The role of biomarkers and dosimetry parameters in overall and progression free survival prediction for patients treated with personalized 90Y glass microspheres SIRT: a preliminary machine learning study.

BACKGROUND: Overall Survival (OS) and Progression-Free Survival (PFS) analyses are crucial metrics for evaluating the efficacy and impact of treatment. This study evaluated the role of clinical biomarkers and dosimetry parameters on survival outcomes of patients undergoing 90Y selective internal radiation therapy (SIRT). MATERIALS/METHODS: This preliminary and retrospective analysis included 17 patients with hepatocellular carcinoma (HCC) treated with 90Y SIRT. The patients underwent personalized treatment planning and voxel-wise dosimetry. After the procedure, the OS and PFS were evaluated. Three structures were delineated including tumoral liver (TL), normal perfused liver (NPL), and whole normal liver (WNL). 289 dose-volume constraints (DVCs) were extracted from dose-volume histograms of physical and biological effective dose (BED) maps calculated on 99mTc-MAA and 90Y SPECT/CT images. Subsequently, the DVCs and 16 clinical biomarkers were used as features for univariate and multivariate analysis. Cox proportional hazard ratio (HR) was employed for univariate analysis. HR and the concordance index (C-Index) were calculated for each feature. Using eight different strategies, a cross-combination of various models and feature selection (FS) methods was applied for multivariate analysis. The performance of each model was assessed using an averaged C-Index on a three-fold nested cross-validation framework. The Kaplan-Meier (KM) curve was employed for univariate and machine learning (ML) model performance assessment. RESULTS: The median OS was 11 months [95% CI: 8.5, 13.09], whereas the PFS was seven months [95% CI: 5.6, 10.98]. Univariate analysis demonstrated the presence of Ascites (HR: 9.2[1.8,47]) and the aim of SIRT (segmentectomy, lobectomy, palliative) (HR: 0.066 [0.0057, 0.78]), Aspartate aminotransferase (AST) level (HR:0.1 [0.012-0.86]), and MAA-Dose-V205(%)-TL (HR:8.5[1,72]) as predictors for OS. 90Y-derived parameters were associated with PFS but not with OS. MAA-Dose-V205(%)-WNL, MAA-BED-V400(%)-WNL with (HR:13 [1.5-120]) and 90Y-Dose-mean-TL, 90Y-D50-TL-Gy, 90Y-Dose-V205(%)-TL, 90Y-Dose- D50-TL-Gy, and 90Y-BED-V400(%)-TL (HR:15 [1.8-120]) were highly associated with PFS among dosimetry parameters. The highest C-index observed in multivariate analysis using ML was 0.94 ± 0.13 obtained from Variable Hunting-variable-importance (VH.VIMP) FS and Cox Proportional Hazard model predicting OS, using clinical features. However, the combination of VH. VIMP FS method with a Generalized Linear Model Network model predicting OS using Therapy strategy features outperformed the other models in terms of both C-index and stratification of KM curves (C-Index: 0.93 ± 0.14 and log-rank p-value of 0.023 for KM curve stratification). CONCLUSION: This preliminary study confirmed the role played by baseline clinical biomarkers and dosimetry parameters in predicting the treatment outcome, paving the way for the establishment of a dose-effect relationship. In addition, the feasibility of using ML along with these features was demonstrated as a helpful tool in the clinical management of patients, both prior to and following 90Y-SIRT.

Langerhans cell histiocytosis of the suprasellar region: diagnosis based on thyroid cytology.

Langerhans cell histiocytosis (LCH) may present as unifocal disease of the suprasellar region, with symptoms and signs of hypopituitarism, arginine vasopressin deficiency (AVP-D), and weight gain. Transcranial biopsy is necessary to define diagnosis and guide treatment decisions, but it is associated with significant morbidity. We describe a patient with Hashimoto thyroiditis and a single hypothalamic mass in whom LCH diagnosis was made by thyroid fine-needle aspiration cytology (FNAC) performed despite nonspecific findings in thyroid imaging, on the basis of a slightly elevated [18F]-fluorodeoxyglucose (FDG) avidity on PET/CT and volume increase during follow-up.

Information fusion for fully automated segmentation of head and neck tumors from PET and CT images.

