Comparing the diagnostic value of 68Ga-prostate-specific membrane antigen PET/CT and multiparametric MRI in pelvic lymph node metastasis of locally advanced prostate cancer
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ABSTRACT:
SUBMITTER: Xiong Z
PROVIDER: S-EPMC11291416 | biostudies-literature | 2024 Jul
REPOSITORIES: biostudies-literature
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Project description:The aim was to assess the performance of prostate 3T MRI for pelvic lymph node (LN) staging in prostate cancer (PCa), in comparison to 68Gallium-prostate specific membrane antigen PET-CT (68Ga-PSMA PET-CT) as reference standard for LN detection. 130 patients with PCa underwent non-contrast-enhanced multiparametric prostate 3T MRI and 68Ga-PSMA-PET-CT within 180 days at our institution. Overall, 187 LN metastases (n = 43 patients) detected by 68Ga-PSMA-PET-CT were characterized by calculating maximum standardized uptake value (SUVmax), area, diameter and anatomical location including iliac, obturator, presacral and inguinal region. MRI achieved an overall sensitivity, specificity, positive and negative predictive value of 81.6% (CI 71.1-88.9%), 98.6% (CI 97.6-99.2%), 73.5% (CI 52.1-87.6%) and 99.5% (CI 98.8-99.8%), respectively. On a region-based analysis, detection rates differed non-significantly (ps > 0.12) in the anatomical regions. On a size-dependent analysis, detection of LN > 10 mm did not differ significantly (ps > 0.09) from LN ≤ 10 mm. In comparison to single T1 sequence evaluation, additional use of the T2 weighted sequences did not improve the overall performance significantly (p > 0.05). 3T prostate MRI represented an accurate tool for the detection of LN compared to 68Ga-PSMA-PET-CT. Especially for LN metastases smaller than 10 mm, MRI was less accurate compared to 68Ga-PSMA-PET-CT.
| S-EPMC6656738 | biostudies-literature
Project description:Precise diagnosis of lymph node metastasis is important for therapeutic regimen planning, prognosis analysis and probably better outcomes for cancer patients. In this work, 68Ga-labeled amphiphilic alternating copolymers nanoparticles with different rigid ligands were synthesized as positron emission tomography (PET) probes for lymph node metastasis imaging. The labeling efficiency and stability of nanoparticles was improved with increased rigidity of coordination unit. PU(68Ga-L-MDI-PEG) nanoparticles (PU(68Ga-L-MDI-PEG) NPs) with the strongest rigidity of coordination unit exhibited the lowest critical micelle concentration, the best 68Ga labeling efficiency and stability. During in vivo lymph node metastasis imaging, PU(68Ga-L-MDI-PEG) NPs led to different accumulations in normal lymph nodes (N-LN) and tumor metastasized sentinel lymph nodes (T-SLN), which resulted in different PET signal presentation, making it feasible to differentiate N-LN from T-SLN. In comparison, small molecule probe 68GaL had poor lymph node accumulation, not only making it difficult to find lymph nodes on PET/computed tomography scan, but also tough to distinguish N-LN from metastatic ones. Overall, this work provides a reference for design of 68Ga labeled polymeric nanoparticles with high chelation efficiency and stability, as sensitive PET probes for lymph node imaging.
