Dataset Information

Evaluation of the total distribution volume of ¹⁸F-FBPA in normal tissues of healthy volunteers by non-compartmental kinetic modeling.

ABSTRACT:

Objective

Boron neutron capture therapy (BNCT) is a noninvasive radiation therapy method for cancer treatment. In BNCT, 4-borono-2-[¹⁸F]-fluoro-L-phenylalanine (¹⁸F-FBPA) PET has been employed to estimate ¹⁰B accumulation in target tumors and normal tissues if ¹⁰B borono-L-phenylalanine (¹⁰B-BPA) is used as a boron carrier. The purpose of the current study was to evaluate the total distribution volume (Vt) of ¹⁸F-FBPA in normal organs of healthy volunteers by kinetic analysis and to estimate boron concentration in normal organs for the therapeutic dose of ¹⁰B-BPA using obtained Vt values.

Methods

Six healthy volunteers were injected with ¹⁸F-FBPA (3-5 MBq/kg), and 7 PET-CT scans were performed subsequently. ¹⁸F-FBPA radioactivity in whole blood and plasma was measured before, and eight times after the injection. PET images were analyzed by PMOD software. Twelve volumetric regions of interest including the brain, heart, right lung, spleen, liver, parotid salivary glands, esophagus, stomach, pancreas, intestines, and bone marrow were drawn manually for each subject and analyzed with the Logan plot and two Ichise multilinear analyses (MA1 and MA2). The better model was defined by several goodness-of-fit parameters and residual distribution. After Vt values had been derived, boron concentration was estimated in ppm for the ¹⁰B-BPA-fructose (¹⁰B-BPA-fr) dose 30 g 1 and 2 h post-injection using Vt and interpolated plasma activity data.

Results

The Ichise MA2 model showed the best fit among all models. Akaike Information Criterion (AIC) was the lowest for the Ichise's MA2 in all regions (mean AIC value - 14.0) comparing to the other models (Logan plot mean AIC 31.4; Ichise MA1 model mean AIC - 4.2). Mean Vt values of the Ichise MA2 model ranged from 0.94?±?0.14 ml/ml in the pancreas to 0.16?±?0.02 ml/ml in the right lung. Estimated boron concentration for ¹⁰B-BPA-fr had the highest value in the pancreas (14.0?±?1.9 ppm 1 h after, and 5.7?±?1.7 ppm 2 h after the ¹⁸F-FBPA administration) and the lowest value in the right lung (2.4?±?0.3 ppm 1 h, and 1.0?±?0.3 ppm 2 h post-injection).

Conclusion

The ¹⁰B concentration in normal tissues was best estimated using Vt values of ¹⁸F-FBPA with the Ichise multilinear analysis 2 (MA2).

Trail registry

The UMIN clinical trial number: UMIN000022850.

SUBMITTER: Romanov V

PROVIDER: S-EPMC7033086 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Evaluation of the total distribution volume of 18F-FBPA in normal tissues of healthy volunteers by non-compartmental kinetic modeling.

Romanov Victor V Isohashi Kayako K Alobthani Galal G Beshr Rouaa R Horitsugi Genki G Kanai Yasukazu Y Naka Sadahiro S Watabe Tadashi T Shimosegawa Eku E Hatazawa Jun J

Annals of nuclear medicine 20191205 3

<h4>Objective</h4>Boron neutron capture therapy (BNCT) is a noninvasive radiation therapy method for cancer treatment. In BNCT, 4-borono-2-[18F]-fluoro-L-phenylalanine (18F-FBPA) PET has been employed to estimate 10B accumulation in target tumors and normal tissues if 10B borono-L-phenylalanine (10B-BPA) is used as a boron carrier. The purpose of the current study was to evaluate the total distribution volume (Vt) of 18F-FBPA in n ...[more]

PMID: 31808134

Similar Datasets

Project description:IntroductionCompartmental modelling is an established method of quantifying 18F-FDG uptake; however, only recently has it been applied to evaluate pulmonary inflammation. Implementation of compartmental models remains challenging in the lung, partly due to the low signal-to-noise ratio compared to other organs and the lack of standardisation. Good reproducibility is a key requirement of an imaging biomarker which has yet to be demonstrated in pulmonary compartmental models of 18F-FDG; in this paper, we address this unmet need.MethodsRetrospective subject data were obtained from the EVOLVE observational study: Ten COPD patients (age =66±9; 8M/2F), 10 α1ATD patients (age =63±8; 7M/3F) and 10 healthy volunteers (age =68±8; 9M/1F) never smokers. PET and CT images were co-registered, and whole lung regions were extracted from CT using an automated algorithm; the descending aorta was defined using a manually drawn region. Subsequent stages of the compartmental analysis were performed by two independent operators using (i) a MIAKATTM based pipeline and (ii) an in-house developed pipeline. We evaluated the metabolic rate constant of 18F-FDG (Kim) and the fractional blood volume (Vb); Bland-Altman plots were used to compare the results. Further, we adjusted the in-house pipeline to identify the salient features in the analysis which may help improve the standardisation of this technique in the lung.ResultsThe initial agreement on a subject level was poor: Bland-Altman coefficients of reproducibility for Kim and Vb were 0.0031 and 0.047 respectively. However, the effect size between the groups (i.e. COPD, α1ATD and healthy subjects) was similar using either pipeline. We identified the key drivers of this difference using an incremental approach: ROI methodology, modelling of the IDIF and time delay estimation. Adjustment of these factors led to improved Bland-Altman coefficients of reproducibility of 0.0015 and 0.027 for Kim and Vb respectively.ConclusionsDespite similar methodology, differences in implementation can lead to disparate results in the outcome parameters. When reporting the outcomes of lung compartmental modelling, we recommend the inclusion of the details of ROI methodology, input function fitting and time delay estimation to improve reproducibility.