BACKGROUND: PET/CT images combining anatomic and metabolic data provide complementary information that can improve clinical task performance. PET image segmentation algorithms exploiting the multi-modal information available are still lacking. PURPOSE: Our study aimed to assess the performance of PET and CT image fusion for gross tumor volume (GTV) segmentations of head and neck cancers (HNCs) utilizing conventional, deep learning (DL), and output-level voting-based fusions. METHODS: The current study is based on a total of 328 histologically confirmed HNCs from six different centers. The images were automatically cropped to a 200 × 200 head and neck region box, and CT and PET images were normalized for further processing. Eighteen conventional image-level fusions were implemented. In addition, a modified U2-Net architecture as DL fusion model baseline was used. Three different input, layer, and decision-level information fusions were used. Simultaneous truth and performance level estimation (STAPLE) and majority voting to merge different segmentation outputs (from PET and image-level and network-level fusions), that is, output-level information fusion (voting-based fusions) were employed. Different networks were trained in a 2D manner with a batch size of 64. Twenty percent of the dataset with stratification concerning the centers (20% in each center) were used for final result reporting. Different standard segmentation metrics and conventional PET metrics, such as SUV, were calculated. RESULTS: In single modalities, PET had a reasonable performance with a Dice score of 0.77 ± 0.09, while CT did not perform acceptably and reached a Dice score of only 0.38 ± 0.22. Conventional fusion algorithms obtained a Dice score range of [0.76-0.81] with guided-filter-based context enhancement (GFCE) at the low-end, and anisotropic diffusion and Karhunen-Loeve transform fusion (ADF), multi-resolution singular value decomposition (MSVD), and multi-level image decomposition based on latent low-rank representation (MDLatLRR) at the high-end. All DL fusion models achieved Dice scores of 0.80. Output-level voting-based models outperformed all other models, achieving superior results with a Dice score of 0.84 for Majority_ImgFus, Majority_All, and Majority_Fast. A mean error of almost zero was achieved for all fusions using SUVpeak , SUVmean and SUVmedian . CONCLUSION: PET/CT information fusion adds significant value to segmentation tasks, considerably outperforming PET-only and CT-only methods. In addition, both conventional image-level and DL fusions achieve competitive results. Meanwhile, output-level voting-based fusion using majority voting of several algorithms results in statistically significant improvements in the segmentation of HNC.

Artificial Intelligence-Driven Single-Shot PET Image Artifact Detection and Disentanglement: Toward Routine Clinical Image Quality Assurance.

PURPOSE: Medical imaging artifacts compromise image quality and quantitative analysis and might confound interpretation and misguide clinical decision-making. The present work envisions and demonstrates a new paradigm PET image Quality Assurance NETwork (PET-QA-NET) in which various image artifacts are detected and disentangled from images without prior knowledge of a standard of reference or ground truth for routine PET image quality assurance. METHODS: The network was trained and evaluated using training/validation/testing data sets consisting of 669/100/100 artifact-free oncological 18 F-FDG PET/CT images and subsequently fine-tuned and evaluated on 384 (20% for fine-tuning) scans from 8 different PET centers. The developed DL model was quantitatively assessed using various image quality metrics calculated for 22 volumes of interest defined on each scan. In addition, 200 additional 18 F-FDG PET/CT scans (this time with artifacts), generated using both CT-based attenuation and scatter correction (routine PET) and PET-QA-NET, were blindly evaluated by 2 nuclear medicine physicians for the presence of artifacts, diagnostic confidence, image quality, and the number of lesions detected in different body regions. RESULTS: Across the volumes of interest of 100 patients, SUV MAE values of 0.13 ± 0.04, 0.24 ± 0.1, and 0.21 ± 0.06 were reached for SUV mean , SUV max , and SUV peak , respectively (no statistically significant difference). Qualitative assessment showed a general trend of improved image quality and diagnostic confidence and reduced image artifacts for PET-QA-NET compared with routine CT-based attenuation and scatter correction. CONCLUSION: We developed a highly effective and reliable quality assurance tool that can be embedded routinely to detect and correct for 18 F-FDG PET image artifacts in clinical setting with notably improved PET image quality and quantitative capabilities.

Differential privacy preserved federated transfer learning for multi-institutional 68Ga-PET image artefact detection and disentanglement.

