WE-AB-204-01: Performance Characterization of Regularized-Reconstruction Algorithm for 90Y PET/CT Images

2015 ◽  
Vol 42 (6Part37) ◽  
pp. 3658-3659
Author(s):  
W Siman ◽  
S Kappadath ◽  
O Mawlawi
Keyword(s):  
Reconstruction Algorithm ◽  
Ct Images ◽  
Performance Characterization ◽  
Pet Ct ◽  
90Y Pet

scholarly journals Impact of the Q.Clear reconstruction algorithm on the interpretation of PET/CT images in patients with lymphoma

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Michał Wyrzykowski ◽  
Natalia Siminiak ◽  
Maciej Kaźmierczak ◽  
Marek Ruchała ◽  
Rafał Czepczyński
Keyword(s):  
Reconstruction Algorithm ◽  
Ct Images ◽  
Pet Ct

Initial Performance Characterization of a Clinical Noise–Suppressing Reconstruction Algorithm for MDCT

2011 ◽  
Vol 197 (6) ◽  
pp. 1404-1409 ◽  
Author(s):  
Peter B. Noël ◽  
Alexander A. Fingerle ◽  
Bernhard Renger ◽  
Daniela Münzel ◽  
Ernst J. Rummeny ◽  
...  
Keyword(s):  
Reconstruction Algorithm ◽  
Performance Characterization

scholarly journals Characterization of PET/CT images using texture analysis: the past, the present… any future?

2016 ◽  
Vol 44 (1) ◽  
pp. 151-165 ◽  
Author(s):  
Mathieu Hatt ◽  
Florent Tixier ◽  
Larry Pierce ◽  
Paul E. Kinahan ◽  
Catherine Cheze Le Rest ◽  
...  
Keyword(s):  
Texture Analysis ◽  
Ct Images ◽  
The Past ◽  
Pet Ct

scholarly journals Impact of Q.Clear reconstruction algorithm on the interpretation of PET/CT images in patients with lymphoma

2020 ◽  
Author(s):  
Michał Wyrzykowski ◽  
Natalia Siminiak ◽  
Maciej Kaźmierczak ◽  
Marek Ruchała ◽  
Rafał Czepczyński
Keyword(s):  
Treatment Response ◽  
Reconstruction Algorithm ◽  
Ct Images ◽  
Response To Treatment ◽  
Early Treatment Response ◽  
Pet Ct ◽  
Penalised Likelihood ◽  
Pet Reconstruction ◽  
Fdg Pet Ct ◽  
The Impact

Abstract Background. Q.Clear is a new Bayesian penalised-likelihood PET reconstruction algorithm. It has been documented that Q.Clear increases SUVmax values of different malignant lesions. Purpose. As SUVmax values are crucial for interpretation of PET/CT images in patients with lymphoma, particularly when early and final response to treatment is evaluated, aim of the study was to systematically analyze the impact of the use of Q.Clear on interpretation of PET/CT in patients with lymphoma. Methods. 280 18F-FDG PET/CT scans in patients with lymphoma performed for staging (sPET), for early treatment response (iPET), after the end of treatment (ePET) and when a lymphoma relapse was suspected (rPET) were retrospectively analyzed. Scans separately reconstructed with two algorithms: Q.Clear and OSEM were compared. Results. The lymphoma stage was concordantly diagnosed in 69/70 patients with both algorithms in sPET. Discordant assessment of Deauville score (p < 0.001) was found in 11 cases (15.7%) of 70 iPET scans and in 11 cases of 70 ePET scans. An upgrade from negative to positive scan by Q.Clear resulted in case of 3 (4.3%) iPET scans and 7 (10.0%) ePET scans that resulted in alteration of management. Results of all 70 r-PET scans were concordant. SUVmax values of the target lymphoma lesions measured with Q.Clear were higher than with OSEM in 88.8% scans. Conclusion. Although the Q.Clear algorithm may alter interpretation of PET/CT only in a small proportion of patients, we recommend to use standard OSEM reconstruction for assessment of treatment response.