| S-EPMC10112949 | biostudies-literature
Project description:PurposeTo assess the accuracy of [68Ga]-PSMA-11 PET/CT or [68Ga]-PSMA-11 PET/MRI (PSMA-11 PET/CT(MRI)) for lymph node (LN) staging using salvage LN dissection (SLND) in patients with biochemical recurrence (BCR) after radical prostatectomy (RP).Patients and methodsIn a prospective study, 65 consecutive patients who developed BCR after RP underwent SLND after PSMA-11 PET/CT(MRI) between 2014 and 2018. Extended SLND up to the inferior mesenteric artery was performed in all patients. Regional and template-based correlations between the presence of LN metastases on histopathology and whole-body PSMA-11 PET/CT(MRI) results were evaluated. The diagnostic accuracy of PSMA-11 PET/CT(MRI) was also evaluated in relation to PSA level at the time of SLND.ResultsThe median age of the patients at the time of SLND was 65 years (IQR 63-69 years) and the median PSA level was 1.4 ng/ml (IQR 0.8-2.9 ng/ml). Before SLND, 50 patients (77%) had additional therapy after RP (26.2% androgen-deprivation therapy and 50.8% radiotherapy). The median number of LNs removed on SLND was 40 (IQR 33-48) and the median number of positive nodes was 4 (IQR 2-6). LN metastases were seen in 13.8% of resected LNs (317 of 2,292). LNs positive on PSMA-11 PET/CT(MRI) had a median diameter of 7.2 mm (IQR 5.3-9 mm). Metastatic LNs in regions negative on PSMA-11 PET had a median diameter of 3.4 mm (IQR 2.1-5.4 mm). In a regional analysis, the sensitivity of PSMA-11 PET/CT(MRI) ranged from 72% to 100%, and the specificity from 96% to 100%. Region-specific positive and negative predictive values ranged from 95% to 100% and 93% to 100%, respectively.ConclusionPSMA-11 PET/CT(MRI) has a very good performance for the identification of LN metastases in patients with BCR after RP. The high diagnostic accuracy in the regional and subregional analyses demonstrates the potential of this approach to enable a region-directed instead of a complete bilateral therapeutic intervention. The performance of PSMA-11 PET/CT(MRI) is dependent on the PSA level and the size of the metastatic deposit.
| S-EPMC6667405 | biostudies-literature
Project description:ObjectiveTo identify which patient with prostate cancer (PCa) could safely avoid extended pelvic lymph node dissection (ePLND) by predicting lymph node invasion (LNI), via a radiomics-based machine learning approach.MethodsAn integrative radiomics model (IRM) was proposed to predict LNI, confirmed by the histopathologic examination, integrating radiomics features, extracted from prostatic index lesion regions on MRI images, and clinical features via SVM. The study cohort comprised 244 PCa patients with MRI and followed by radical prostatectomy (RP) and ePLND within 6 months between 2010 and 2019. The proposed IRM was trained in training/validation set and evaluated in an internal independent testing set. The model's performance was measured by area under the curve (AUC), sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV). AUCs were compared via Delong test with 95% confidence interval (CI), and the rest measurements were compared via chi-squared test or Fisher's exact test.ResultsOverall, 17 (10.6%) and 14 (16.7%) patients with LNI were included in training/validation set and testing set, respectively. Shape and first-order radiomics features showed usefulness in building the IRM. The proposed IRM achieved an AUC of 0.915 (95% CI: 0.846-0.984) in the testing set, superior to pre-existing nomograms whose AUCs were from 0.698 to 0.724 (p < 0.05).ConclusionThe proposed IRM could be potentially feasible to predict the risk of having LNI for patients with PCa. With the improved predictability, it could be utilized to assess which patients with PCa could safely avoid ePLND, thus reduce the number of unnecessary ePLND.Key points• The combination of MRI-based radiomics features with clinical information improved the prediction of lymph node invasion, compared with the model using only radiomics features or clinical features. • With improved prediction performance on predicting lymph node invasion, the number of extended pelvic lymph node dissection (ePLND) could be reduced by the proposed integrative radiomics model (IRM), compared with the existing nomograms.
| S-EPMC9283224 | biostudies-literature
Project description:PurposeTo develop and evaluate a lymph node invasion (LNI) prediction model for men staged with [68Ga]Ga-PSMA-11 PET.MethodsA consecutive sample of intermediate to high-risk prostate cancer (PCa) patients undergoing [68Ga]Ga-PSMA-11 PET, extended pelvic lymph node dissection (ePLND), and radical prostatectomy (RP) at two tertiary referral centers were retrospectively identified. The training cohort comprised 173 patients (treated between 2013 and 2017), the validation cohort 90 patients (treated between 2016 and 2019). Three models for LNI prediction were developed and evaluated using cross-validation. Optimal risk-threshold was determined during model development. The best performing model was evaluated and compared to available conventional and multiparametric magnetic resonance imaging (mpMRI)-based prediction models using area under the receiver operating characteristic curves (AUC), calibration plots, and decision curve analysis (DCA).ResultsA combined model including prostate-specific antigen, biopsy Gleason grade group, [68Ga]Ga Ga-PSMA-11 positive volume of the primary tumor, and the assessment of the [68Ga]Ga-PSMA-11 report N-status yielded an AUC of 0.923 (95% CI 0.863-0.984) in the external validation. Using a cutoff of ≥ 17%, 44 (50%) ePLNDs would be spared and LNI missed in one patient (4.8%). Compared to conventional and MRI-based models, the proposed model showed similar calibration, higher AUC (0.923 (95% CI 0.863-0.984) vs. 0.700 (95% CI 0.548-0.852)-0.824 (95% CI 0.710-0.938)) and higher net benefit at DCA.ConclusionsOur results indicate that information from [68Ga]Ga-PSMA-11 may improve LNI prediction in intermediate to high-risk PCa patients undergoing primary staging especially when combined with clinical parameters. For better LNI prediction, future research should investigate the combination of information from both PSMA PET and mpMRI for LNI prediction in PCa patients before RP.