PURPOSE: Image artefacts continue to pose challenges in clinical molecular imaging, resulting in misdiagnoses, additional radiation doses to patients and financial costs. Mismatch and halo artefacts occur frequently in gallium-68 (68Ga)-labelled compounds whole-body PET/CT imaging. Correcting for these artefacts is not straightforward and requires algorithmic developments, given that conventional techniques have failed to address them adequately. In the current study, we employed differential privacy-preserving federated transfer learning (FTL) to manage clinical data sharing and tackle privacy issues for building centre-specific models that detect and correct artefacts present in PET images. METHODS: Altogether, 1413 patients with 68Ga prostate-specific membrane antigen (PSMA)/DOTA-TATE (TOC) PET/CT scans from 3 countries, including 8 different centres, were enrolled in this study. CT-based attenuation and scatter correction (CT-ASC) was used in all centres for quantitative PET reconstruction. Prior to model training, an experienced nuclear medicine physician reviewed all images to ensure the use of high-quality, artefact-free PET images (421 patients' images). A deep neural network (modified U2Net) was trained on 80% of the artefact-free PET images to utilize centre-based (CeBa), centralized (CeZe) and the proposed differential privacy FTL frameworks. Quantitative analysis was performed in 20% of the clean data (with no artefacts) in each centre. A panel of two nuclear medicine physicians conducted qualitative assessment of image quality, diagnostic confidence and image artefacts in 128 patients with artefacts (256 images for CT-ASC and FTL-ASC). RESULTS: The three approaches investigated in this study for 68Ga-PET imaging (CeBa, CeZe and FTL) resulted in a mean absolute error (MAE) of 0.42 ± 0.21 (CI 95%: 0.38 to 0.47), 0.32 ± 0.23 (CI 95%: 0.27 to 0.37) and 0.28 ± 0.15 (CI 95%: 0.25 to 0.31), respectively. Statistical analysis using the Wilcoxon test revealed significant differences between the three approaches, with FTL outperforming CeBa and CeZe (p-value < 0.05) in the clean test set. The qualitative assessment demonstrated that FTL-ASC significantly improved image quality and diagnostic confidence and decreased image artefacts, compared to CT-ASC in 68Ga-PET imaging. In addition, mismatch and halo artefacts were successfully detected and disentangled in the chest, abdomen and pelvic regions in 68Ga-PET imaging. CONCLUSION: The proposed approach benefits from using large datasets from multiple centres while preserving patient privacy. Qualitative assessment by nuclear medicine physicians showed that the proposed model correctly addressed two main challenging artefacts in 68Ga-PET imaging. This technique could be integrated in the clinic for 68Ga-PET imaging artefact detection and disentanglement using multicentric heterogeneous datasets.

The Clinical Added Value of Breast Cancer Imaging Using Hybrid PET/MR Imaging.

Dedicated MR imaging is highly performant for the evaluation of the primary lesion and should regularly be added to whole-body PET/MR imaging for the initial staging. PET/MR imaging is highly sensitive for the detection of nodal involvement and could be combined with the high specificity of axillary second look ultrasound for the confirmation of the N staging. For M staging, with the exception of lung lesions, PET/MR imaging is superior to PET/computed tomography, at half the radiation dose. The predictive value of multiparametric imaging with PET/MR imaging holds promise to improve through radiomics and artificial intelligence.

Predictive value of 99mTc-MAA-based dosimetry in personalized 90Y-SIRT planning for liver malignancies.

BACKGROUND: Selective internal radiation therapy with 90Y radioembolization aims to selectively irradiate liver tumours by administering radioactive microspheres under the theragnostic assumption that the pre-therapy injection of 99mTc labelled macroaggregated albumin (99mTc-MAA) provides an estimation of the 90Y microspheres biodistribution, which is not always the case. Due to the growing interest in theragnostic dosimetry for personalized radionuclide therapy, a robust relationship between the delivered and pre-treatment radiation absorbed doses is required. In this work, we aim to investigate the predictive value of absorbed dose metrics calculated from 99mTc-MAA (simulation) compared to those obtained from 90Y post-therapy SPECT/CT. RESULTS: A total of 79 patients were analysed. Pre- and post-therapy 3D-voxel dosimetry was calculated on 99mTc-MAA and 90Y SPECT/CT, respectively, based on Local Deposition Method. Mean absorbed dose, tumour-to-normal ratio, and absorbed dose distribution in terms of dose-volume histogram (DVH) metrics were obtained and compared for each volume of interest (VOI). Mann-Whitney U-test and Pearson's correlation coefficient were used to assess the correlation between both methods. The effect of the tumoral liver volume on the absorbed dose metrics was also investigated. Strong correlation was found between simulation and therapy mean absorbed doses for all VOIs, although simulation tended to overestimate tumour absorbed doses by 26%. DVH metrics showed good correlation too, but significant differences were found for several metrics, mostly on non-tumoral liver. It was observed that the tumoral liver volume does not significantly affect the differences between simulation and therapy absorbed dose metrics. CONCLUSION: This study supports the strong correlation between absorbed dose metrics from simulation and therapy dosimetry based on 90Y SPECT/CT, highlighting the predictive ability of 99mTc-MAA, not only in terms of mean absorbed dose but also of the dose distribution.

