Dataset Information

A Pilot Study of Radiomics Models Combining Multi-Probe and Multi-Modality Images of ⁶⁸Ga-NOTA-PRGD2 and ¹⁸F-FDG PET/CT for Differentiating Benign and Malignant Pulmonary Space-Occupying Lesions.

ABSTRACT:

Background

This is a pilot study of radiomics based on ⁶⁸Ga-NOTA-PRGD2 [NOTA-PEG4-E[c(RGDfK)]2)] and ¹⁸F-FDG PET/CT to (i) evaluate the diagnostic efficacy of radiomics features of ⁶⁸Ga-NOTA-PRGD2 PET in the differential diagnosis of benign and malignant pulmonary space-occupying lesions and (ii) compare the diagnostic efficacy of multi-modality and multi-probe images.

Methods

We utilized a dataset of 48 patients who participated in ⁶⁸Ga-NOTA-PRGD2 PET/CT and ¹⁸F-FDG PET/CT clinical trials to extract image features and evaluate their diagnostic efficacy in the differentiation of benign and malignant lesions by the Mann-Whitney U test. After feature selection with sequential forward selection, random forest models were developed with tenfold cross-validation. The diagnostic performance of models based on different image features was visualized by receiver operating characteristic (ROC) curves and compared by permutation tests.

Results

Fourteen of the ⁶⁸Ga-NOTA-PRGD2 PET features between benign and malignant pulmonary space-occupying lesions had significant differences (P<0.05, Mann-Whitney U test). Eighteen of the ⁶⁸Ga-NOTA-PRGD2 PET features demonstrated higher AUC values than all CT features in the differential diagnosis of pulmonary lesions. The AUC value (0.908) of the three-modal feature model was significantly higher (P<0.05, permutation test) than those of the single- and dual-modal models.

Conclusion

⁶⁸Ga-NOTA-PRGD2 PET features have better diagnostic capacity than CT features for pulmonary space-occupying lesions. The combination of multi-modality and multi-probe images can improve the diagnostic efficiency of models. Our preliminary clinical hypothesis of using radiomics based on ⁶⁸Ga-NOTA-PRGD2 PET images and multimodal images as a diagnostic tool warrants further validation in a larger multicenter sample size.

SUBMITTER: Xie F

PROVIDER: S-EPMC9201288 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundFluorine-18-labeled SSAs have the potential to become the next-generation tracer in SSTR-imaging in neuroendocrine tumor (NET) patients given their logistical advantages over the current gold standard gallium-68-labeled SSAs. In particular, [18F]AlF-OC has already shown excellent clinical performance. We demonstrated in our previous report from our prospective multicenter trial that [18F]AlF-OC PET/CT outperforms [68Ga]Ga-DOTA-SSA, but histological confirmation was lacking due to ethical and practical reasons. In this second arm, we therefore aimed to provide evidence that the vast majority of [18F]AlF-OC PET lesions are in fact true NET lesions by analyzing their MR characteristics on simultaneously acquired MRI. We had a special interest in lesions solely detected by [18F]AlF-OC ("incremental lesions").MethodsTen patients with a histologically confirmed neuroendocrine tumor (NET) and a standard-of-care [68Ga]Ga-DOTATATE PET/CT, performed within 3 months, were prospectively included. Patients underwent a whole-body PET/MRI (TOF, 3 T, GE Signa), 2 hours after IV injection of 4 MBq/kg [18F]AlF-OC. Positive PET lesions were evaluated for a corresponding lesion on MRI. The diagnostic performance of both PET tracers was evaluated by determining the detection ratio (DR) for each scan and the differential detection ratio (DDR) per patient.ResultsIn total, 195 unique lesions were detected: 167 with [68Ga]Ga-DOTATATE and 193 with [18F]AlF-OC. The DR for [18F]AlF-OC was 99.1% versus 91.4% for [68Ga]Ga-DOTATATE, significant for non-inferiority testing (p = 0.0001). Out of these 193 [18F]AlF-OC lesions, 96.2% were confirmed by MRI to be NET lesions. Thirty-three incremental lesions were identified by [18F]AlF-OC, of which 91% were confirmed by MRI and considered true positives.ConclusionThe DR of [18F]AlF-OC was numerically higher and non-inferior to the DR of [68Ga]Ga-DOTATATE. [18F]AlF-OC lesions and especially incremental lesions were confirmed as true positives by MRI in more than 90% of lesions. Taken together, these data further validate [18F]AlF-OC as a new alternative for SSTR PET in clinical practice. Trial registration ClinicalTrials.gov: NCT04552847. Registered 17 September 2020, https://beta.Clinicaltrialsgov/study/NCT04552847.