| S-EPMC10382335 | biostudies-literature
Project description:Imaging of the prostate-specific membrane antigen (PSMA) has become an important tool for managing patients with recurrent prostate cancer, and one of the most frequently employed radiopharmaceuticals is [68Ga]Ga-PSMA-11. Herein, we summarize the preclinical development and the clinical applications of [68Ga]Ga-PSMA-11 and present side-by-side comparisons with other radiopharmaceuticals or imaging modalities, in order to assist imagers and clinicians in recommending, performing, and interpreting the results of [68Ga]Ga-PSMA-11 PET scans in patients with prostate cancer.
| S-EPMC7724278 | biostudies-literature
Project description:PurposeTo compare the accuracy of multiparametric MRI (mpMRI), 68Ga-PSMA PET and the Briganti 2019 nomogram in the prediction of metastatic pelvic lymph nodes (PLN) in prostate cancer, to assess the accuracy of mpMRI and the Briganti nomogram in prediction of PET positive PLN and to investigate the added value of quantitative mpMRI parameters to the Briganti nomogram.MethodThis retrospective IRB-approved study included 41 patients with prostate cancer undergoing mpMRI and 68Ga-PSMA PET/CT or MR prior to prostatectomy and pelvic lymph node dissection. A board-certified radiologist assessed the index lesion on diffusion-weighted (Apparent Diffusion Coefficient, ADC; mean/volume), T2-weighted (capsular contact length, lesion volume/maximal diameters) and contrast-enhanced (iAUC, kep, Ktrans, ve) sequences. The probability for metastatic pelvic lymph nodes was calculated using the Briganti 2019 nomogram. PET examinations were evaluated by two board-certified nuclear medicine physicians.ResultsThe Briganti 2019 nomogram performed superiorly (AUC: 0.89) compared to quantitative mpMRI parameters (AUCs: 0.47-0.73) and 68Ga-PSMA-11 PET (AUC: 0.82) in the prediction of PLN metastases and superiorly (AUC: 0.77) in the prediction of PSMA PET positive PLN compared to MRI parameters (AUCs: 0.49-0.73). The addition of mean ADC and ADC volume from mpMRI improved the Briganti model by a fraction of new information of 0.21.ConclusionsThe Briganti 2019 nomogram performed superiorly in the prediction of metastatic and PSMA PET positive PLN, but the addition of parameters from mpMRI can further improve its accuracy. The combined model could be used to stratify patients requiring ePLND or PSMA PET.
| S-EPMC10091040 | biostudies-literature
Project description:PurposeThis meta-analysis evaluates the comparative diagnostic efficacy of 68Ga-prostate-specific membrane antigen-11 PET (68Ga-PSMA-11 PET) and multiparametric MRI (mpMRI) for the initial lymph node staging of prostate cancer.MethodsWe searched PubMed and Embase databases through October 2023 for studies that provide a head-to-head comparison of 68Ga-PSMA-11 PET and mpMRI, using pelvic lymph node dissection as the gold standard. We assessed sensitivity and specificity using the DerSimonian and Laird method, with variance stabilization via the Freeman-Tukey double inverse sine transformation. The quality of included studies was evaluated using the Quality Assessment of Diagnostic Performance Studies (QUADAS-2) tool.ResultsThe meta-analysis incorporated 13 articles, involving a total of 1,527 patients. 68Ga-PSMA-11 PET demonstrated an overall sensitivity of 0.73 (95% CI: 0.51-0.91) and a specificity of 0.94 (95% CI: 0.88-0.99). In comparison, mpMRI showed a sensitivity of 0.49 (95% CI: 0.30-0.68) and a specificity of 0.94 (95% CI: 0.88-0.99). Although 68Ga-PSMA-11 PET appeared to be more sensitive than mpMRI, the differences in sensitivity (p = 0.11) and specificity (p = 0.47) were not statistically significant.ConclusionOur findings indicated that 68Ga-PSMA-11 PET and mpMRI exhibit similar sensitivity and specificity in the diagnosis of initial lymph node staging of prostate cancer. However, given that most included studies were retrospective, further prospective studies with larger sample sizes are essential to validate these results.Systematic review registrationPROSPERO code is CRD42023495266.
