| 1. |
- Saito, Shintaro, et al.
(författare)
-
Convolutional neural network-based automatic heart segmentation and quantitation in 123 I-metaiodobenzylguanidine SPECT imaging
- 2021
-
Ingår i: EJNMMI Research. - : Springer Science and Business Media LLC. - 2191-219X. ; 11:1
-
Tidskriftsartikel (refereegranskat)abstract
- Background: Since three-dimensional segmentation of cardiac region in 123I-metaiodobenzylguanidine (MIBG) study has not been established, this study aimed to achieve organ segmentation using a convolutional neural network (CNN) with 123I-MIBG single photon emission computed tomography (SPECT) imaging, to calculate heart counts and washout rates (WR) automatically and to compare with conventional quantitation based on planar imaging. Methods: We assessed 48 patients (aged 68.4 ± 11.7 years) with heart and neurological diseases, including chronic heart failure, dementia with Lewy bodies, and Parkinson's disease. All patients were assessed by early and late 123I-MIBG planar and SPECT imaging. The CNN was initially trained to individually segment the lungs and liver on early and late SPECT images. The segmentation masks were aligned, and then, the CNN was trained to directly segment the heart, and all models were evaluated using fourfold cross-validation. The CNN-based average heart counts and WR were calculated and compared with those determined using planar parameters. The CNN-based SPECT and conventional planar heart counts were corrected by physical time decay, injected dose of 123I-MIBG, and body weight. We also divided WR into normal and abnormal groups from linear regression lines determined by the relationship between planar WR and CNN-based WR and then analyzed agreement between them. Results: The CNN segmented the cardiac region in patients with normal and reduced uptake. The CNN-based SPECT heart counts significantly correlated with conventional planar heart counts with and without background correction and a planar heart-to-mediastinum ratio (R2 = 0.862, 0.827, and 0.729, p < 0.0001, respectively). The CNN-based and planar WRs also correlated with and without background correction and WR based on heart-to-mediastinum ratios of R2 = 0.584, 0.568 and 0.507, respectively (p < 0.0001). Contingency table findings of high and low WR (cutoffs: 34% and 30% for planar and SPECT studies, respectively) showed 87.2% agreement between CNN-based and planar methods. Conclusions: The CNN could create segmentation from SPECT images, and average heart counts and WR were reliably calculated three-dimensionally, which might be a novel approach to quantifying SPECT images of innervation.
|
|
| 2. |
- Cheng, Qing, et al.
(författare)
-
Preclinical PET imaging of EGFR levels : pairing a targeting with a non-targeting Sel-tagged Affibody-based tracer to estimate the specific uptake
- 2016
-
Ingår i: EJNMMI Research. - : Springer. - 2191-219X. ; 6
-
Tidskriftsartikel (refereegranskat)abstract
- Background: Though overexpression of epidermal growth factor receptor (EGFR) in several forms of cancer is considered to be an important prognostic biomarker related to poor prognosis, clear correlations between biomarker assays and patient management have been difficult to establish. Here, we utilize a targeting directly followed by a non-targeting tracer-based positron emission tomography (PET) method to examine some of the aspects of determining specific EGFR binding in tumors. Methods: The EGFR-binding Affibody molecule Z(EGFR:2377) and its size-matched non-binding control Z(Taq:3638) were recombinantly fused with a C-terminal selenocysteine-containing Sel-tag (Z(EGFR:2377)-ST and Z(Taq:3638)-ST). The proteins were site-specifically labeled with DyLight488 for flow cytometry and ex vivo tissue analyses or with C-11 for in vivo PET studies. Kinetic scans with the C-11-labeled proteins were performed in healthy mice and in mice bearing xenografts from human FaDu (squamous cell carcinoma) and A431 (epidermoid carcinoma) cell lines. Changes in tracer uptake in A431 xenografts over time were also monitored, followed by ex vivo proximity ligation assays (PLA) of EGFR expressions. Results: Flow cytometry and ex vivo tissue analyses confirmed EGFR targeting by ZE(GFR:2377)-ST-DyLight488. [Methyl-C-11]-labeled Z(EGFR:2377)-ST-CH3 and Z(Taq:3638)-ST-CH3 showed similar distributions in vivo, except for notably higher concentrations of the former in particularly the liver and the blood. [Methyl-C-11]-Z(EGFR:2377)-ST-CH3 successfully visualized FaDu and A431 xenografts with moderate and high EGFR expression levels, respectively. However, in FaDu tumors, the non-specific uptake was large and sometimes equally large, illustrating the importance of proper controls. In the A431 group observed longitudinally, non-specific uptake remained at same level over the observation period. Specific uptake increased with tumor size, but changes varied widely over time in individual tumors. Total (membranous and cytoplasmic) EGFR in excised sections increased with tumor growth. There was no positive correlation between total EGFR and specific tracer uptake, which, since Z(EGFR:2377) binds extracellularly and is slowly internalized, indicates a discordance between available membranous and total EGFR expression levels. Conclusions: Same-day in vivo dual tracer imaging enabled by the Sel-tag technology and C-11-labeling provides a method to non-invasively monitor membrane-localized EGFR as well as factors affecting non-specific uptake of the PET ligand.
|
|
| 3. |
- Lindgren Belal, Sarah, et al.