Project description:IntroductionThe yield per elution of a 68Ge/68Ga generator decreases during its lifespan. This affects the number of patients injected per elution or the injected dose per patient, thereby negatively affecting the cost of examinations and the quality of PET images due to increased image noise. We aimed to investigate whether AI-based PET denoising can offset this decrease in image quality parameters.MethodsAll patients addressed to our PET unit for a 68Ga-DOTATOC PET/CT from April 2020 to February 2021 were enrolled. Forty-four patients underwent their PET scans according to Protocol_FixedDose (150 MBq) and 32 according to Protocol_WeightDose (1.5 MBq/kg). Protocol_WeightDose examinations were processed using the Subtle PET software (Protocol_WeightDoseAI). Liver and vascular SUV mean were recorded as well as SUVmax, SUVmean and metabolic tumour volume (MTV) of the most intense tumoural lesion and its background SUVmean. Liver and vascular coefficients of variation (CV), tumour-to-background and tumour-to-liver ratios were calculated.ResultsThe mean injected dose of 2.1 (0.4) MBq/kg per patient was significantly higher in the Protocol_FixedDose group as compared to 1.5 (0.1) MBq/kg for the Protocol_WeightDose group. Protocol_WeightDose led to noisier images than Protocol_FixedDose with higher CVs for liver (15.57% ± 4.32 vs. 13.04% ± 3.51, p = 0.018) and blood-pool (28.67% ± 8.65 vs. 22.25% ± 10.37, p = 0.0003). Protocol_WeightDoseAI led to less noisy images than Protocol_WeightDose with lower liver CVs (11.42% ± 3.05 vs. 15.57% ± 4.32, p < 0.0001) and vascular CVs (16.62% ± 6.40 vs. 28.67% ± 8.65, p < 0.0001). Tumour-to-background and tumour-to-liver ratios were lower for protocol_WeightDoseAI: 6.78 ± 3.49 vs. 7.57 ± 4.73 (p = 0.01) and 5.96 ± 5.43 vs. 6.77 ± 6.19 (p < 0.0001), respectively. MTVs were higher after denoising whereas tumour SUVmax were lower: the mean% differences in MTV and SUVmax were + 11.14% (95% CI = 4.84-17.43) and -3.92% (95% CI = -6.25 to -1.59).ConclusionThe degradation of PET image quality due to a reduction in injected dose at the end of the 68Ge/68Ga generator lifespan can be effectively counterbalanced by using AI-based PET denoising.

Project description:BackgroundInflammation drives atherosclerotic plaque rupture. Although inflammation can be measured using fluorine-18-labeled fluorodeoxyglucose positron emission tomography ([18F]FDG PET), [18F]FDG lacks cell specificity, and coronary imaging is unreliable because of myocardial spillover.ObjectivesThis study tested the efficacy of gallium-68-labeled DOTATATE (68Ga-DOTATATE), a somatostatin receptor subtype-2 (SST2)-binding PET tracer, for imaging atherosclerotic inflammation.MethodsWe confirmed 68Ga-DOTATATE binding in macrophages and excised carotid plaques. 68Ga-DOTATATE PET imaging was compared to [18F]FDG PET imaging in 42 patients with atherosclerosis.ResultsTarget SSTR2 gene expression occurred exclusively in "proinflammatory" M1 macrophages, specific 68Ga-DOTATATE ligand binding to SST2 receptors occurred in CD68-positive macrophage-rich carotid plaque regions, and carotid SSTR2 mRNA was highly correlated with in vivo 68Ga-DOTATATE PET signals (r = 0.89; 95% confidence interval [CI]: 0.28 to 0.99; p = 0.02). 68Ga-DOTATATE mean of maximum tissue-to-blood ratios (mTBRmax) correctly identified culprit versus nonculprit arteries in patients with acute coronary syndrome (median difference: 0.69; interquartile range [IQR]: 0.22 to 1.15; p = 0.008) and transient ischemic attack/stroke (median difference: 0.13; IQR: 0.07 to 0.32; p = 0.003). 68Ga-DOTATATE mTBRmax predicted high-risk coronary computed tomography features (receiver operating characteristics area under the curve [ROC AUC]: 0.86; 95% CI: 0.80 to 0.92; p < 0.0001), and correlated with Framingham risk score (r = 0.53; 95% CI: 0.32 to 0.69; p <0.0001) and [18F]FDG uptake (r = 0.73; 95% CI: 0.64 to 0.81; p < 0.0001). [18F]FDG mTBRmax differentiated culprit from nonculprit carotid lesions (median difference: 0.12; IQR: 0.0 to 0.23; p = 0.008) and high-risk from lower-risk coronary arteries (ROC AUC: 0.76; 95% CI: 0.62 to 0.91; p = 0.002); however, myocardial [18F]FDG spillover rendered coronary [18F]FDG scans uninterpretable in 27 patients (64%). Coronary 68Ga-DOTATATE PET scans were readable in all patients.ConclusionsWe validated 68Ga-DOTATATE PET as a novel marker of atherosclerotic inflammation and confirmed that 68Ga-DOTATATE offers superior coronary imaging, excellent macrophage specificity, and better power to discriminate high-risk versus low-risk coronary lesions than [18F]FDG. (Vascular Inflammation Imaging Using Somatostatin Receptor Positron Emission Tomography [VISION]; NCT02021188).