Retrospective interactive rigid fusion of 18F-FDG-PET and CT

2006 ◽  
Vol 45 (02) ◽  
pp. 88-95 ◽  
Author(s):  
A. Nömayr ◽  
H. Greess ◽  
E. Fiedler ◽  
G. Platsch ◽  
B. Schuler-Thurner ◽  
...  
Keyword(s):  
Malignant Melanoma ◽  
Image Fusion ◽  
Fdg Pet ◽  
False Negative ◽  
Spiral Ct ◽  
Ct Images ◽  
Pet Ct ◽  
Malignant Lesions ◽  
Ct Data

Summary Aim: This study investigates whether interactive rigid fusion of routine PET and CT data improves localization, detection and characterization of lesions compared to separate reading. For this purpose, routine PET and CT scans of patients with metastases from malignant melanoma were used. Patients, methods: In 34 patients with histologically confirmed malignant melanoma, FDG-PET and spiral CT were performed using clinical standard protocols. For all of these patients, gold standard was available. Clinical and radiological follow-up identified 82 lesions as definitely pathological. Two board-certified nuclear medicine physicians and two board-certified radiologists analyzed PET and CT images independently from each other. For each patient up to 32 anatomical regions (24 lymph node regions, 8 extranodular regions) were systematically classified. Discordant areas were interactively analyzed in manually and rigidly registered images using a commercially available fusion tool. No side-by-side reading was performed. Results: Image fusion disclosed that the evaluation of the PET images alone led to a mislocalization in 26 of 91 focally FDG enhancing lesions. The overall sensitivities of PET, CT, and image fusion were 85, 88, and 94%, respectively; the overall specificities of PET, CT and image fusion were 98, 95 and 100%, respectively. Image fusion exhibited statistically significant higher specificity values as compared with CT. Ten definitely malignant sites were false-negative in CT, but could be detected by PET. On the other hand, twelve metastases were false-negative in PET, but could be detected by CT. These included two lesions, which had a clear correlate on the PET image when the fused images were evaluated. On the whole, registration of the PET and CT images yielded additional diagnostic information in 44% of the definitely malignant lesions. Conclusion: Retrospective image fusion of independently obtained PET and CT data is particularly valuable in exactly localizing foci of abnormal FDG uptake and improves the detection of metastases of malignant melanoma.

Deep Supervised Residual U-Net for Automatic Characterization of Lesions on 68Ga-PSMA PET/CT images

2019 ◽  
Author(s):  
Y Zhao ◽  
A Gafita ◽  
G Tetteh ◽  
L Xu ◽  
F Haupt ◽  
...  
Keyword(s):  
Ct Images ◽  
Psma Pet ◽  
Pet Ct

scholarly journals Impact of the Q.Clear reconstruction algorithm on the interpretation of PET/CT images in patients with lymphoma

2020 ◽  
Author(s):  
Michał Wyrzykowski ◽  
Natalia Siminiak ◽  
Maciej Kaźmierczak ◽  
Marek Ruchała ◽  
Rafał Czepczyński
Keyword(s):  
Treatment Response ◽  
Reconstruction Algorithm ◽  
Ct Images ◽  
Early Treatment Response ◽  
End Of Treatment ◽  
Pet Ct ◽  
Positive Scan ◽  
Pet Reconstruction ◽  
Fdg Pet Ct ◽  
The Impact

Abstract Background. Q.Clear is a new Bayesian penalized-likelihood PET reconstruction algorithm. It has been documented that Q.Clear increases the SUVmax values of different malignant lesions. Purpose. As SUVmax values are crucial for interpretation of PET/CT images in patients with lymphoma, particularly when early and final responses to treatment are evaluated. The aim of the study was to systematically analyse the impact of the use of Q.Clear on interpretation of PET/CT in patients with lymphoma.Methods. A total of 280 18F-FDG PET/CT scans in patients with lymphoma were performed for staging (sPET), for early treatment response (iPET), after the end of treatment (ePET) and when a relapse of lymphoma was suspected (rPET). Scans were separately reconstructed with two algorithms, Q.Clear and OSEM, and further compared.Results. The stage of lymphoma was concordantly diagnosed in 69/70 patients with both algorithms on sPET. Discordant assessment of the Deauville score (p<0.001) was found in 11 cases (15.7%) of 70 iPET scans and in 11 cases of 70 ePET scans. An upgrade from a negative to a positive scan by Q.Clear occurred in 3 cases (4.3%) of iPET scans and 7 cases (10.0%) of ePET. The results of all 70 r-PET scans were concordant. The SUVmax values of the target lymphoma lesions measured with Q.Clear were higher than those measured with OSEM in 88.8% of scans. Conclusion. Although the Q.Clear algorithm may alter interpretations of PET/CT in only a small proportion of patients, we recommend using standard OSEM reconstruction for the assessment of treatment response.

