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"Just Accepted" papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note that during production of the final copyedited article, errors may be discovered which could affect the content. Purpose To test transformer-based models' performance when manipulating pretraining weights, dataset size, input size and comparing the best-model with reference standard and state-of-the-art models for a resting-state functional (rs-fMRI) fetal brain extraction task. Materials and Methods An internal retrospective dataset (fetuses = 172; images = 519; collected from 2018-2022) was used to investigate influence of dataset size, pretraining approaches and image input size on Swin-UNETR and UNETR models. The internal and an external (fetuses = 131; images = 561) datasets were used to cross-validate and to assess generalization capability of the best model against state-of-the-art models on different scanner types and number of gestational weeks (GW). The Dice similarity coefficient (DSC) and the Balanced average Hausdorff distance (BAHD) were used as segmentation performance metrics. GEE multifactorial models were used to assess significant model and interaction effects of interest. Results Swin-UNETR was not affected by pretraining approach and dataset size and performed best with the mean dataset image size, with a mean DSC of 0.92 and BAHD of 0.097. The Swin-UNETR was not affected by scanner type. Generalization results on the internal dataset showed that Swin-UNETR had lower performances compared with reference standard models and comparable performances on the external dataset. Cross-validation on internal and external test sets demonstrated better and comparable performance of Swin-UNETR versus convolutional neural network architectures during the late-fetal period (GWs > 25) but lower performance during the midfetal period (GWs ≤ 25). Conclusion Swin-UNTER showed flexibility in dealing with smaller datasets, regardless of pretraining approaches. For fetal brain extraction of rs-fMRI, Swin-UNTER showed comparable performance with reference standard models during the late-fetal period and lower performance during the early GW period. ©RSNA, 2024.
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PURPOSE: Accurate identification of lymph node (LN) metastases is pivotal for surgical planning of pancreatic neuroendocrine tumours (PanNETs); however, current imaging techniques have sub-optimal diagnostic sensitivity. Aim of this study is to investigate whether [68Ga]Ga-DOTATOC PET radiomics might improve the identification of LN metastases in patients with non-functioning PanNET (NF-PanNET) referred to surgical intervention. METHODS: Seventy-two patients who performed preoperative [68Ga]Ga-DOTATOC PET between December 2017 and March 2022 for NF-PanNET. [68Ga]Ga-DOTATOC PET qualitative assessment of LN metastases was measured using diagnostic balanced accuracy (bACC), sensitivity (SN), specificity (SP), positive and negative predictive values (PPV, NPV). SUVmax, SUVmean, Somatostatin receptor density (SRD), total lesion SRD (TLSRD) and IBSI-compliant radiomic features (RFs) were obtained from the primary tumours. To predict LN involvement, these parameters were engineered, selected and used to train different machine learning models. Models were validated using tenfold repeated cross-validation and control models were developed. Models' bACC, SN, SP, PPV and NPV were collected and compared (Kruskal-Wallis, Mann-Whitney). RESULTS: LN metastases were detected in 29/72 patients at histology. [68Ga]Ga-DOTATOC PET qualitative examination of LN involvement provided bACC = 60%, SN = 24%, SP = 95%, PPV = 78% and NPV = 65%. The best-performing radiomic model provided a bACC = 70%, SN = 77%, SP = 61%, PPV = 60% and NPV = 83% (outperforming the control model, p < 0.05*). CONCLUSION: In this study, [68Ga]Ga-DOTATOC PET radiomics allowed to increase diagnostic sensitivity in detecting LN metastases from 24 to 77% in NF-PanNET patients candidate to surgery. Especially in case of micrometastatic involvement, this approach might assist clinicians in a better patients' stratification.