| S-EPMC11222328 | biostudies-literature
Project description:This study proposed a new workflow for co-registering prostate PET images from a dual-tracer PET/MRI study with histopathological images of resected prostate specimens. The method aims to establish an accurate correspondence between PET/MRI findings and histology, facilitating a deeper understanding of PET tracer distribution and enabling advanced analyses like radiomics. To achieve this, images derived by three patients who underwent both [68Ga]Ga-PSMA and [68Ga]Ga-RM2 PET/MRI before radical prostatectomy were selected. After surgery, in the resected fresh specimens, fiducial markers visible on both histology and MR images were inserted. An ex vivo MRI of the prostate served as an intermediate step for co-registration between histological specimens and in vivo MRI examinations. The co-registration workflow involved five steps, ensuring alignment between histopathological images and PET/MRI data. The target registration error (TRE) was calculated to assess the precision of the co-registration. Furthermore, the DICE score was computed between the dominant intraprostatic tumor lesions delineated by the pathologist and the nuclear medicine physician. The TRE for the co-registration of histopathology and in vivo images was 1.59 mm, while the DICE score related to the site of increased intraprostatic uptake on [68Ga]Ga-PSMA and [68Ga]Ga-RM2 PET images was 0.54 and 0.75, respectively. This work shows an accurate co-registration method for histopathological and in vivo PET/MRI prostate examinations that allows the quantitative assessment of dual-tracer PET/MRI diagnostic accuracy at a millimetric scale. This approach may unveil radiotracer uptake mechanisms and identify new PET/MRI biomarkers, thus establishing the basis for precision medicine and future analyses, such as radiomics.
| S-EPMC10451901 | biostudies-literature
Project description:BackgroundThere are some limitations in the commonly used methods for the detection of prostate cancer. There is a lack of nomograms based on multiparametric magnetic resonance imaging (mpMRI) and 68Ga-prostate-specific membrane antigen (PSMA) positron emission tomography-computed tomography (PET-CT) for the prediction of prostate cancer. The study seeks to compare the performance of mpMRI and 68Ga-PSMA PET-CT, and design a novel predictive model capable of predicting clinically significant prostate cancer (csPCa) before biopsy based on a combination of 68Ga-PSMA PET-CT, mpMRI, and patient clinical parameters.MethodsFrom September 2020 to June 2021, we prospectively enrolled 112 consecutive patients with no prior history of prostate cancer who underwent both 68Ga-PSMA PET-CT and mpMRI prior to biopsy at our clinical center. Univariate and multivariate regression analyses were used to identify predictors of csPCa, with a predictive model and its nomogram incorporating 68Ga-PSMA PET-CT, mpMRI, and the clinical predictors then being generated. The constructed model was evaluated using receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis, and further validated with the internal and external cohorts.ResultsThe model incorporated prostate-specific antigen density (PSAd), Prostate Imaging Reporting and Data System (PI-RADS) category, and maximum standardized uptake value (SUVmax), and it exhibited excellent predictive efficacy when applying to evaluate both training and validation cohorts [area under the curve (AUC): 0.936 and 0.940, respectively]. Compared with SUVmax alone, the model demonstrated excellent diagnostic performance with improved specificity (0.910, 95% CI: 0.824-0.963) and positive predictive values (0.811, 95% CI: 0.648-0.920). Calibration curve and decision curve analysis further confirmed that the model exhibited a high degree of clinical net benefit and low error rate.ConclusionsThe constructed model in this study was capable of accurately predicting csPCa prior to biopsy with excellent discriminative ability. As such, this model has the potential to be an effective non-invasive approach for the diagnosis of csPCa.
| S-EPMC10406546 | biostudies-literature