared. The diagnostic accuracy was validated with another 503 multi-center bone scans including patients with prostate (n = 207), breast (n = 166), and other cancer types. The ANN value (probability of abnormality) and BSI were calculated. Receiver operating characteristic (ROC) and net reclassification improvement (NRI) analyses were performed. Results The ROC analysis based on the ANN value showed significant improvement from EB to BN1 and BN2. In men (n = 296), the area under the curve (AUC) was 0.877 for EB, 0.912 for BN1 (p = not significant (ns) vs. EB) and 0.934 for BN2 (p = 0.007 vs. EB). In women (n = 207), the AUC was 0.831 for EB, 0.910 for BN1 (p = 0.016 vs. EB), and 0.932 for BN2 (p < 0.0001 vs. EB). The optimum sensitivity and specificity based on BN2 was 90% and 84% for men and 93% and 85% for women. In patients with prostate cancer, the AUC was equally high with EB, BN1, and BN2 (0.939, 0.949, and 0.957, p = ns). In patients with breast cancer, the AUC was improved from EB (0.847) to BN1 (0.910, p = ns) and BN2 (0.924, p = 0.039). The NRI using ANN between EB and BN1 was 17.7% (p = 0.0042), and that between EB and BN2 was 29.6% (p < 0.0001). With respect to BSI, the NRI analysis showed downward reclassification with total NRI of 31.9% (p < 0.0001). Conclusion In the software for calculating BSI, the multi-institutional database significantly improved identification of bone metastasis compared with the original database, indicating the importance of a sufficient number of training databases including various types of cancers. © 2013 Nakajima et al.
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| 7. |
- Norberg, Pernilla, et al.
(författare)
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Quantitative lung SPECT applied on simulated early COPD and humans with advanced COPD
- 2013
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Ingår i: EJNMMI Research. - Germany : SpringerOpen. - 2191-219X. ; 3:28
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND:Reduced ventilation in lung regions affected by chronic obstructive pulmonary disease (COPD), reflected as inhomogeneities in the single-photon emission computed tomography (SPECT) lung image, is correlated to disease advancement. An analysis method for measuring these inhomogeneities is proposed in this work. The first aim was to develop a quantitative analysis method that could discriminate between Monte Carlo simulated normal and COPD lung SPECT images. A second aim was to evaluate the ability of the present method to discriminate between human subjects with advanced COPD and healthy volunteers.METHODS:In the simulated COPD study, different activity distributions in the lungs were created to mimic the healthy lung (normal) and different levels of COPD. Gamma camera projections were Monte Carlo simulated, representing clinically acquired projections of a patient who had inhaled 125 MBq 99mTc-Technegas followed by a 10-min SPECT examination. Reconstructions were made with iterative ordered subset expectation maximisation. The coefficient of variance (CV) was calculated for small overlapping volumes covering the 3D reconstructed activity distribution. A CV threshold value (CVT) was calculated as the modal value of the CV distribution of the simulated normal. The area under the distribution curve (AUC), for CV values greater than CVT, AUC(CVT), was then calculated. Moreover, five patients with advanced emphysema and five healthy volunteers inhaled approximately 75 MBq 99mTc-Technegas immediately before the 20-min SPECT acquisition. In the human study, CVT was based on the mean CV distribution of the five healthy volunteers.RESULTS:A significant difference (p < 0.001) was found between the Monte-Carlo simulated normal and COPD lung SPECT examinations. The present method identified a total reduction of ventilation of approximately 5%, not visible to the human eye in the reconstructed image. In humans the same method clearly discriminated between the five healthy volunteers and five patients with advanced COPD (p < 0.05).CONCLUSIONS:While our results are promising, the potential of the AUC(CVT) method to detect less advanced COPD in patients needs further clinical studies.
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