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Metástase Linfática , Tumores Neuroendócrinos , Octreotida , Compostos Organometálicos , Neoplasias Pancreáticas , Humanos , Neoplasias Pancreáticas/diagnóstico por imagem , Neoplasias Pancreáticas/cirurgia , Neoplasias Pancreáticas/patologia , Feminino , Pessoa de Meia-Idade , Masculino , Tumores Neuroendócrinos/diagnóstico por imagem , Tumores Neuroendócrinos/patologia , Tumores Neuroendócrinos/cirurgia , Octreotida/análogos & derivados , Metástase Linfática/diagnóstico por imagem , Idoso , Adulto , Processamento de Imagem Assistida por Computador/métodos , Tomografia por Emissão de Pósitrons combinada à Tomografia Computadorizada/métodos , Tomografia por Emissão de Pósitrons/métodos , Período Pré-Operatório , RadiômicaRESUMO
PURPOSE: To compare the diagnostic accuracy and detection rates of PET/MRI with [68Ga]Ga-PSMA-11 and [68Ga]Ga-M2 in patients with biochemical recurrence of prostate cancer (PCa). METHODS: Sixty patients were enrolled in this prospective single-center phase II clinical trial from June 2020 to October 2022. Forty-four/60 completed all study examinations and were available at follow-up (median: 22.8 months, range: 6-31.5 months). Two nuclear medicine physicians analyzed PET images and two radiologists interpreted MRI; images were then re-examined to produce an integrated PET/MRI report for both [68Ga]Ga-PSMA-11 and [68Ga]Ga-RM2 examinations. A composite reference standard including histological specimens, response to treatment, and conventional imaging gathered during follow-up was used to validate imaging findings. Detection rates, accuracy, sensitivity, specificity, positive, and negative predictive value were assessed. McNemar's test was used to compare sensitivity and specificity on a per-patient base and detection rate on a per-region base. Prostate bed, locoregional lymph nodes, non-skeletal distant metastases, and bone metastases were considered. p-value significance was defined below the 0.05 level after correction for multiple testing. RESULTS: Patients' median age was 69.8 years (interquartile range (IQR): 61.8-75.1) and median PSA level at time of imaging was 0.53 ng/mL (IQR: 0.33-2.04). During follow-up, evidence of recurrence was observed in 31/44 patients. Combining MRI with [68Ga]Ga-PSMA-11 PET and [68Ga]Ga-RM2 PET resulted in sensitivity = 100% and 93.5% and specificity of 69.2% and 69.2%, respectively. When considering the individual imaging modalities, [68Ga]Ga-RM2 PET showed lower sensitivity compared to [68Ga]Ga-PSMA-11 PET and MRI (61.3% vs 83.9% and 87.1%, p = 0.046 and 0.043, respectively), while specificity was comparable among the imaging modalities (100% vs 84.6% and 69.2%, p = 0.479 and 0.134, respectively). CONCLUSION: This study brings further evidence on the utility of fully hybrid PET/MRI for disease characterization in patients with biochemically recurrent PCa. Imaging with [68Ga]Ga-PSMA-11 PET showed high sensitivity, while the utility of [68Ga]Ga-RM2 PET in absence of a simultaneous whole-body/multiparametric MRI remains to be determined.
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Isótopos de Gálio , Radioisótopos de Gálio , Neoplasias da Próstata , Masculino , Humanos , Idoso , Estudos Prospectivos , Neoplasias da Próstata/diagnóstico por imagem , Neoplasias da Próstata/patologia , Imageamento por Ressonância Magnética , Tomografia por Emissão de Pósitrons combinada à Tomografia Computadorizada , Ácido EdéticoRESUMO
Localized prostate cancer (PCa) can be treated with radical prostatectomy (RP). Up to 30% of patients undergoing this procedure experience biochemical recurrence (BCR), namely the rise in serum prostate-specific antigen (PSA) levels during the post-surgical follow-up, requiring further treatments and with the risk of severe disease progression. Currently, the most accurate imaging technique to confirm, detect, and locate disease relapses in BCR patients is prostate-specific membrane antigen (PSMA)-targeted PET, as recommended by international clinical guidelines. The aim of the study was to investigate potential clinical and pathological predictors of PSMA PET positivity, validated by clinical and instrumental follow-up or histopathological data. In this study, a selected cohort of BCR patients after RP and no other PCa-related therapy who underwent either PSMA PET/CT or PSMA PET/MRI has been analysed. Among the considered predictors, both pathological staging after RP equal or higher than pT3a and higher PSA levels at the time of the scan were significantly correlated with PSMA PET positivity on multivariate logistic regression analysis. As expected, PSMA PET confirmed its role as an accurate imaging technique in the setting of BCR in PCa. These findings may inform appropriate and tailored patient selection and scan timing to optimize and fully exploit this powerful diagnostic tool.
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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.
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A link between maternal anxiety during pregnancy and adverse socio-emotional outcomes in childhood has been consistently sustained on the very early neurodevelopmental alteration of structural pathways between fetal limbic and cortical brain regions. In this study, we provide follow-up evidence for a feed-forward model linking (i) maternal anxiety, (ii) fetal functional neurodevelopment, (iii) neonatal functional network organization with (iv) socio-emotional neurobehavioral development in early childhood. Namely, we investigate a sample of 16 mother-fetus dyads and show how a maternal state-trait anxiety profile with pregnancy-specific worries can significantly influence functional synchronization patterns between regions of the fetal limbic system (i.e., hippocampus and amygdala) and the neocortex, as assessed through resting-state functional magnetic resonance imaging. Generalization of the findings was supported by leave-one-out cross-validation. We further show how this maternal-fetal cross-talk propagates to functional network topology in the neonate, specifically targeting connector hubs, and further maps onto socio-emotional profiles, assessed through Bayley-III socio-emotional scale in early childhood (i.e., in the 12-24 months range). Based on this evidence, we put forward the hypothesis of a "Maternal-Fetal-Neonatal Anxiety Backbone", through which neurobiological changes driven by maternal anxiety could trigger a divergence in the establishment of a cognitive-emotional development blueprint, in terms of the nascent functional homeostasis between bottom-up limbic and top-down higher-order neuronal circuitry.