Unusual phosphaturic mesenchymal tumor mimicking osteoid osteoma.

Phosphaturic mesenchymal tumor is a rare tumor characterized by paraneoplastic osteomalacia. The diagnosis is often delayed because of nonspecific symptoms and difficulty to localize the tumor. In this study we report a case of PMT of the left femur detected by Ga-68-DOTATATE PET-CT with radiological features mimicking osteoid osteoma. We report a 31-year-old female patient who presented to our hospital for evaluation due to progressive bone pain and muscle weakness. Her laboratory data showed hypophosphatemia and increased fibroblast growth factor 23 (FGF-23) together with reduced bone mineral density on bone densitometry. The diagnosis of PMT was suspected and the tumor was identified on Ga-68-DOTATATE PET-CT as a focal uptake in a lucent lesion of the left femoral head with a central sclerotic dot mimicking a nidus as seen in osteoid osteoma. The lesion was treated with percutaneous radiofrequency ablation. Laboratory tests and bone densitometry rapidly improved post-treatment. The present case emphasizes the difficulty to diagnose PMT due to its nonspecific biochemical and clinical presentation and the relevance of functional imaging for locating these tumors despite different radiological presentation.

Increased Petrous Bone Uptake on 18 F-PSMA-1007 PET/CT Due to Otospongiosis.

ABSTRACT: We report the case of a 74-year-old man who had undergone radical prostatectomy for prostatic cancer 6 months earlier. Elevated prostate-specific antigen during follow-up prompted 18 F-prostate-specific membrane antigen (PSMA) ligand PET/CT ( 18 F-PSMA-1007 PET/CT) to search for new manifestations of prostate cancer, revealing an increased focal uptake (SUV max , 5.9) in the left cochlear/pericochlear temporal bone and equivocal PSMA-RADS-3a external iliac nodes. Comparison with cone-beam CT and MRI showed that the focal temporal bone uptake corresponded to the typical morphological features of active otospongiosis (otosclerosis) in the context of a previously known long-standing otospongiosis.

PET/CT-Based Salvage Radiotherapy for Recurrent Prostate Cancer After Radical Prostatectomy: Impact on Treatment Management and Future Directions.

Biochemical recurrence is a clinical situation experienced by 20 to 40% of prostate cancer patients treated with radical prostatectomy (RP). Prostate bed (PB) radiation therapy (RT) remains the mainstay salvage treatment, although it remains non-curative for up to 30% of patients developing further recurrence. Positron emission tomography with computed tomography (PET/CT) using prostate cancer-targeting radiotracers has emerged in the last decade as a new-generation imaging technique characterized by a better restaging accuracy compared to conventional imaging. By adapting targeting of recurrence sites and modulating treatment management, implementation in clinical practice of restaging PET/CT is challenging the established therapeutic standards born from randomized controlled trials. This article reviews the potential impact of restaging PET/CT on changes in the management of recurrent prostate cancer after RP. Based on PET/CT findings, it addresses potential adaptation of RT target volumes and doses, as well as use of androgen-deprivation therapy (ADT). However, the impact of such management changes on the oncological outcomes of PET/CT-based salvage RT strategies is as yet unknown.

Deep learning-assisted ultra-fast/low-dose whole-body PET/CT imaging.