Project description:Total metabolic tumor volume (TMTV), calculated from 18F-FDG PET/CT baseline studies, is a prognostic factor in diffuse large B-cell lymphoma (DLBCL) whose measurement requires the segmentation of all malignant foci throughout the body. No consensus currently exists regarding the most accurate approach for such segmentation. Further, all methods still require extensive manual input from an experienced reader. We examined whether an artificial intelligence-based method could estimate TMTV with a comparable prognostic value to TMTV measured by experts. Methods: Baseline 18F-FDG PET/CT scans of 301 DLBCL patients from the REMARC trial (NCT01122472) were retrospectively analyzed using a prototype software (PET Assisted Reporting System [PARS]). An automated whole-body high-uptake segmentation algorithm identified all 3-dimensional regions of interest (ROIs) with increased tracer uptake. The resulting ROIs were processed using a convolutional neural network trained on an independent cohort and classified as nonsuspicious or suspicious uptake. The PARS-based TMTV (TMTVPARS) was estimated as the sum of the volumes of ROIs classified as suspicious uptake. The reference TMTV (TMTVREF) was measured by 2 experienced readers using independent semiautomatic software. The TMTVPARS was compared with the TMTVREF in terms of prognostic value for progression-free survival (PFS) and overall survival (OS). Results: TMTVPARS was significantly correlated with the TMTVREF (ρ = 0.76; P < 0.001). Using PARS, an average of 24 regions per subject with increased tracer uptake was identified, and an average of 20 regions per subject was correctly identified as nonsuspicious or suspicious, yielding 85% classification accuracy, 80% sensitivity, and 88% specificity, compared with the TMTVREF region. Both TMTV results were predictive of PFS (hazard ratio, 2.3 and 2.6 for TMTVPARS and TMTVREF, respectively; P < 0.001) and OS (hazard ratio, 2.8 and 3.7 for TMTVPARS and TMTVREF, respectively; P < 0.001). Conclusion: TMTVPARS was consistent with that obtained by experts and displayed a significant prognostic value for PFS and OS in DLBCL patients. Classification of high-uptake regions using deep learning for rapidly discarding physiologic uptake may considerably simplify TMTV estimation, reduce observer variability, and facilitate the use of TMTV as a predictive factor in DLBCL patients.

Project description:PurposeGlioblastoma multiforme (GBM) is the most common glioma and standard therapies can only slightly prolong the survival. Neo-vascularization is a potential target to image tumor microenvironment, as it defines its brain invasion. We investigate [18F]rhPSMA-7.3 with PET/MRI for quantitative imaging of neo-vascularization in GBM bearing mice and human tumor tissue and compare it to [18F]FET and [18F]fluciclovine using PET pharmacokinetic modeling (PKM).Methods[18F]rhPSMA-7.3, [18F]FET, and [18F]fluciclovine were i.v. injected with 10.5 ± 3.1 MBq, 8.0 ± 2.2 MBq, 11.5 ± 1.9 MBq (n = 28, GL261-luc2) and up to 90 min PET/MR imaged 21/28 days after surgery. Regions of interest were delineated on T2-weighted MRI for (i) tumor, (ii) brain, and (iii) the inferior vena cava. Time-activity curves were expressed as SUV mean, SUVR and PKM performed using 1-/2-tissue-compartment models (1TCM, 2TCM), Patlak and Logan analysis (LA). Immunofluorescent staining (IFS), western blotting, and autoradiography of tumor tissue were performed for result validation.Results[18F]rhPSMA-7.3 showed a tumor uptake with a tumor-to-background-ratio (TBR) = 2.1-2.5, in 15-60 min. PKM (2TCM) confirmed higher K1 (0.34/0.08, p = 0.0012) and volume of distribution VT (0.24/0.1, p = 0.0017) in the tumor region compared to the brain. Linearity in LA and similar k3 = 0.6 and k4 = 0.47 (2TCM, tumor, p = ns) indicated reversible binding. K1, an indicator for vascularization, increased (0.1/0.34, 21 to 28 days, p < 0.005). IFS confirmed co-expression of PSMA and tumor vascularization. [18F]fluciclovine showed higher TBR (2.5/1.8, p < 0.001, 60 min) and VS (1.3/0.7, p < 0.05, tumor) compared to [18F]FET and LA indicated reversible binding. VT increased (p < 0.001, tumor, 21 to 28 days) for [18F]FET (0.5-1.4) and [18F]fluciclovine (0.84-1.5).Conclusion[18F]rhPSMA-7.3 showed to be a potential candidate to investigate the tumor microenvironment of GBM. Following PKM, this uptake was associated with tumor vascularization. In contrast to what is known from PSMA-PET in prostate cancer, reversible binding was found for [18F]rhPSMA-7.3 in GBM, contradicting cellular trapping. Finally, [18F]fluciclovine was superior to [18F]FET rendering it more suitable for PET imaging of GBM.