Project description:PurposeThe widespread use of 68Ga for positron emission tomography (PET) relies on the development of radiopharmaceutical precursors that can be radiolabelled and dispensed in a simple, quick, and convenient manner. The DATA (6-amino-1,4-diazapine-triacetate) scaffold represents a novel hybrid chelator architecture possessing both cyclic and acyclic character that may allow for facile access to 68Ga-labelled tracers in the clinic. We report the first bifunctional DATA chelator conjugated to [Tyr3]octreotide (TOC), a somatostatin subtype 2 receptor (SST2)-targeting vector for imaging and functional characterisation of SSTR2 expressing tumours.MethodsThe radiopharmaceutical precursor, DATA-TOC, was synthesised as previously described and used to complex natGa(III) and 68Ga(III). Competition binding assays of [natGa]Ga-DATA-TOC or [natGa]Ga-DOTA-TOC against [125I-Tyr25]LTT-SS28 were conducted in membranes of HEK293 cells transfected to stably express one of the hSST2,3,5 receptor subtypes (HEK293-hSST2/3/5 cells). First in vivo studies were performed in female NMRI-nude mice bearing SST2-positive mouse phaeochromocytoma mCherry (MPC-mCherry) tumours to compare the in vivo SST2-specific tumour-targeting of [68Ga]Ga-DATA-TOC and its overall pharmacokinetics versus the [68Ga]Ga-DOTA-TOC reference. A direct comparison of [68Ga]Ga-DATA-TOC with the well-established PET radiotracer [68Ga]Ga-DOTA-TOC was additionally performed in a 46-year-old male patient with a well-differentiated NET (neuroendocrine tumour), representing the first in human administration of [68Ga]Ga-DATA-TOC.ResultsDATA-TOC was labelled with 68Ga with a radiolabelling efficiency of > 95% in less than 10 min at ambient temperature. A molar activity up to 35 MBq/nmol was achieved. The hSST2-affinities of [natGa]Ga-DATA-TOC and [natGa]Ga-DOTA-TOC were found similar with only sub-nanomolar differences in the respective IC50 values. In mice, [68Ga]Ga-DATA-TOC was able to visualise the tumour lesions, showing standardised uptake values (SUVs) similar to [68Ga]Ga-DOTA-TOC. Direct comparison of the two PET tracers in a NET patient revealed very similar tumour uptake for the two 68Ga-radiotracers, but with a higher tumour-to-liver contrast for [68Ga]Ga-DATA-TOC.Conclusion[68Ga]Ga-DATA-TOC was prepared, to a quality appropriate for in vivo use, following a highly efficient kit type process. Furthermore, the novel radiopharmaceutical was comparable or better than [68Ga]Ga-DOTA-TOC in all preclinical tests, achieving a higher tumour-to-liver contrast in a NET-patient. The results illustrate the potential of the DATA-chelator to facilitate the access to and preparation of 68Ga-radiotracers in a routine clinical radiopharmacy setting.

Dataset Information

A Pilot Study of Radiomics Models Combining Multi-Probe and Multi-Modality Images of ⁶⁸Ga-NOTA-PRGD2 and ¹⁸F-FDG PET/CT for Differentiating Benign and Malignant Pulmonary Space-Occupying Lesions.

Background

Methods

Results

Conclusion

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Dataset Information

A Pilot Study of Radiomics Models Combining Multi-Probe and Multi-Modality Images of 68Ga-NOTA-PRGD2 and 18F-FDG PET/CT for Differentiating Benign and Malignant Pulmonary Space-Occupying Lesions.

Background

Methods

Results

Conclusion

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

A Pilot Study of Radiomics Models Combining Multi-Probe and Multi-Modality Images of ⁶⁸Ga-NOTA-PRGD2 and ¹⁸F-FDG PET/CT for Differentiating Benign and Malignant Pulmonary Space-Occupying Lesions.