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Encéfalo , Imageamento por Ressonância Magnética , Recém-Nascido , Feminino , Gravidez , Humanos , Pré-Escolar , Encéfalo/patologia , Emoções , Feto , AnsiedadeRESUMO
PURPOSE: The aim of this study is to investigate the role of [68Ga]Ga-PSMA-11 PET radiomics for the prediction of post-surgical International Society of Urological Pathology (PSISUP) grade in primary prostate cancer (PCa). METHODS: This retrospective study included 47 PCa patients who underwent [68Ga]Ga-PSMA-11 PET at IRCCS San Raffaele Scientific Institute before radical prostatectomy. The whole prostate was manually contoured on PET images and 103 image biomarker standardization initiative (IBSI)-compliant radiomic features (RFs) were extracted. Features were then selected using the minimum redundancy maximum relevance algorithm and a combination of the 4 most relevant RFs was used to train 12 radiomics machine learning models for the prediction of PSISUP grade: ISUP ≥ 4 vs ISUP < 4. Machine learning models were validated by means of fivefold repeated cross-validation, and two control models were generated to assess that our findings were not surrogates of spurious associations. Balanced accuracy (bACC) was collected for all generated models and compared with Kruskal-Wallis and Mann-Whitney tests. Sensitivity, specificity, and positive and negative predictive values were also reported to provide a complete overview of models' performance. The predictions of the best performing model were compared against ISUP grade at biopsy. RESULTS: ISUP grade at biopsy was upgraded in 9/47 patients after prostatectomy, resulting in a bACC = 85.9%, SN = 71.9%, SP = 100%, PPV = 100%, and NPV = 62.5%, while the best-performing radiomic model yielded a bACC = 87.6%, SN = 88.6%, SP = 86.7%, PPV = 94%, and NPV = 82.5%. All radiomic models trained with at least 2 RFs (GLSZM-Zone Entropy and Shape-Least Axis Length) outperformed the control models. Conversely, no significant differences were found for radiomic models trained with 2 or more RFs (Mann-Whitney p > 0.05). CONCLUSION: These findings support the role of [68Ga]Ga-PSMA-11 PET radiomics for the accurate and non-invasive prediction of PSISUP grade.
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Radioisótopos de Gálio , Neoplasias da Próstata , Masculino , Humanos , Neoplasias da Próstata/diagnóstico por imagem , Neoplasias da Próstata/cirurgia , Neoplasias da Próstata/patologia , Estudos Retrospectivos , Tomografia por Emissão de Pósitrons combinada à Tomografia Computadorizada/métodosRESUMO
Introduction: State of the art artificial intelligence (AI) models have the potential to become a "one-stop shop" to improve diagnosis and prognosis in several oncological settings. The external validation of AI models on independent cohorts is essential to evaluate their generalization ability, hence their potential utility in clinical practice. In this study we tested on a large, separate cohort a recently proposed state-of-the-art convolutional neural network for the automatic segmentation of intraprostatic cancer lesions on PSMA PET images. Methods: Eighty-five biopsy proven prostate cancer patients who underwent 68Ga PSMA PET for staging purposes were enrolled in this study. Images were acquired with either fully hybrid PET/MRI (N = 46) or PET/CT (N = 39); all participants showed at least one intraprostatic pathological finding on PET images that was independently segmented by two Nuclear Medicine physicians. The trained model was available at https://gitlab.com/dejankostyszyn/prostate-gtv-segmentation and data processing has been done in agreement with the reference work. Results: When compared to the manual contouring, the AI model yielded a median dice score = 0.74, therefore showing a moderately good performance. Results were robust to the modality used to acquire images (PET/CT or PET/MRI) and to the ground truth labels (no significant difference between the model's performance when compared to reader 1 or reader 2 manual contouring). Discussion: In conclusion, this AI model could be used to automatically segment intraprostatic cancer lesions for research purposes, as instance to define the volume of interest for radiomics or deep learning analysis. However, more robust performance is needed for the generation of AI-based decision support technologies to be proposed in clinical practice.