PURPOSE: Tendency is to moderate the injected activity and/or reduce acquisition time in PET examinations to minimize potential radiation hazards and increase patient comfort. This work aims to assess the performance of regular full-dose (FD) synthesis from fast/low-dose (LD) whole-body (WB) PET images using deep learning techniques. METHODS: Instead of using synthetic LD scans, two separate clinical WB 18F-Fluorodeoxyglucose (18F-FDG) PET/CT studies of 100 patients were acquired: one regular FD (~ 27 min) and one fast or LD (~ 3 min) consisting of 1/8th of the standard acquisition time. A modified cycle-consistent generative adversarial network (CycleGAN) and residual neural network (ResNET) models, denoted as CGAN and RNET, respectively, were implemented to predict FD PET images. The quality of the predicted PET images was assessed by two nuclear medicine physicians. Moreover, the diagnostic quality of the predicted PET images was evaluated using a pass/fail scheme for lesion detectability task. Quantitative analysis using established metrics including standardized uptake value (SUV) bias was performed for the liver, left/right lung, brain, and 400 malignant lesions from the test and evaluation datasets. RESULTS: CGAN scored 4.92 and 3.88 (out of 5) (adequate to good) for brain and neck + trunk, respectively. The average SUV bias calculated over normal tissues was 3.39 ± 0.71% and - 3.83 ± 1.25% for CGAN and RNET, respectively. Bland-Altman analysis reported the lowest SUV bias (0.01%) and 95% confidence interval of - 0.36, + 0.47 for CGAN compared with the reference FD images for malignant lesions. CONCLUSION: CycleGAN is able to synthesize clinical FD WB PET images from LD images with 1/8th of standard injected activity or acquisition time. The predicted FD images present almost similar performance in terms of lesion detectability, qualitative scores, and quantification bias and variance.

[68Ga]Ga-PSMA-11 in prostate cancer: a comprehensive review.

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.

Projection Space Implementation of Deep Learning-Guided Low-Dose Brain PET Imaging Improves Performance over Implementation in Image Space.

Our purpose was to assess the performance of full-dose (FD) PET image synthesis in both image and sinogram space from low-dose (LD) PET images and sinograms without sacrificing diagnostic quality using deep learning techniques. Methods: Clinical brain PET/CT studies of 140 patients were retrospectively used for LD-to-FD PET conversion. Five percent of the events were randomly selected from the FD list-mode PET data to simulate a realistic LD acquisition. A modified 3-dimensional U-Net model was implemented to predict FD sinograms in the projection space (PSS) and FD images in image space (PIS) from their corresponding LD sinograms and images, respectively. The quality of the predicted PET images was assessed by 2 nuclear medicine specialists using a 5-point grading scheme. Quantitative analysis using established metrics including the peak signal-to-noise ratio (PSNR), structural similarity index metric (SSIM), regionwise SUV bias, and first-, second- and high-order texture radiomic features in 83 brain regions for the test and evaluation datasets was also performed. Results: All PSS images were scored 4 or higher (good to excellent) by the nuclear medicine specialists. PSNR and SSIM values of 0.96 ± 0.03 and 0.97 ± 0.02, respectively, were obtained for PIS, and values of 31.70 ± 0.75 and 37.30 ± 0.71, respectively, were obtained for PSS. The average SUV bias calculated over all brain regions was 0.24% ± 0.96% and 1.05% ± 1.44% for PSS and PIS, respectively. The Bland-Altman plots reported the lowest SUV bias (0.02) and variance (95% confidence interval, -0.92 to +0.84) for PSS, compared with the reference FD images. The relative error of the homogeneity radiomic feature belonging to the gray-level cooccurrence matrix category was -1.07 ± 1.77 and 0.28 ± 1.4 for PIS and PSS, respectively. Conclusion: The qualitative assessment and quantitative analysis demonstrated that the FD PET PSS led to superior performance, resulting in higher image quality and lower SUV bias and variance than for FD PET PIS.

Recurrent prostate cancer after radical prostatectomy: restaging performance of 18F-choline hybrid PET/MRI.

To evaluate the diagnostic performance of a whole-body 18F-choline (FCH) hybrid PET/MRI for prostate cancer patients at biochemical relapse after radical prostatectomy (RP) compared to pelvic multiparametric MRI (mpMRI), one of the standard imaging modality for this patient population. From 2010 to 2016, 58 whole-body FCH PET/MRI studies with mpMRI acquisitions were performed in 53 prostate cancer patients relapsing after curative RP. Median PSA and PSA doubling time (PSA DT) at PET study were 1.5 ng/ml and 6.5 months, respectively. The overall positivity rate of FCH PET/MRI was 58.6% (n = 34), dropping to 44% in patients with a PSA ≤ 2 ng/ml (n = 36). Median PSA values in positive and negative PET/MRI studies were 2.2 ng/ml and 0.8 ng/ml, respectively, with no differences in PSA DT (6.5 vs. 6.6 months). A PSA value ≥ 1.5 ng/ml was a significant predictor of positivity on PET/MRI studies. Compared to PET, mpMRI identified more local relapses (17 vs. 14, p = 0.453) while PET outperformed whole-body Dixon MRI for regional (16 vs. 9, p = 0.016) and distant (12 vs. 6, p = 0.031) metastases. Compared to pelvic mpMRI, the treatment approach turned out to be influenced more frequently using whole-body FCH hybrid PET/MRI studies (58.6% vs. 38%). In prostate cancer patients with biochemical recurrence after RP, whole-body FCH PET/MRI achieved a higher detection rate of nodal/distant metastases compared to pelvic mpMRI alone, increasing the change of treatment strategy by more than 20%.