(författare)
-
3D skeletal uptake of F-18 sodium fluoride in PET/CT images is associated with overall survival in patients with prostate cancer
- 2017
-
Ingår i: EJNMMI Research. - : Springer Science and Business Media LLC. - 2191-219X. ; 7:1
-
Tidskriftsartikel (refereegranskat)abstract
- Background: Sodium fluoride (NaF) positron emission tomography combined with computer tomography (PET/CT) has shown to be more sensitive than the whole-body bone scan in the detection of skeletal uptake due to metastases in prostate cancer. We aimed to calculate a 3D index for NaF PET/CT and investigate its correlation to the bone scan index (BSI) and overall survival (OS) in a group of patients with prostate cancer. Methods: NaF PET/CT and bone scans were studied in 48 patients with prostate cancer. Automated segmentation of the thoracic and lumbar spines, sacrum, pelvis, ribs, scapulae, clavicles, and sternum were made in the CT images. Hotspots in the PET images were selected using both a manual and an automated method. The volume of each hotspot localized in the skeleton in the corresponding CT image was calculated. Two PET/CT indices, based on manual (manual PET index) and automatic segmenting using a threshold of SUV 15 (automated PET15 index), were calculated by dividing the sum of all hotspot volumes with the volume of all segmented bones. BSI values were obtained using a software for automated calculations. Results: BSI, manual PET index, and automated PET15 index were all significantly associated with OS and concordance indices were 0.68, 0.69, and 0.70, respectively. The median BSI was 0.39 and patients with a BSI > 0.39 had a significantly shorter median survival time than patients with a BSI 0.53 had a significantly shorter median survival time than patients with a manual PET index 0.11 had a significantly shorter median survival time than patients with an automated PET15 index
|
|
| 4. |
- Pemberton, Hugh G., et al.
(författare)
-
Software compatibility analysis for quantitative measures of [18F]flutemetamol amyloid PET burden in mild cognitive impairment
- 2023
-
Ingår i: EJNMMI Research. - 2191-219X. ; 13:1
-
Tidskriftsartikel (refereegranskat)abstract
- Rationale: Amyloid-β (Aβ) pathology is one of the earliest detectable brain changes in Alzheimer’s disease pathogenesis. In clinical practice, trained readers will visually categorise positron emission tomography (PET) scans as either Aβ positive or negative. However, adjunct quantitative analysis is becoming more widely available, where regulatory approved software can currently generate metrics such as standardised uptake value ratios (SUVr) and individual Z-scores. Therefore, it is of direct value to the imaging community to assess the compatibility of commercially available software packages. In this collaborative project, the compatibility of amyloid PET quantification was investigated across four regulatory approved software packages. In doing so, the intention is to increase visibility and understanding of clinically relevant quantitative methods. Methods: Composite SUVr using the pons as the reference region was generated from [18F]flutemetamol (GE Healthcare) PET in a retrospective cohort of 80 amnestic mild cognitive impairment (aMCI) patients (40 each male/female; mean age = 73 years, SD = 8.52). Based on previous autopsy validation work, an Aβ positivity threshold of ≥ 0.6 SUVrpons was applied. Quantitative results from MIM Software’s MIMneuro, Syntermed’s NeuroQ, Hermes Medical Solutions’ BRASS and GE Healthcare’s CortexID were analysed using intraclass correlation coefficient (ICC), percentage agreement around the Aβ positivity threshold and kappa scores. Results: Using an Aβ positivity threshold of ≥ 0.6 SUVrpons, 95% agreement was achieved across the four software packages. Two patients were narrowly classed as Aβ negative by one software package but positive by the others, and two patients vice versa. All kappa scores around the same Aβ positivity threshold, both combined (Fleiss’) and individual software pairings (Cohen’s), were ≥ 0.9 signifying “almost perfect” inter-rater reliability. Excellent reliability was found between composite SUVr measurements for all four software packages, with an average measure ICC of 0.97 and 95% confidence interval of 0.957–0.979. Correlation coefficient analysis between the two software packages reporting composite z-scores was strong (r 2 = 0.98). Conclusion: Using an optimised cortical mask, regulatory approved software packages provided highly correlated and reliable quantification of [18F]flutemetamol amyloid PET with a ≥ 0.6 SUVrpons positivity threshold. In particular, this work could be of interest to physicians performing routine clinical imaging rather than researchers performing more bespoke image analysis. Similar analysis is encouraged using other reference regions as well as the Centiloid scale, when it has been implemented by more software packages.
|
|