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Background: Tumor heterogeneity poses major clinical challenges in high-grade gliomas (HGGs). Quantitative radiomic analysis with spatial tumor habitat clustering represents an innovative, non-invasive approach to represent and quantify tumor microenvironment heterogeneity. To date, habitat imaging has been applied mainly on conventional magnetic resonance imaging (MRI), although virtually extendible to any imaging modality, including advanced MRI techniques such as perfusion and diffusion MRI as well as positron emission tomography (PET) imaging. Objectives: This study aims to evaluate an innovative PET and MRI approach for assessing hypoxia, perfusion, and tissue diffusion in HGGs and derive a combined map for clustering of intra-tumor heterogeneity. Materials and Methods: Seventeen patients harboring HGGs underwent a pre-operative acquisition of MR perfusion (PWI), Diffusion (dMRI) and 18F-labeled fluoroazomycinarabinoside (18F-FAZA) PET imaging to evaluate tumor vascularization, cellularity, and hypoxia, respectively. Tumor volumes were segmented on fluid-attenuated inversion recovery (FLAIR) and T1 post-contrast images, and voxel-wise clustering of each quantitative imaging map identified eight combined PET and physiologic MRI habitats. Habitats' spatial distribution, quantitative features and histopathological characteristics were analyzed. Results: A highly reproducible distribution pattern of the clusters was observed among different cases, particularly with respect to morphological landmarks as the necrotic core, contrast-enhancing vital tumor, and peritumoral infiltration and edema, providing valuable supplementary information to conventional imaging. A preliminary analysis, performed on stereotactic bioptic samples where exact intracranial coordinates were available, identified a reliable correlation between the expected microenvironment of the different spatial habitats and the actual histopathological features. A trend toward a higher representation of the most aggressive clusters in WHO (World Health Organization) grade IV compared to WHO III was observed. Conclusion: Preliminary findings demonstrated high reproducibility of the PET and MRI hypoxia, perfusion, and tissue diffusion spatial habitat maps and correlation with disease-specific histopathological features.
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Resting-state functional magnetic resonance imaging (rs-fMRI) most recently has proved to open a measureless window on functional neurodevelopment in utero. Fetal brain activation and connectivity maps can be heavily influenced by 1) fetal-specific motion effects on the time-series and 2) the accuracy of time-series spatial normalization to a standardized gestational-week (GW) specific fetal template space.Due to the absence of a standardized and generalizable image processing protocol, the objective of the present work was to implement a validated fetal rs-fMRI preprocessing pipeline (RS-FetMRI) divided into 6 inter-dependent preprocessing modules (i.e., M1 to M6) and designed to work entirely as an extension for Statistical Parametric Mapping (SPM).RS-FetMRI pipeline output analyses on rs-fMRI time-series sampled from a cohort of fetuses acquired on both 1.5 T and 3 T MRI scanning systems showed increased efficacy of estimation of the degree of movement coupled with an efficient motion censoring procedure, resulting in increased number of motion-uncorrupted volumes and temporal continuity in fetal rs-fMRI time-series data. Moreover, a "structural-free" SPM-based spatial normalization procedure granted a high degree of spatial overlap with high reproducibility and a significant improvement in whole-brain and parcellation-specific Temporal Signal-to-Noise Ratio (TSNR) mirrored by functional connectivity analysis.To our knowledge, the RS-FetMRI pipeline is the first semi-automatic and easy-to-use standardized fetal rs-fMRI preprocessing pipeline completely integrated in MATLAB-SPM able to remove entry barriers for new research groups into the field of fetal rs-fMRI, for both research or clinical purposes, and ultimately to make future fetal brain connectivity investigations more suitable for comparison and cross-validation.
