Aggregates of hyperphosphorylated tau (PHF-tau), such as neurofibrillary tangles, are linked to the degree of cognitive impairment in Alzheimer's disease. We have recently reported early clinical results of a novel PHF-tau targeting PET imaging agent, [F18]-T807. Since then, we have investigated a second novel PHF-tau targeting PET imaging agent, [F18]-T808, with different pharmacokinetic characteristics, which may be favorable for imaging Alzheimer's disease and other tauopathies. Here, we describe the first human brain images with [F18]-T808.

Purpose

To assess whether hypermetabolically-defined regions of interest (ROIs) on 3,4-dihydroxy-6-[18F]-fluoro-L-phenylalanine (FDOPA) positron emission tomography (PET) could be used to evaluate physiological features and whether there are measurable differences between molecular subtypes and tumor grades.

Methods

Sixty-eight treatment-naïve glioma patients who underwent FDOPA PET and magnetic resonance imaging (MRI) were retrospectively included. Fluid-attenuated inversion recovery hyperintense regions (FLAIR_ROI) were segmented. FDOPA hypermetabolic regions (FDOPA_ROI, tumor-to-striatum ratios > 1) within FLAIR_ROI were extracted. Normalized maximum standardized uptake value (nSUV_max), volume of each ROI, and median relative cerebral blood volume (rCBV) and apparent diffusion coefficient (ADC) within FLAIR_ROI or FDOPA_ROI were calculated. Imaging metrics were compared using Students t or Mann-Whitney U tests. Area under the curve (AUC) of receiver-operating characteristic curves were used to determine whether imaging metrics within FLAIR_ROI or FDOPA_ROI can discriminate different molecular statuses or grades.

Results

Using either FLAIR_ROI or FDOPA_ROI, the nSUV_max and rCBV were significantly higher and the ADC was lower in isocitrate dehydrogenase (IDH) wild-type than mutant gliomas, and in higher-grade gliomas (HGGs) than lower-grade gliomas (LGGs). The FDOPA_ROI volume was significantly higher in 1p19q codeleted than non-codeleted gliomas, and in HGGs than LGGs. Although not significant, imaging metrics extracted by FDOPA_ROI discriminated molecular status and tumor grade more accurately than those extracted by FLAIR_ROI (AUC of IDH status, 0.87 vs. 0.82; 1p19q status, 0.78 vs. 0.73; grade, 0.87 vs. 0.76).

Conclusion

FDOPA hypermetabolic ROI may extract useful imaging features of gliomas, which can illuminate biological differences between different molecular status or tumor grades.

Background

The purpose of this study was to develop a voxel-wise clustering method of multiparametric magnetic resonance imaging (MRI) and 3,4-dihydroxy-6-[¹⁸F]-fluoro-L-phenylalanine (FDOPA) positron emission tomography (PET) images using an unsupervised, two-level clustering approach followed by support vector machine in order to classify the isocitrate dehydrogenase (IDH) status of gliomas.

Methods

Sixty-two treatment-naïve glioma patients who underwent FDOPA PET and MRI were retrospectively included. Contrast enhanced T1-weighted images, T2-weighted images, fluid-attenuated inversion recovery images, apparent diffusion coefficient maps, and relative cerebral blood volume maps, and FDOPA PET images were used for voxel-wise feature extraction. An unsupervised two-level clustering approach, including a self-organizing map followed by the K-means algorithm was used, and each class label was applied to the original images. The logarithmic ratio of labels in each class within tumor regions was applied to a support vector machine to differentiate IDH mutation status. The area under the curve (AUC) of receiver operating characteristic curves, accuracy, and F1-socore were calculated and used as metrics for performance.

Results

The associations of multiparametric imaging values in each cluster were successfully visualized. Multiparametric images with 16-class clustering revealed the highest classification performance to differentiate IDH status with the AUC, accuracy, and F1-score of 0.81, 0.76, and 0.76, respectively.

Conclusions

Machine learning using an unsupervised two-level clustering approach followed by a support vector machine classified the IDH mutation status of gliomas, and visualized voxel-wise features from multiparametric MRI and FDOPA PET images. Unsupervised clustered features may improve the understanding of prioritizing multiparametric imaging for classifying IDH status.