What is the diagnostic performance of 18-FDG-PET/MR compared to PET/CT for the N- and M- staging of breast cancer?

PURPOSE: To compare the diagnostic performance of 18-FDG-PET/MR and PET/CT for the N- and M- staging of breast cancer. METHODS AND MATERIALS: Two independent readers blinded to clinical/follow-up data reviewed PET/MR and PET/CT examinations performed for initial or recurrent breast cancer staging in 80 consecutive patients (mean age = 48 ± 12.9 years). The diagnostic confidence for lesions in the contralateral breast, axillary/internal mammary nodes, bones and other distant sites were recorded. Sensitivity, specificity, positive (PPV) and negative predictive values (NPV) were calculated. The standard of reference included pathology and/or follow-up > 12 months. RESULTS: Nine of 80 patients had bone metastases; 13/80 had other distant metastases, 44/80 had axillary, 9/80 had internal mammary and 3/80 had contralateral breast tumours. Inter-reader agreement for lesions was excellent (weighted kappa = 0.833 for PET/CT and 0.823 for PET/MR) with similar reader confidence for the two tests (ICC = 0.875). In the patient-per-patient analysis, sensitivity and specificity of PET/MRI and PET/CT were similar (p > 0.05). In the lesion-per-lesion analysis, the sensitivity of PET/MR and PET/CT for bone metastases, other metastases, axillary and internal mammary nodes, contralateral tumours and all lesions together was 0.924 and 0.6923 (p = 0.0034), 0.923 and 0.923 (p = 1), 0.854 and 0.812 (p = 0.157), 0.9 and 0.9 (p = 1), 1 and 0.25 (p = 0.083), and 0.89 and 0.77 (p = 0.0013) respectively. The corresponding specificity was 0.953 and 1 (p = 0.0081), 1 and 1 (p = 1), 0.893 and 0.92 (p = 0.257), 1 and 1 (p = 1), 0.987 and 0.99 (p = 1) and 0.96 and 0.98 (p = 0.0075) respectively. CONCLUSIONS: Reader confidence, inter-reader agreement and diagnostic performance per patient were similar with PET/MR and PET/CT. However, for all lesions together, PET/MR had a superior sensitivity and lower specificity in the lesion-per-lesion analysis. KEY POINTS: • N and M breast cancer staging performance of PET/MR and PET/CT is similar per patient. • In a lesion-per-lesion analysis PET/MR is more sensitive than PET/CT especially for bone metastasis. • Readers' diagnostic confidence is similar for both tests.

Dopaminergic imaging separates normal pressure hydrocephalus from its mimics.

OBJECTIVE: Idiopathic normal pressure hydrocephalus (iNPH) and iNPH mimics (i.e., Parkinson's disease, progressive supranuclear palsy or dementia with Lewy bodies) share similar clinical features, and discrimination between both conditions relies on invasive time-consuming investigations. This study aims to compare [123I]FP-CIT SPECT imaging-visual rating and semiquantitative values-between iNPH and iNPH mimics. METHODS: Among 56 patients with a suspicion of iNPH (76.5 ± 6.1 years; 23.2% women), 26 fulfilled the iNPH diagnostic criteria and the remaining 30 were classified as iNPH mimics. Patients were visually categorized as having normal or abnormal [123I]FP-CIT SPECT; and for the quantification of the [123I]FP-CIT SPECT imaging, we calculated striatal binding ratios (SBR) using BRASS™ automated brain analysis while applying locally established reference limits (adjusted for age). Logistic regressions were used to assess the association between [123I]FP-CIT SPECT and diagnostic groups. RESULTS: A normal SBR [123I]FP-CIT SPECT was present in 69.2% of iNPH and 37.9% of mimics (p value = .020), while visual rating did not differ between the two groups. Normal SBR [123I]FP-CIT SPECT values were associated with the diagnosis of iNPH, even after adjusting for white matter changes and comorbidities (adjusted odds ratio: 4.17; 95% CI 1.26-13.80). CONCLUSION: Semi-quantitative [123I]FP-CIT SPECT evaluation, but not visual assessment, discriminates iNPH patients from their mimics. [123I]FP-CIT SPECT represents an interesting neuroimaging biomarker to improve the selection of patients with iNPH for invasive shunt surgery.

