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BackgroundMR 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.PurposeA 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.MethodsBoth 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.ResultsMNI 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.ConclusionThese 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.

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

New complex tissue microstructure estimators have been presented recently in order to elucidate white matter fibre orientations. Since these algorithms are based on the diffusion-weighted signal profile, the estimations are affected by noise arte-facts. The proven robustness of these methods cannot counteract distortions since the statistical Rician behavior has not been taken into account. In this study, two techniques to counteract the noise distortions are presented to improve the fibre orientation estimations. Simulations and in vivo experiments show an improvement in the angular resolution and convergence of the results. One of these strategies represents a good compromise between computational cost and result improvements. Index Terms--Diffusion tensor imaging (DTI), high angular resolution diffusion imaging (HARDI), orientation estimators, Rician noise.

A deconvolution approach is presented to solve fiber crossing in diffusion magnetic resonance imaging. In order to provide a direct physical interpretation of the signal generation process, we started from the classical multicompartment model and rewrote this in terms of a convolution process, identifying a significant scalar parameter [alpha] to characterize the physical system response. Deconvolution is performed by a modified version of the Richardson-Lucy algorithm. Simulations show the ability of this method to correctly separate fiber crossing, even in the presence of noisy data, with lower signal-to-noise ratio, and imprecision in the impulse response function imposed during deconvolution. The in vivo data confirms the efficacy of this method to resolve fiber crossing in real complex brain structures. These results suggest the usefulness of our approach in fiber tracking or connectivity studies. Index Terms--DTI, DW-MRI, fiber crossing, HARDI, multicompartment model, Richardson-Lucy algorithm, spherical deconvolution.

Obese adolescents are at risk of developing NAFLD and type 2 diabetes. We measured noninvasively the IHF content of obese adolescents to ascertain whether it is associated with insulin resistance and abnormal energy homeostasis. IHF content, whole body energy homeostasis, insulin sensitivity, and body composition were measured using localized hepatic [sup.1]H-MRS, indirect calorimetry, fasting-derived and 3-h-OGTT-derived surrogate indexes (HOMA2 and WBISI), and DEXA, respectively, in 54 obese adolescents (24 female and 30 male, age 13 [+ or -] 2 yr, BMI >99th percentile for their age and sex). NAFLD (defined as IHF content >5 % wet weight) was found in 16 individuals (30%) in association with higher ALT (P < 0.006), Hb [A.sub.1c] (P = 0.021), trunk fat content (P < 0.03), and lower HDL cholesterol (P < 0.05). Individuals with NAFLD had higher fasting plasma glucose (89 [+ or -] 8 vs. 83 [+ or -] 9 mg/dl, P = 0.01) and impaired insulin sensitivity (HOMA2 and WBISI, P < 0.05). Meanwhile, parameters of insulin secretion were unaffected. Their reliance on fat oxidation in the fasting state was lower (RQ 0.83 [+ or -] 0.08 vs. 0.77 [+ or -] 0.05, P < 0.01), and their ability to suppress it during the oral glucose challenge was impaired (P < 0.05) vs. those with normal IHF content. When controlling for trunk fat content, the correlation between IHF content and insulin sensitivity was weakened, whereas the correlation with fasting lipid oxidation was maintained. In conclusion, NAFLD is common in childhood obesity, and insulin resistance is present in association with increased trunk fat content. In contrast, the rearrangement of whole body substrate oxidation in these youngsters appeared to be an independent feature. nonalcoholic fatty liver disease; fat oxidation; 1H magnetic resonance spectroscopy; indirect calorimetry; oral glucose tolerance test.

Antiretroviral therapy in human immunodeficiency virus (HIV)-positive patients can induce a lipodystrophy syndrome of peripheral fat wasting and central adiposity, dyslipidemia, and insulin resistance. To test whether in this syndrome insulin resistance is associated with abnormal muscle handling of fatty acids, 12 HIV-1 patients (8 females/4 males, age = 26 [+ or -] 2 yr, HIV duration = 8 [+ or -] yr, body mass index = 22.0 [+ or -] 1.0 kg/[m.sup.2], on protease inhibitors and nucleoside analog RT inhibitors) and 12 healthy subjects were studied. HIV-1 patients had a total body fat content (assessed by dual-energy X-ray absorptiometry) similar to that of controls (22 [+ or -] 1 vs. 23 [+ or -] 2%; P = 0.56), with a topographic fat redistribution characterized by reduced fat content in the legs (18 [+ or -] 2 vs. 32 [+ or -] 3%; P < 0.01) and increased fat content in the trunk (25 [+ or -] 2 vs. 19 [+ or -] 2%; P = 0.03). In HIV-positive patients, insulin sensitivity (assessed by QUICKI) was markedly impaired (0.341 [+ or -] 0.011 vs. 0.376 [+ or -] 0.007; P = 0.012). HIV-positive patients also had increased total plasma cholesterol (216 [+ or -] 20 vs. 174 [+ or -] 9 mg/dl; P = 0.05) and triglyceride (298 [+ or -] 96 vs. 87 [+ or -] 11 mg/dl; P = 0.03) concentrations. Muscular triglyceride content assessed by means of [sup.1]H NMR spectroscopy was higher in HIV patients in soleus [92 [+ or -] 12 vs. 42 [+ or -] 5 arbitrary units (AU); P < 0.01] and tibialis anterior (26 [+ or -] 6 vs. 11 [+ or -] 3 AU; P = 0.04) muscles; in a stepwise regression analysis, it was strongly associated with QUICKI ([R.sup.2] = 0.27; P < 0.0093). Even if the basal metabolic rate (assessed by indirect calorimetry) was comparable to that of normal subjects, postabsorptive lipid oxidation was significantly impaired (0.30 [+ or -] 0.07 vs. 0.88 [+ or -] 0.09 mg * [kg.sup.-1] * [min.sup.-1]; P < 0.01). In conclusion, lipodystrophy in HIV-1 patients in antiretroviral treatment is associated with intramuscular fat accumulation, which may mediate the development of the insulin resistance syndrome. human immunodeficiency virus