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- Garpered, Sabine, et al.
(författare)
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Evaluation of 18F-FDG uptake in lung parenchyma compensating for tissue fraction : Comparison between non-enhanced low dose CT and intravenous contrast-enhanced diagnostic CT
- 2020
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Ingår i: Nuklearmedizin. - : Georg Thieme Verlag KG. - 0029-5566 .- 2567-6407. ; 59:1, s. 20-25
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Tidskriftsartikel (refereegranskat)abstract
- AIM: To determine how the presence of intravenous (IV) contrast-enhanced CT influences SUV measurements corrected for both attenuation and tissue fraction. MATERIAL AND METHODS: Eighteen patients with different malignancies, free from lung disorders, lung cancer or metastasis, were prospectively recruited when referred for staging with combined 18F-FDG-PET/CT examination. A non-enhanced low-dose CT over the chest was immediately followed by a whole-body IV contrast-enhanced diagnostic CT and finally the PET acquisition. PET data were reconstructed with attenuation correction based on the two CT data sets. The lungs were segmented in the CT images and lung density was measured. Uptake of 18F-FDG in lung parenchyma was recorded using both non-enhanced and IV contrast-enhanced CT as well as with and without compensation for lung aeration. A comparison of SUV values of corrected and uncorrected PET images was performed. RESULTS: There was no significant difference between low dose PET/CT and IV contrast-enhanced PET/CT when removing the impact of air fraction (p = 0.093 for the right lung and p = 0.085 for the left lung). When tissue fraction was not corrected for, there was a significant difference between low dose PET/CT and IV contrast enhanced PET/CT used for attenuation correction (p = 0.006 for the right lung and p = 0.015 for the left lung). CONCLUSION: There was only a marginal effect on the assessement of SUV in the lung tissue when using IV contrast enhanced CT for attenuation correction when the air fraction was accounted for.
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| 3. |
- Trägårdh, Elin, et al.
(författare)
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Freely available artificial intelligence for pelvic lymph node metastases in PSMA PET-CT that performs on par with nuclear medicine physicians
- 2022
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Ingår i: European Journal of Nuclear Medicine and Molecular Imaging. - : Springer Science and Business Media LLC. - 1619-7070 .- 1619-7089. ; 49, s. 3412-3418
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Tidskriftsartikel (refereegranskat)abstract
- Purpose The aim of this study was to develop and validate an artificial intelligence (AI)-based method using convolutional neural networks (CNNs) for the detection of pelvic lymph node metastases in scans obtained using [F-18]PSMA-1007 positron emission tomography-computed tomography (PET-CT) from patients with high-risk prostate cancer. The second goal was to make the AI-based method available to other researchers. Methods [F-18]PSMA PET-CT scans were collected from 211 patients. Suspected pelvic lymph node metastases were marked by three independent readers. A CNN was developed and trained on a training and validation group of 161 of the patients. The performance of the AI method and the inter-observer agreement between the three readers were assessed in a separate test group of 50 patients. Results The sensitivity of the AI method for detecting pelvic lymph node metastases was 82%, and the corresponding sensitivity for the human readers was 77% on average. The average number of false positives was 1.8 per patient. A total of 5-17 false negative lesions in the whole cohort were found, depending on which reader was used as a reference. The method is available for researchers at www.recomia.org. Conclusion This study shows that AI can obtain a sensitivity on par with that of physicians with a reasonable number of false positives. The difficulty in achieving high inter-observer sensitivity emphasizes the need for automated methods. On the road to qualifying AI tools for clinical use, independent validation is critical and allows performance to be assessed in studies from different hospitals. Therefore, we have made our AI tool freely available to other researchers.
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| 4. |
- Trägårdh, Elin, et al.
(författare)
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Freely Available, Fully Automated AI-Based Analysis of Primary Tumour and Metastases of Prostate Cancer in Whole-Body [F-18]-PSMA-1007 PET-CT
- 2022
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Ingår i: Diagnostics. - : MDPI AG. - 2075-4418. ; 12:9
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Tidskriftsartikel (refereegranskat)abstract
- Here, we aimed to develop and validate a fully automated artificial intelligence (AI)-based method for the detection and quantification of suspected prostate tumour/local recurrence, lymph node metastases, and bone metastases from [F-18]PSMA-1007 positron emission tomography-computed tomography (PET-CT) images. Images from 660 patients were included. Segmentations by one expert reader were ground truth. A convolutional neural network (CNN) was developed and trained on a training set, and the performance was tested on a separate test set of 120 patients. The AI method was compared with manual segmentations performed by several nuclear medicine physicians. Assessment of tumour burden (total lesion volume (TLV) and total lesion uptake (TLU)) was performed. The sensitivity of the AI method was, on average, 79% for detecting prostate tumour/recurrence, 79% for lymph node metastases, and 62% for bone metastases. On average, nuclear medicine physicians' corresponding sensitivities were 78%, 78%, and 59%, respectively. The correlations of TLV and TLU between AI and nuclear medicine physicians were all statistically significant and ranged from R = 0.53 to R = 0.83. In conclusion, the development of an AI-based method for prostate cancer detection with sensitivity on par with nuclear medicine physicians was possible. The developed AI tool is freely available for researchers.
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| 5. |
- Valind, Kristian, et al.
(författare)
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[18F]PSMA-1007 PET is comparable to [99mTc]Tc-DMSA SPECT for renal cortical imaging.
- 2023
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Ingår i: European journal of hybrid imaging. - 2510-3636. ; 7:1
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Scintigraphy using technetium-99m labelled dimercaptosuccinic acid ([99mTc]Tc-DMSA), taken up in the proximal tubules, is the standard in functional imaging of the renal cortex. Recent guidelines recommend performing [99mTc]Tc-DMSA scintigraphy with single photon emission computed tomography (SPECT). Prostate-specific membrane antigen (PSMA) targeted positron emission tomography (PET) is used for staging and localization of recurrence in prostate cancer. A high renal uptake is often seen on PSMA PET, concordant with known PSMA expression in proximal tubules. This suggests PSMA PET could be used analogous to [99mTc]Tc-DMSA scintigraphy for renal cortical imaging. [18F]PSMA-1007 is a promising radiopharmaceutical for this purpose due to low urinary clearance. In this study, we aimed to compare [18F]PSMA-1007 PET to [99mTc]Tc-DMSA SPECT regarding split renal uptake and presence of renal uptake defects, in patients with prostate cancer. Three readers interpreted PET and SPECT images regarding presence of renal uptake defects, with each kidney split into cranial, mid and caudal segments. Kidneys were segmented in PET and SPECT images, and left renal uptake as a percentage of total renal uptake was measured. RESULTS: Twenty patients with prostate cancer were included. 2 participants had single kidneys; thus 38 kidneys were evaluated. A total of 29 defects were found on both [99mTc]Tc-DMSA SPECT and [18F]PSMA-1007 PET. Cohen's kappa for concordance regarding presence of any defect was 0.76 on a per-segment basis and 0.67 on a per-kidney basis. Spearman's r for left renal uptake percentage between [99mTc]Tc-DMSA SPECT and [18F]PSMA-1007 PET was 0.95. CONCLUSIONS: [18F]PSMA-1007 PET is comparable to [99mTc]Tc-DMSA SPECT for detection of uptake defects in this setting. Measurements of split renal function made using [18F]PSMA-1007 PET are valid and strongly correlated to measurements made with [99mTc]Tc-DMSA SPECT.
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