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Mapeamento Encefálico , Imageamento por Ressonância Magnética , Humanos , Imageamento por Ressonância Magnética/métodos , Mapeamento Encefálico/métodos , Reprodutibilidade dos Testes , Descanso/fisiologia , Processamento de Imagem Assistida por Computador/métodos , Encéfalo/diagnóstico por imagem , Encéfalo/fisiologia , Feto/diagnóstico por imagemRESUMO
The aim of the present study is to investigate and compare the performances of 68Ga-PSMA and 68Ga-DOTA-RM2 PET/MRI in identifying recurrent prostate cancer (PCa) after primary treatment and to explore the association of dual-tracer PET findings with clinical and histopathological characteristics. Thirty-five patients with biochemical relapse (BCR) of PCa underwent 68Ga PSMA PET/MRI for restaging purpose, with 31/35 also undergoing 68Ga-DOTA-RM2 PET/MRI scan within 16 days (mean: 3 days, range: 2-16 days). Qualitative and quantitative image analysis has been performed by comparing 68Ga-PSMA and 68Ga-DOTA-RM2 PET/MRI findings both on a patient and lesion basis. Clinical and instrumental follow-up was used to validate PET findings. Fisher's exact test and Mann-Whitney U test were used to investigate the association between dual-tracer PET findings, clinical and histopathological data. p-value significance was defined below the 0.05 level. Patients' mean age was 70 years (range: 49-84) and mean PSA at time of PET/MR scans was 1.88 ng/mL (range: 0.21-14.4). A higher detection rate was observed for 68Ga-PSMA PET/MRI, with more lesions being detected compared to 68Ga-DOTA-RM2 PET/MRI (26/35 patients, 95 lesions vs. 15/31 patients, 41 lesions; p = 0.016 and 0.002). 68Ga-PSMA and 68Ga-DOTA-RM2 PET/MRI findings were discordant in 11/31 patients; among these, 10 were 68Ga-PSMA positive (9/10 confirmed as true positive and 1/10 as false positive by follow-up examination). Patients with higher levels of PSA and shorter PSA doubling time (DT) presented more lesions on 68Ga-PSMA PET/MRI (p = 0.006 and 0.044), while no association was found between PET findings and Gleason score. 68Ga-PSMA has a higher detection rate than 68Ga-DOTA-RM2 in detecting PCa recurrence. The number of 68Ga-PSMA PET positive lesions is associated with higher levels of PSA and shorter PSA DT, thus representing potential prognostic factors.
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AIM: The assessment of deep myometrial invasion (MI) and lymph node involvement is of utmost importance in the preoperative staging of endometrial cancer (EC). Imaging parameters derived respectively from MRI and PET have shown good predictive value. The main aim of the present study is to assess the diagnostic performance of hybrid 18F-FDG PET/MRI in EC staging, with particular focus on MI and lymphnodal involvement detection. PATIENTS AND METHODS: Prospective monocentric study including 35 patients with biopsy-proven EC undergoing preoperative 18F-FDG PET/MRI (December 2018-March 2021) for staging purpose. Histological examination was the reference standard. PET (SUVmax, SUVmean with a threshold of 40% of SUVmax-SUVmean40, metabolic tumor volume, total lesion glycolysis) and MRI (volume index [VI], total tumor volume, tumor volume ratio [TVR], mean apparent diffusion coefficient, minimum apparent diffusion coefficient) parameters were calculated on the primary tumor, and their role in predicting EC risk group, the presence of lymphovascular space invasion (LVSI), and MI was assessed. Receiver operating characteristics analysis was used to assess the predictive value of PET and MRI parameters on EC characteristics. RESULTS: Patients' median age was 66.57 years (SD, 10.21 years). 18F-FDG PET/MRI identified the primary tumor in all patients. Twenty-two of 35 patients had high-risk EC and 13/35 low-risk disease; 13/35 presented LVSI, 22/35 had deep MI at histological examination, and 13/35 had p53 hyperexpression.PET/MRI was able to detect lymphnodal involvement with high accuracy and high specificity (sensitivity of 0.8571, specificity of 0.9286, accuracy of 0.9143), also showing a high negative predictive value (NPV) for lymphnodal involvement (NPV of 0.9630, positive predictive value [PPV] of 0.7500).The assessment of deep MI using PET/MRI correctly staged 27 patients (77.1%; sensitivity of 0.7273, specificity of 0.8462, accuracy of 0.7714), with also a good PPV (PPV of 0.8889, NPV of 0.647).MRI-derived total tumor volume, VI, and TVR were significant in predicting EC groups (high-risk vs low-risk patients) (P = 0.0059, 0.0235, 0.0181, respectively). MRI-derived volume, VI, TVR, and PET-derived metabolic tumor volume and total lesion glycolysis were able to predict LVSI (P = 0.0023, 0.0068, 0.0068, 0.0027, 0.01394, respectively). Imaging was not able to predict grading, presence of deep MI, nor hyperexpression of p53. CONCLUSIONS: 18F-FDG PET/MRI has good accuracy in preoperative staging of EC; PET and MRI parameters have synergic role in preoperatively predicting LVSI, with MRI parameters being also predictive for EC risk group.
