Brain Metabolic Profile in Presymptomatic GRN Carriers Throughout a 5-Year Follow-up

BACKGROUND AND OBJECTIVES

GRN variants are a frequent cause of familial frontotemporal dementia (FTD). Monitoring disease progression in asymptomatic carriers of genetic variants is a major challenge in delivering preventative therapies before clinical onset. This study aimed to assess the usefulness of fluorodeoxyglucose (FDG)-PET in identifying metabolic changes in presymptomatic GRN carriers (PS-GRN+) and to trace their longitudinal progression.

METHODS

Participants were longitudinally evaluated over 5 years in a prospective cohort study focused on GRN disease (Predict-PGRN). They underwent cognitive/behavioral assessment, plasma neurofilament measurement, brain MRI, and FDG-PET. Voxel-wise comparisons of structural and metabolic imaging data between 2 groups were performed for each time point. Longitudinal PET changes were evaluated with voxel-wise comparisons and the metabolic percent annual changes method. The association of regional brain metabolism with plasma neurofilament and cognitive changes was analyzed.

RESULTS

Among the 80 individuals enrolled in the study, 58 (27 PS-GRN+ and 31 noncarriers) were included in the analyses. Cross-sectional comparisons between PS-GRN+ and controls found a significant hypometabolism in the left superior temporal sulcus (STS) region (encompassing the middle and superior temporal gyri), approximately 15 years before the expected disease onset, without significant cortical atrophy. The longitudinal metabolic decline over the following 5 years peaked around the right STS in carriers (p < 0.001), without significantly greater volume loss compared with that in controls. Their estimated annualized metabolic decrease (-1.37%) was higher than that in controls (-0.21%, p = 0.004). Lower glucose uptake was associated with higher neurofilament increase (p = 0.003) and lower frontal cognitive scores (p = 0.014) in PS-GRN+.

DISCUSSION

This study detected brain metabolic changes in the STS region, preceding structural and cognitive alterations, thus contributing to the characterization of the pathochronology of preclinical GRN disease. Owing to the STS involvement in the perception of facially communicated cues, it is likely that its dysfunction contributes to social cognition deficits characterizing FTD. Overall, our study highlights brain metabolic changes as an early disease-tracking biomarker and proposes annualized percent decrease as a metric to monitor therapeutic response in forthcoming trials.

Respiratory gated multistatic PET reconstructions to delineate radiotherapy target volume in patients with mobile lung tumors

BACKGROUND

PET-CT with ¹⁸F-FDG or other radiopharmaceuticals is a recommended tool to help the delineation of lung cancers candidate to radiotherapy. The motion artifacts caused by respiratory movements are reduced by 4D acquisitions. We introduced an extended reconstruction algorithm (multiple reconstruct register and average [multi-RRA]) which requires much shorter acquisition times than standard 4D PET-CT. Our aim was to evaluate the interest on multi-RRA images as an alternative of 3D and 4D PET-CT for the delineation of lung lesion.

METHODS

PET acquisitions synchronized to the respiratory signal were obtained in 18 patients with mobile lung tumors. We compared the tumor volumes delineated on Multi-RRA images to 3D and 4D PET-CT, considering the 4D CT as a reference. The tumor volumes were delineated and compared with topologic similarity indexes (Dice, Jaccard and overlap).

RESULTS

Twenty tumors were delineated. The volumes delineated with multi-RRA and 4D PET were not significantly different (mean difference of 0.2±0.7 mL). Comparison by pairs (Tukey-Kramer test) showed that 3D-PET volumes were significantly smaller than 4D-PET and multi-RRA volumes (P<0.001). Topologic similarity indexes with 4D-PET were slightly statistically higher with multi-RRA than with 3D-PET (Dice and Jaccard) or 4D-CT (Dice, Jaccard and Overlap).

CONCLUSIONS

The tumor volumes delineated on multi-RRA are similar to the volumes obtained with 4D PET, with shorter acquisition time.