Education-Adjusted Normality Thresholds for FDG-PET in the Diagnosis of Alzheimer Disease.

BACKGROUND: A corollary of the reserve hypothesis is that what is regarded as pathological cortical metabolism in patients might vary according to education. OBJECTIVE: The aim of this study is to assess the incremental diagnostic value of education-adjusted over unadjusted thresholds on the diagnostic accuracy of FDG-PET as a biomarker for Alzheimer disease (AD). METHODS: We compared cortical metabolism in 90 healthy controls and 181 AD patients from the Alzheimer Disease Neuroimaging Initiative (ADNI) database. The AUC of the ROC curve did not differ significantly between the whole group and the higher-education patients or the lower-education subjects. RESULTS: The threshold of wMetaROI values providing 80% sensitivity was lower in higher-education patients and higher in the lower-education patients, compared to the standard threshold derived over the whole AD collective, without, however, significant changes in sensitivity and specificity. CONCLUSION: These data show that education, as a proxy of reserve, is not a major confounder in the diagnostic accuracy of FDG-PET in AD and the adoption of education-adjusted thresholds is not required in daily practice.

The Effect of Neoadjuvant Androgen Deprivation Therapy on Tumor Hypoxia in High-Grade Prostate Cancer: An 18F-MISO PET-MRI Study.

PURPOSE: Tumor hypoxia is associated with radioresistance and poor prognosis after radiation therapy for prostate cancer (PCa). In this prospective pilot study, we assessed the ability of 18F-misonidazole (18F-MISO) positron emission tomography (PET)-magnetic resonance imaging (MRI) to detect hypoxia in high-grade PCa patients who were candidates for curative radiation therapy, and we evaluated 18F-MISO PET-MRI modulation after 3 months of neoadjuvant androgen deprivation therapy (nADT). METHODS AND MATERIALS: Eleven PCa patients with a Gleason score (GS) ≥ 8 underwent 18F-fluorocholine (18F-FCH) PET-computed tomography at diagnosis and an 18F-MISO hybrid PET-MRI examination before nADT; a second 18F-MISO PET-MRI examination was acquired after 3 months of nADT for all patients but one who dropped out because of noncompliance with nADT. Immunohistochemistry for tissue hypoxia- and proliferation-related biomarkers (glucose transporter 1, carbonic anhydrase IX, vascular endothelial growth factor A, Ki-67, hypoxia-inducible factor 1 alpha, and epidermal growth factor receptor) was performed in lesions bearing the highest GS. We used nonparametric tests to assess (1) the presence of 18F-MISO-positive regions (tumor-to-background ratio [TBR] ≥ 1.4) at baseline; (2) the correlation between imaging parameters (PET tracer uptake, Prostate Imaging Reporting and Data System [PIRADS] scores, and dynamic contrast enhancement perfusion markers) at baseline; (3) the difference in immunohistochemistry staining between 18F-MISO-positive and -negative lesions; and (4) the changes in 18F-MISO PET-MRI after nADT. RESULTS: Uptake of 18F-MISO was significant in 7 patients, being coincidental with the highest GS region in 5 of them. A significant correlation was found at baseline between GS and 18F-MISO TBR, between 18F-MISO TBR and MRI perfusion markers, between GS and 18F-FCH maximum standardized uptake value, between GS and PIRADS score, and between 18F-FCH maximum standardized uptake value and PIRADS score. No difference was found between 18F-MISO-positive and -negative biopsy specimens with respect to tissue biomarkers. The TBR of 18F-MISO diminished significantly after nADT only in high-grade lesions and in regions with a significant uptake at baseline. CONCLUSIONS: PET imaging with 18F-MISO showed variable uptake in PCa, associated with a higher GS, lowering significantly after 3 months of nADT in high-grade lesions. These results suggest the existence of a hypoxic microenvironment in PCa and a reoxygenation effect of nADT.