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Neoplasias do Endométrio , Tomografia por Emissão de Pósitrons , Idoso , Neoplasias do Endométrio/diagnóstico por imagem , Neoplasias do Endométrio/patologia , Feminino , Fluordesoxiglucose F18 , Humanos , Metástase Linfática/diagnóstico por imagem , Imageamento por Ressonância Magnética , Estadiamento de Neoplasias , Estudos Prospectivos , Compostos Radiofarmacêuticos , Sensibilidade e EspecificidadeRESUMO
Deep learning (DL) strategies applied to magnetic resonance (MR) images in positron emission tomography (PET)/MR can provide synthetic attenuation correction (AC) maps, and consequently PET images, more accurate than segmentation or atlas-registration strategies. As first objective, we aim to investigate the best MR image to be used and the best point of the AC pipeline to insert the synthetic map in. Sixteen patients underwent a 18F-fluorodeoxyglucose (FDG) PET/computed tomography (CT) and a PET/MR brain study in the same day. PET/CT images were reconstructed with attenuation maps obtained: (1) from CT (reference), (2) from MR with an atlas-based and a segmentation-based method and (3) with a 2D UNet trained on MR image/attenuation map pairs. As for MR, T1-weighted and Zero Time Echo (ZTE) images were considered; as for attenuation maps, CTs and 511 keV low-resolution attenuation maps were assessed. As second objective, we assessed the ability of DL strategies to provide proper AC maps in presence of cranial anatomy alterations due to surgery. Three 11C-methionine (METH) PET/MR studies were considered. PET images were reconstructed with attenuation maps obtained: (1) from diagnostic coregistered CT (reference), (2) from MR with an atlas-based and a segmentation-based method and (3) with 2D UNets trained on the sixteen FDG anatomically normal patients. Only UNets taking ZTE images in input were considered. FDG and METH PET images were quantitatively evaluated. As for anatomically normal FDG patients, UNet AC models generally provide an uptake estimate with lower bias than atlas-based or segmentation-based methods. The intersubject average bias on images corrected with UNet AC maps is always smaller than 1.5%, except for AC maps generated on too coarse grids. The intersubject bias variability is the lowest (always lower than 2%) for UNet AC maps coming from ZTE images, larger for other methods. UNet models working on MR ZTE images and generating synthetic CT or 511 keV low-resolution attenuation maps therefore provide the best results in terms of both accuracy and variability. As for METH anatomically altered patients, DL properly reconstructs anatomical alterations. Quantitative results on PET images confirm those found on anatomically normal FDG patients.
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Fluordesoxiglucose F18 , Tomografia por Emissão de Pósitrons combinada à Tomografia Computadorizada , Encéfalo/anatomia & histologia , Encéfalo/diagnóstico por imagem , Humanos , Processamento de Imagem Assistida por Computador/métodos , Imageamento por Ressonância Magnética/métodos , Imagem Multimodal/métodos , Tomografia por Emissão de Pósitrons/métodosRESUMO
We present the current clinical applications of radiomics in the context of prostate cancer (PCa) management. Several online databases for original articles using a combination of the following keywords: "(radiomic or radiomics) AND (prostate cancer or prostate tumour or prostate tumor or prostate neoplasia)" have been searched. The selected papers have been pooled as focus on (i) PCa detection, (ii) assessing the clinical significance of PCa, (iii) biochemical recurrence prediction, (iv) radiation-therapy outcome prediction and treatment efficacy monitoring, (v) metastases detection, (vi) metastases prediction, (vii) prediction of extra-prostatic extension. Seventy-six studies were included for qualitative analyses. Classifiers powered with radiomic features were able to discriminate between healthy tissue and PCa and between low- and high-risk PCa. However, before radiomics can be proposed for clinical use its methods have to be standardized, and these first encouraging results need to be robustly replicated in large and independent cohorts.
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Imageamento por Ressonância Magnética , Neoplasias da Próstata , Humanos , Masculino , Neoplasias da Próstata/diagnóstico por imagem , Neoplasias da Próstata/terapiaRESUMO
The aim of the present study is to investigate the synergic role of 68Ga-PSMA PET/MRI and 68Ga-DOTA-RM2 PET/MRI in prostate cancer (PCa) staging. We present pilot data on twenty-two patients with biopsy-proven PCa that underwent 68Ga-PSMA PET/MRI for staging purposes, with 19/22 also undergoing 68Gaa-DOTA-RM2 PET/MRI. TNM classification based on image findings was performed and quantitative imaging parameters were collected for each scan. Furthermore, twelve patients underwent radical prostatectomy with the availability of histological data that were used as the gold standard to validate intraprostatic findings. A DICE score between regions of interest manually segmented on the primary tumour on 68Ga-PSMA PET, 68Ga-DOTA-RM2 PET and on T2 MRI was computed. All imaging modalities detected the primary PCa in 18/19 patients, with 68Ga-DOTA-RM2 PET not detecting any lesion in 1/19 patients. In the remaining patients, 68Ga-PSMA and MRI were concordant. Seven patients presented seminal vesicles involvement on MRI, with two of these being also detected by 68Ga-PSMA, and 68Ga-DOTA-RM2 PET being negative. Regarding extraprostatic disease, 68Ga-PSMA PET, 68Ga-DOTA-RM2 PET and MRI resulted positive in seven, four and five patients at lymph-nodal level, respectively, and at a bone level in three, zero and one patients, respectively. These preliminary results suggest the potential complementary role of 68Ga-PSMA PET, 68Ga-DOTA-RM2 PET and MRI in PCa characterization during the staging phase.