The role of prostate-specific membrane antigen (PSMA)-targeted PET in comparison to multiparametric MRI (mpMRI) in the evaluation of intraprostatic cancer foci is not well defined. The aim of our study was to compare the diagnostic performance of ⁶⁸Ga-PSMA-11 PET/CT (PSMA PET/CT), mpMRI, and PSMA PET/CT + mpMRI using 3 independent masked readers for each modality and with histopathology as the gold standard in the detection, intraprostatic localization, and determination of local extension of primary prostate cancer. Methods: Patients with intermediate- or high-risk prostate cancer who underwent PSMA PET/CT as part of a prospective trial (NCT03368547) and mpMRI before radical prostatectomy were included. Each imaging modality was interpreted by 3 independent readers who were unaware of the other modality result. A central majority rule was applied (2:1). Pathologic examination of whole-mount slices was used as the gold standard. Imaging scans and whole-mount slices were interpreted using the same standardized approach on a segment level and a lesion level. A "neighboring" approach was used to define imaging-pathology correlation for the detection of individual prostate cancer foci. Accuracy in determining the location, extraprostatic extension (EPE), and seminal vesicle invasion (SVI) of prostate cancer foci was assessed using receiver-operating-characteristic curve analysis. Interreader agreement was calculated using intraclass correlation coefficient analysis. Results: The final analysis included 74 patients (14 [19%] with intermediate risk and 60 [81%] with high risk). The cancer detection rate (lesion-based analysis) was 85%, 83%, and 87% for PSMA PET/CT, mpMRI, and PSMA PET/CT + mpMRI, respectively. The change in AUC was statistically significant between PSMA PET/CT + mpMRI and the 2 imaging modalities alone for delineation of tumor localization (segment-based analysis) (P < 0.001) but not between PSMA PET/CT and mpMRI (P = 0.093). mpMRI outperformed PSMA PET/CT in detecting EPE (P = 0.002) and SVI (P = 0.001). In the segment-level analysis, intraclass correlation coefficient analysis showed moderate reliability among PSMA PET/CT and mpMRI readers using a 5-point Likert scale (range, 0.53-0.64). In the evaluation of T staging, poor reliability was found among PSMA PET/CT readers and poor to moderate reliability was found for mpMRI readers. Conclusion: PSMA PET/CT and mpMRI have similar accuracy in the detection and intraprostatic localization of prostate cancer foci. mpMRI performs better in identifying EPE and SVI. For the T-staging evaluation of intermediate to high-risk prostate cancer, mpMRI should still be considered the imaging modality of reference. Whenever available, PSMA PET/MRI or the coregistration or fusion of PSMA PET/CT and mpMRI (PSMA PET/CT + mpMRI) should be used as it improves tumor extent delineation.

Introduction

In addition to being a risk factor for breast cancer, breast density has been hypothesized to be a surrogate biomarker for predicting response to endocrine-based chemotherapies. The purpose of this study was to evaluate whether a noninvasive bedside scanner based on diffuse optical spectroscopic imaging (DOSI) provides quantitative metrics to measure and track changes in breast tissue composition and density. To access a broad range of densities in a limited patient population, we performed optical measurements on the contralateral normal breast of patients before and during neoadjuvant chemotherapy (NAC). In this work, DOSI parameters, including tissue hemoglobin, water, and lipid concentrations, were obtained and correlated with magnetic resonance imaging (MRI)-measured fibroglandular tissue density. We evaluated how DOSI could be used to assess breast density while gaining new insight into the impact of chemotherapy on breast tissue.

Methods

This was a retrospective study of 28 volunteers undergoing NAC treatment for breast cancer. Both 3.0-T MRI and broadband DOSI (650 to 1,000 nm) were obtained from the contralateral normal breast before and during NAC. Longitudinal DOSI measurements were used to calculate breast tissue concentrations of oxygenated and deoxygenated hemoglobin, water, and lipid. These values were compared with MRI-measured fibroglandular density before and during therapy.

Results

Water (r = 0.843; P < 0.001), deoxyhemoglobin (r = 0.785; P = 0.003), and lipid (r = -0.707; P = 0.010) concentration measured with DOSI correlated strongly with MRI-measured density before therapy. Mean DOSI parameters differed significantly between pre- and postmenopausal subjects at baseline (water, P < 0.001; deoxyhemoglobin, P = 0.024; lipid, P = 0.006). During NAC treatment measured at about 90 days, significant reductions were observed in oxyhemoglobin for pre- (-20.0%; 95% confidence interval (CI), -32.7 to -7.4) and postmenopausal subjects (-20.1%; 95% CI, -31.4 to -8.8), and water concentration for premenopausal subjects (-11.9%; 95% CI, -17.1 to -6.7) compared with baseline. Lipid increased slightly in premenopausal subjects (3.8%; 95% CI, 1.1 to 6.5), and water increased slightly in postmenopausal subjects (4.4%; 95% CI, 0.1 to 8.6). Percentage change in water at the end of therapy compared with baseline correlated strongly with percentage change in MRI-measured density (r = 0.864; P = 0.012).