scholarly journals Impact of Q.Clear reconstruction algorithm on the interpretation of PET/CT images in patients with lymphoma

2020 ◽  
Author(s):  
Michał Wyrzykowski ◽  
Natalia Siminiak ◽  
Maciej Kaźmierczak ◽  
Marek Ruchała ◽  
Rafał Czepczyński
Keyword(s):  
Treatment Response ◽  
Reconstruction Algorithm ◽  
Ct Images ◽  
Response To Treatment ◽  
Early Treatment Response ◽  
Pet Ct ◽  
Positive Scan ◽  
Pet Reconstruction ◽  
Fdg Pet Ct ◽  
The Impact

Abstract Background. Q.Clear is a new Bayesian penalized-likelihood PET reconstruction algorithm. It has been documented that Q.Clear increases SUVmax values of different malignant lesions. Purpose. As SUVmax values are crucial for interpretation of PET/CT images in patients with lymphoma, particularly when early and final response to treatment is evaluated. The aim of the study was to systematically analyze the impact of the use of Q.Clear on interpretation of PET/CT in patients with lymphoma.Methods. 280 18F-FDG PET/CT scans in patients with lymphoma were performed for staging (sPET), for early treatment response (iPET), after the end of treatment (ePET) and when a relapse of the lymphoma was suspected (rPET). Scans were separately reconstructed with two algorithms: Q.Clear and OSEM and further compared.Results. The stage of lymphoma was concordantly diagnosed in 69/70 patients with both algorithms in sPET. Discordant assessment of Deauville score (p<0.001) was found in 11 cases (15.7%) of 70 iPET scans and in 11 cases of 70 ePET scans. An upgrade from negative to positive scan by Q.Clear resulted in 3 cases (4.3%) of iPET scans and 7 (10.0%) of ePET. Results of all 70 r-PET scans were concordant. SUVmax values of the target lymphoma lesions measured with Q.Clear were higher than with OSEM in 88.8% scans. Conclusion. Although the Q.Clear algorithm may alter interpretation of PET/CT only in a small proportion of patients, we recommend to use standard OSEM reconstruction for the assessment of treatment response.

scholarly journals Impact of Q.Clear reconstruction algorithm on the interpretation of PET/CT images in patients with lymphoma

2020 ◽  
Author(s):  
Michał Wyrzykowski ◽  
Natalia Siminiak ◽  
Maciej Kaźmierczak ◽  
Marek Ruchała ◽  
Rafał Czepczyński
Keyword(s):  
Treatment Response ◽  
Reconstruction Algorithm ◽  
Ct Images ◽  
Response To Treatment ◽  
Early Treatment Response ◽  
Pet Ct ◽  
Penalised Likelihood ◽  
Pet Reconstruction ◽  
Fdg Pet Ct ◽  
The Impact

Abstract Background Q.Clear is a new Bayesian penalised-likelihood PET reconstruction algorithm. It has been documented that Q.Clear increases SUVmax values of different malignant lesions. Purpose. As SUVmax values are crucial for interpretation of PET/CT images in patients with lymphoma, particularly when early and final response to treatment is evaluated, aim of the study was to systematically analyze the impact of the use of Q.Clear on interpretation of PET/CT in patients with lymphoma. Methods 280 18 F-FDG PET/CT scans in patients with lymphoma performed for staging (sPET), for early treatment response (iPET), after the end of treatment (ePET) and when a lymphoma relapse was suspected (rPET) were retrospectively analyzed. Scans separately reconstructed with two algorithms: Q.Clear and OSEM were compared. Results The lymphoma stage was concordantly diagnosed in 69/70 patients with both algorithms in sPET. Discordant assessment of Deauville score (p<0.001) was found in 11 cases (15.7%) of 70 iPET scans and in 11 cases of 70 ePET scans. An upgrade from negative to positive scan by Q.Clear resulted in case of 3 (4.3%) iPET scans and 7 (10.0%) ePET scans that resulted in alteration of management. Results of all 70 r-PET scans were concordant. SUVmax values of the target lymphoma lesions measured with Q.Clear were higher than with OSEM in 88.8% scans. Conclusion Although the Q.Clear algorithm may alter interpretation of PET/CT only in a small proportion of patients, we recommend to use standard OSEM reconstruction for assessment of treatment response.

Sign in / Sign up

Export Citation Format

Share Document