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Motion perception deficits in dyslexia show a large intersubjective variability, partly reflecting genetic factors influencing brain architecture development. In previous work, we have demonstrated that dyslexic carriers of a mutation of the DCDC2 gene have a very strong impairment in motion perception. In the present study, we investigated structural white matter alterations associated with the poor motion perception in a cohort of twenty dyslexics with a subgroup carrying the DCDC2 gene deletion (DCDC2d+) and a subgroup without the risk variant (DCDC2d-). We observed significant deficits in motion contrast sensitivity and in motion direction discrimination accuracy at high contrast, stronger in the DCDC2d+ group. Both motion perception impairments correlated significantly with the fractional anisotropy in posterior ventral and dorsal tracts, including early visual pathways both along the optic radiation and in proximity of occipital cortex, MT and VWFA. However, the DCDC2d+ group showed stronger correlations between FA and motion perception impairments than the DCDC2d- group in early visual white matter bundles, including the optic radiations, and in ventral pathways located in the left inferior temporal cortex. Our results suggest that the DCDC2d+ group experiences higher vulnerability in visual motion processing even at early stages of visual analysis, which might represent a specific feature associated with the genotype and provide further neurobiological support to the visual-motion deficit account of dyslexia in a specific subpopulation.
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Dislexia , Percepção de Movimento , Substância Branca , Dislexia/diagnóstico por imagem , Dislexia/genética , Humanos , Proteínas Associadas aos Microtúbulos , Lobo Occipital , Vias Visuais , Percepção Visual , Substância Branca/diagnóstico por imagemRESUMO
Axillary surgery in breast cancer (BC) is no longer a therapeutic procedure but has become a purely staging procedure. The progressive improvement in imaging techniques has paved the way to the hypothesis that prognostic information on nodal status deriving from surgery could be obtained with an accurate diagnostic exam. Positron emission tomography/magnetic resonance imaging (PET/MRI) is a relatively new imaging tool and its role in breast cancer patients is still under investigation. We reviewed the available literature on PET/MRI in BC patients. This overview showed that PET/MRI yields a high diagnostic performance for the primary tumor and distant lesions of liver, brain and bone. In particular, the results of PET/MRI in staging the axilla are promising. This provided the rationale for two prospective comparative trials between axillary surgery and PET/MRI that could lead to a further de-escalation of surgical treatment of BC. ⢠SNB vs. PET/MRI 1 trial compares PET/MRI and axillary surgery in staging the axilla of BC patients undergoing primary systemic therapy (PST). ⢠SNB vs. PET/MRI 2 trial compares PET/MRI and sentinel node biopsy (SNB) in staging the axilla of early BC patients who are candidates for upfront surgery. Finally, these ongoing studies will help clarify the role of PET/MRI in BC and establish whether it represents a useful diagnostic tool that could guide, or ideally replace, axillary surgery in the future.
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BACKGROUND: To investigate the correlation between 18F-labeled fluoroazomycinarabinoside (18F-FAZA) PET data and hypoxia immunohistochemical markers in patients with high-grade glioma (HGG). PATIENTS AND METHODS: Prospective study including 20 patients with brain MRI suggestive for HGG and undergoing 18F-FAZA PET/CT before treatment for hypoxia assessment. For each 18F-FAZA PET scan SUVmax, SUVmean and 18F-FAZA tumour volume (FTV) at 40, 50 and 60% threshold of SUVmax were calculated; hypoxic volume was estimated by applying different thresholds (1.2, 1.3 and 1.4) to tumour/blood ratio. Seventeen patients were analysed. The immunohistochemical analysis assessed the following parameters: hypoxia-inducible factor 1α, carbonic anhydrase IX (CA-IX), glucose transporter-1, tumour vascularity and Ki-67. RESULTS: 18F-FAZA PET showed a single lesion in 15/17 patients and multiple lesions in 2/17 patients. Twelve/17 patients had grade IV glioma and 5/17 with grade III glioma. Bioptic and surgical samples have been analysed separately. In the surgical subgroup (n = 7) a positive correlation was observed between CA-IX and SUVmax (P = 0.0002), SUVmean40 (P = 0.0058), SUVmean50 (P = 0.009), SUVmean60 (P = 0.0153), FTV-40-50-60 (P = 0.0424) and hypoxic volume1.2-1.3-1.4 (P = 0.0058). In the bioptic group (n = 10) tumour vascularisation was inversely correlated with SUVmax (P = 0.0094), SUVmean40 (P = 0.0107), SUVmean50 (P = 0.0094) and SUVmean60 (P = 0.0154). CONCLUSIONS: The correlation of 18F-FAZA PET parameters with CD31 and CA-IX represents a reliable method for assessing tumour hypoxia in HGG. The inverse correlation between tumour vascularisation, SUVmax and SUVmean suggest that highly vascularized tumours might present more oxygen supply than hypoxia.