Conclusions

DOSI functional measurements correlate with MRI fibroglandular density, both before therapy and during NAC. Although from a limited patient dataset, these results suggest that DOSI may provide new functional indices of density based on hemoglobin and water that could be used at the bedside to assess response to therapy and evaluate disease risk.

Purpose

Although tumor localization and 3,4-dihydroxy-6-¹⁸F-fluoro-L-phenylalanine (FDOPA) uptake may have an association, preferential tumor localization in relation to FDOPA uptake is yet to be investigated in lower-grade gliomas (LGGs). This study aimed to identify differences in the frequency of tumor localization between FDOPA hypometabolic and hypermetabolic LGGs using a probabilistic radiographic atlas.

Methods

Fifty-one patients with newly diagnosed LGG (WHO grade II, 29; III, 22; isocitrate dehydrogenase wild-type, 21; mutant 1p19q non-codeleted,16; mutant codeleted, 14) who underwent FDOPA positron emission tomography (PET) were retrospectively selected. Semiautomated tumor segmentation on FLAIR was performed. Patients with LGGs were separated into two groups (FDOPA hypometabolic and hypermetabolic LGGs) according to the normalized maximum standardized uptake value of FDOPA PET (a threshold of the uptake in the striatum) within the segmented regions. Spatial normalization procedures to build a 3D MRI-based atlas using each segmented region were validated by an analysis of differential involvement statistical mapping.

Results

Superimposition of regions of interest showed a high number of hypometabolic LGGs localized in the frontal lobe, while a high number of hypermetabolic LGGs was localized in the insula, putamen, and temporal lobe. The statistical mapping revealed that hypometabolic LGGs occurred more frequently in the superior frontal gyrus (close to the supplementary motor area), while hypermetabolic LGGs occurred more frequently in the insula.

Conclusion

Radiographic atlases revealed preferential frontal lobe localization for FDOPA hypometabolic LGGs, which may be associated with relatively early detection.

⁶⁸Ga-satoreotide trizoxetan is a novel somatostatin receptor antagonist associated with high sensitivity and reproducibility in neuroendocrine tumor (NET) detection and localization. However, the optimal peptide mass and radioactivity ranges for ⁶⁸Ga-satoreotide trizoxetan have not yet been established. We therefore aimed to determine its optimal dosing regimen in patients with metastatic gastroenteropancreatic NETs in a prospective, randomized, 2 × 3 factorial, multicenter phase II study. Methods: Patients received ⁶⁸Ga-satoreotide trizoxetan at a peptide mass of 5-20 µg on day 1 of the study and of 30-45 µg on days 16-22, at 1 of 3 ⁶⁸Ga radioactivity ranges (40-80, 100-140, or 160-200 MBq). Whole-body PET/CT imaging was performed 50-70 min after each injection. The primary endpoint was the detection rate of NET lesions imaged by ⁶⁸Ga-satoreotide trizoxetan relative to contrast-enhanced CT (for each of the 6 peptide mass and radioactivity range combinations). Results: Twenty-four patients were evaluated in the per-protocol analysis. The median number of lesions detected by ⁶⁸Ga-satoreotide trizoxetan PET/CT or PET alone was at least twice as high as the number detected by contrast-enhanced CT across the 6 studied peptide mass and radioactivity range combinations. There were no differences between the 2 peptide mass ranges or between the 3 radioactivity ranges in the number of identified lesions. However, a trend toward a lower relative lesion count was noted in the liver for the 40- to 80-MBq range. No relationship was observed between the radioactivity range per patient's body weight (MBq/kg) and the number of lesions detected by ⁶⁸Ga-satoreotide trizoxetan. The median diagnostic sensitivity of ⁶⁸Ga-satoreotide trizoxetan PET/CT, based on the number of lesions per patient, ranged from 85% to 87% across the different peptide mass and radioactivity ranges. Almost all reported adverse events were mild and self-limiting. Conclusion: A radioactivity of 100-200 MBq with a peptide mass of up to 50 µg was confirmed as the optimal dosing regimen for ⁶⁸Ga-satoreotide trizoxetan to be used in future phase III studies.

Background and objectives

To investigate accuracy of magnetic resonance imaging (MRI) for measuring residual tumor size in breast cancer patients receiving neoadjuvant chemotherapy (NAC).