Project description:BackgroundPSMA-based alpha therapy using 225Ac-PSMA-I&T provides treatment for metastatic castration-resistant prostate cancer (mCRPC), even after the failure of 177Lu-PSMA radioligand therapy (RLT). In clinical routine, the total tumor volume (TTV) on PSMA PET impacts therapy outcomes and plays an increasing role in mCRPC patients. Hence, we aimed to assess TTV and its changes during 225Ac-PSMA-I&T RLT.MethodsmCRPC patients undergoing RLT with 225Ac-PSMA-I&T with available 18F-PSMA-1007 PET/CT prior to therapy initiation were included. TTV was assessed in all patients using established cut-off values. Image derived, clinical and biochemistry parameters (PSA, LDH, AP, pain score) were analyzed prior to and after two cycles of 225Ac-PSMA. Changes in TTV and further parameters were directly compared and then correlated with established response criteria, such as RECIST 1.1 or mPERCIST.Results13 mCRPC patients were included. The median overall survival (OS) was 10 months. Prior to 225Ac-PSMA RLT, there was no significant correlation between TTV with other clinical parameters (p > 0.05 each). Between short-term survivors (STS, <10 months OS) and long-term survivors (LTS, ≥10 months OS), TTV and PSA were comparable (p = 0.592 & p = 0.286, respectively), whereas AP was significantly lower in the LTS (p = 0.029). A total of 7/13 patients completed two cycles and underwent a follow-up 18F-PSMA-1007 PET/CT. Among these patients, there was a significant decrease in TTV (median 835 vs. 201 mL, p = 0.028) and PSA (median 687 ng/dL vs. 178 ng/dL, p = 0.018) after two cycles of 225Ac-PSMA RLT. Here, percentage changes of TTV after two cycles showed no direct correlation to all other clinical parameters (p > 0.05 each). In two patients, new PET-avid lesions were detected on 18F-PSMA-1007 PET/CT. However, TTV and PSA were decreasing or stable.ConclusionPET-derived assessment of TTV is an easily applicable imaging biomarker independent of other established parameters prior to 225Ac-PSMA RLT in these preliminary follow-up data. Even after the failure of 177Lu-PSMA, patients with extensive TTV seem to profit from RLT. All but one patient who was eligible for ≥2 cycles of 225Ac-PSMA-RLT demonstrated drastic TTV decreases without direct correlation to other biomarkers, such as serum PSA changes. Changes in TTV might hence improve the response assessment compared to standard classifiers by reflecting the current tumor load independent of the occurrence of new lesions.

Project description:PurposeIdentification of the dominant intraprostatic lesion(s) (DILs) can facilitate diagnosis and treatment by targeting biologically significant intra-prostatic foci. A PSMA ligand, [18F]DCFPyL (2-(3-{1-carboxy-5-[(6-[18F]fluoro-pyridine-3-carbonyl)-amino]-pentyl}-ureido)-pentanedioic acid), is better than choline-based [18F]FCH (fluorocholine) in detecting and localizing DIL because of higher tumour contrast, particularly when imaging is delayed to 1 h post-injection. The goal of this study was to investigate whether the different imaging performance of [18F]FCH and [18F]DCFPyL can be explained by their kinetic behaviour in prostate cancer (PCa) and to evaluate whether DIL can be accurately detected and localized using a short duration dynamic positron emission tomography (PET).Methods19 and 23 PCa patients were evaluated with dynamic [18F]DCFPyL and [18F]FCH PET, respectively. The dynamic imaging protocol with each tracer had a total imaging time of 22 min and consisted of multiple frames with acquisition times from 10 to 180 s. Tumour and benign tissue regions identified by sextant biopsy were compared using standardized uptake value (SUV) and tracer kinetic parameters from kinetic analysis of time-activity curves.ResultsFor [18F]DCFPyL, logistic regression identified Ki and k4 as the optimal model to discriminate tumour from benign tissue (84.2% sensitivity and 94.7% specificity), while only SUV was predictive for [18F]FCH (82.6% sensitivity and 87.0% specificity). The higher k3 (binding) of [18F]FCH than [18F]DCFPyL explains why [18F]FCH SUV can differentiate tumour from benign tissue within minutes of injection. Superior [18F]DCFPyL tumour contrast was due to the higher k4/k3 (more rapid washout) in benign tissue compared to tumour tissue.ConclusionsDIL was detected with good sensitivity and specificity using 22-min dynamic [18F]DCFPyL PET and avoids the need for delayed post-injection imaging timepoints. The dissimilar in vivo kinetic behaviour of [18F]DCFPyL and [18F]FCH could explain their different SUV images. Clinical Trial Registration NCT04009174 (ClinicalTrials.gov).