Assuntos
Nitroimidazóis , Tomografia por Emissão de Pósitrons combinada à Tomografia Computadorizada , Adulto , Humanos , Masculino , Pessoa de Meia-Idade , Tomografia por Emissão de PósitronsRESUMO
Preterm birth can affect cognitive functions, such as attention or more generally executive control mechanisms, with severity in impairments proportional to prematurity. The functional cross-talk between the Default Mode (DMN) and Executive Control (ECN) networks mirrors the integrity of cognitive processing and is directly related to brain development. In this study, a cohort of 20 preterm-born infants was investigated using rs-fMRI. First, we addressed biological maturity of the DMN per se and its interplay with the ECN in terms of patterns of increased functional connectivity. Second, we assessed the impact of the degree of prematurity on the DMN-ECN functional interplay development in relation to cognitive outcome at six months. Our results highlighted the emergence of DMN in preterm neonates, with connectivity strength and synchronization between the anterior DMN hub and frontal areas increasing as a function of biological maturity. Further, cognitive scores at 6 months were predicted by mPFC-ECN connectivity strength with degree of prematurity impacting on mPFC-ECN connectivity and triggering differential patterns of functional maturation of the ECN for very early/early and moderate/late preterm neonates. Our findings suggest that the prematurity window allows to observe precursors of functional plasticity that may underlie different developmental trajectories in preterm children.
Assuntos
Função Executiva , Nascimento Prematuro , Encéfalo/diagnóstico por imagem , Mapeamento Encefálico , Criança , Cognição , Feminino , Humanos , Lactente , Recém-Nascido , Imageamento por Ressonância Magnética , GravidezRESUMO
BACKGROUND: MR Tractography enables non-invasive preoperative depiction of language subcortical tracts, which is crucial for the presurgical work-up of brain tumors; however, it cannot evaluate the exact function of the fibers. PURPOSE: A systematic pipeline was developed to combine tractography reconstruction of language fiber bundles, based on anatomical landmarks (Anatomical-T), with language fMRI cortical activations. A fMRI-targeted Tractography (fMRI-T) was thus obtained, depicting the subsets of the anatomical tracts whose endpoints are located inside a fMRI activation. We hypothesized that fMRI-T could provide additional functional information regarding the subcortical structures, better reflecting the eloquent white matter structures identified intraoperatively. METHODS: Both Anatomical-T and fMRI-T of language fiber tracts were performed on 16 controls and preoperatively on 16 patients with left-hemisphere brain tumors, using a q-ball residual bootstrap algorithm based on High Angular Resolution Diffusion Imaging (HARDI) datasets (b = 3000 s/mm2; 60 directions); fMRI ROIs were obtained using picture naming, verbal fluency, and auditory verb generation tasks. In healthy controls, normalized MNI atlases of fMRI-T and Anatomical-T were obtained. In patients, the surgical resection of the tumor was pursued by identifying eloquent structures with intraoperative direct electrical stimulation mapping and extending surgery to the functional boundaries. Post-surgical MRI allowed to identify Anatomical-T and fMRI-T non-eloquent portions removed during the procedure. RESULTS: MNI Atlases showed that fMRI-T is a subset of Anatomical-T, and that different task-specific fMRI-T involve both shared subsets and task-specific subsets - e.g., verbal fluency fMRI-T strongly involves dorsal frontal tracts, consistently with the phonogical-articulatory features of this task. A quantitative analysis in patients revealed that Anatomical-T removed portions of AF-SLF and IFOF were significantly greater than verbal fluency fMRI-T ones, suggesting that fMRI-T is a more specific approach. In addition, qualitative analyses showed that fMRI-T AF-SLF and IFOF predict the exact functional limits of resection with increased specificity when compared to Anatomical-T counterparts, especially the superior frontal portion of IFOF, in a subcohort of patients. CONCLUSION: These results suggest that performing fMRI-T in addition to the 'classic' Anatomical-T may be useful in a preoperative setting to identify the 'high-risk subsets' that should be spared during the surgical procedure.