Methods

Ninety-eight patients were studied. Several MRI were performed during NAC for response monitoring, and the residual tumor size was measured on last MRI after completing NAC. Covariates, including age, tumor characteristics, biomarkers, NAC regimens, MRI scanners, and time from last MRI to operation, were analyzed. Univariate and Multivariate linear regression models were used to determine the predictive value of these covariates for MRI-pathology size discrepancy as the outcome measure.

Results

The mean (±SD) of the absolute difference between MRI and pathological residual tumor size was 1.0 ± 2.0 cm (range, 0-14 cm). Univariate regression analysis showed tumor type, morphology, HR status, HER2 status, and MRI scanner (1.5 T or 3.0 T) were significantly associated with MRI-pathology size discrepancy (all P < 0.05). Multivariate regression analyses demonstrated that only tumor type, tumor morphology, and biomarker status considering both HR and HER-2 were independent predictors (P = 0.0014, 0.0032, and 0.0286, respectively).

Conclusion

The accuracy of MRI in evaluating residual tumor size depends on tumor type, morphology, and biomarker status. The information may be considered in surgical planning for NAC patients.

AIMS

This study aimed to evaluate the influence of hormonal receptor and Ki-67 proliferation marker in predicting MRI accuracy of measuring residual tumor size in HER2 negative breast cancer receiving neoadjuvant chemotherapy (NAC).

METHODS

Fifty-four women were studied. Patients received AC and/or taxane-based regimens. The accuracy of MR determined clinical complete response (CCR) was compared to pathological complete response (pCR). The size of detectable residual tumor on MRI was correlated with pathology-diagnosed tumor size using Pearson’s correlation.

RESULTS

MRI correctly diagnosed 16 of the 17 pCR patients. There were 8 false negative diagnoses, 7 hormonal receptor (HR) positive and one HR negative. The overall sensitivity, specificity, and accuracy of MRI were 78%, 94%, and 83%, respectively. The positive predictive value was 97% and the negative predictive value was 67%. For MRI-pathology tumor size correlation, HR negative cancers showed a higher correlation (R=0.79) than HR positive cancers (R= 0.58). A worse MRI-pathology size discrepancy was found in HR positive cancer than in HR negative cancer (1.6±2.8 cm vs. 0.56±0.9 cm, p=0.05). Tumors with a low Ki-67 proliferation (<40%) showed a larger size discrepancy than those with a high Ki-67 proliferation (≥40%) (1.2±2.0 cm vs. 0.4±0.8 cm p=0.05).

CONCLUSIONS

The results showed that the diagnostic performance of MRI for breast cancer undergoing NAC is associated with molecular biomarker profile. Among HER2 negative tumors, the accuracy of MRI was worse in HR positive than negative cancers, and also worse in low proliferative than high proliferative tumors. These findings may help in surgical planning.

The aim of this study was to evaluate the change of breast density in the normal breast of patients receiving neoadjuvant chemotherapy (NAC). Forty-four breast cancer patients were studied. MRI acquisition was performed before treatment (baseline), and 4 and 12 weeks after treatment. A computer-algorithm-based program was used to segment breast tissue and calculate breast volume (BV), fibroglandular tissue volume (FV), and percent density (PD) (the ratio of FV over BV × 100%). The reduction of FV and PD after treatment was compared with baseline using paired t-tests with a Bonferroni-Holm correction. The association of density reduction with age was analyzed. FV and PD after NAC showed significant decreases compared with the baseline. FV was 110.0 ml (67.2, 189.8) (geometric mean (interquartile range)) at baseline, 104.3 ml (66.6, 164.4) after 4 weeks (p < 0.0001), and 94.7 ml (60.2, 144.4) after 12 weeks (comparison with baseline, p < 0.0001; comparison with 4 weeks, p = 0.016). PD was 11.2% (6.4, 22.4) at baseline, 10.6% (6.6, 20.3) after 4 weeks (p < 0.0001), and 9.7% (6.2, 17.9) after 12 weeks (comparison with baseline, p = 0.0001; comparison with 4 weeks, p = 0.018). Younger patients tended to show a higher density reduction, but overall correlation with age was only moderate (r = 0.28 for FV, p = 0.07, and r = 0.52 for PD, p = 0.0003). Our study showed that breast density measured from MR images acquired at 3T MR can be accurately quantified using a robust computer-aided algorithm based on non-parametric non-uniformity normalization (N3) and an adaptive fuzzy C-means algorithm. Similar to doxorubicin and cyclophosphamide regimens, the taxane-based NAC regimen also caused density atrophy in the normal breast and showed reduction in FV and PD. The effect of breast density reduction was age related and duration related.