Nucleus Basalis of Meynert Stimulation for Lewy Body Dementia: A Phase I Randomized Clinical Trial

OBJECTIVES

Nucleus basalis of Meynert deep brain stimulation (NBM-DBS) has been proposed for patients with dementia. Here, we aim to assess the safety and effects of NBM-DBS in patients with Lewy body dementia (LBD), in a randomized, double-blind, crossover clinical trial.

METHODS

Six patients with mild to moderate LBD (mean [SD] age, 62.2 [7.8] years) were included, operated on for bilateral NBM-DBS, and assigned to receive either active or sham NBM-DBS followed by the opposite condition for 3 months. The primary outcome was the difference in the total free recalls of the Free and Cued Selective Reminding Test (FCSRT) between active and sham NBM-DBS. Secondary outcomes were assessments of the safety and effects of NBM-DBS on cognition, motor disability, sleep, and PET imaging.

RESULTS

There was no significant difference in the FCSRT score with active vs sham NBM-DBS. The surgical procedures were well tolerated in all patients, but we observed significant decreases in Stroop and Benton scores after electrode implantation. We observed no significant difference in other scales between active and sham NBM-DBS. With active NBM-DBS relative to baseline, phonemic fluency and motor disability significantly decreased. Lastly, the superior lingual gyrus metabolic activity significantly increased with active NBM-DBS.

CONCLUSIONS

NBM-DBS does not appear to be totally safe for patients with LBD with no evidence of cognitive benefit.

CLINICALTRIALSGOV IDENTIFIER

NCT01340001.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that, for patients with LBD operated on for bilateral NBM-DBS, active NBM-DBS stimulation compared to sham stimulation did not significantly change selective recall scores.

Spotting L3 slice in CT scans using deep convolutional network and transfer learning

In this article, we present a complete automated system for spotting a particular slice in a complete 3D Computed Tomography exam (CT scan). Our approach does not require any assumptions on which part of the patient's body is covered by the scan. It relies on an original machine learning regression approach. Our models are learned using the transfer learning trick by exploiting deep architectures that have been pre-trained on imageNet database, and therefore it requires very little annotation for its training. The whole pipeline consists of three steps: i) conversion of the CT scans into Maximum Intensity Projection (MIP) images, ii) prediction from a Convolutional Neural Network (CNN) applied in a sliding window fashion over the MIP image, and iii) robust analysis of the prediction sequence to predict the height of the desired slice within the whole CT scan. Our approach is applied to the detection of the third lumbar vertebra (L3) slice that has been found to be representative to the whole body composition. Our system is evaluated on a database collected in our clinical center, containing 642 CT scans from different patients. We obtained an average localization error of 1.91±2.69 slices (less than 5 mm) in an average time of less than 2.5 s/CT scan, allowing integration of the proposed system into daily clinical routines.

Clinical respiratory motion correction software (reconstruct, register and averaged-RRA), for 18F-FDG-PET-CT: phantom validation, practical implications and patient evaluation

OBJECTIVE

On fluorine-18 fludeoxyglucose (¹⁸F-FDG) positron emission tomography (PET) CT of pulmonary or hepatic lesions, standard uptake value (SUV) is often underestimated due to patient breathing. The aim of this study is to validate, on phantom and patient data, a motion correction algorithm [reconstruct, register and averaged (RRA)] implemented on a PET-CT system.

METHODS

Three phantoms containing five spheres filled with ¹⁸F-FDG and suspended in a water or Styrofoam^®18F-FDG-filled tank to create different contrasts and attenuation environment were acquired on a Discovery GE710. The spheres were animated with a 2-cm longitudinal respiratory-based movement. Respiratory-gated (RRA) and ungated PET images were compared with static reference images (without movement). The optimal acquisition time, number of phases and the best phase within the respiratory cycle were investigated. The impact of irregular motion was also investigated. Quantification impact was computed on each sphere. Quantification improvement on 28 lung lesions was also investigated.

RESULTS

Phantoms: 4 min was required to obtain a stable quantification with the RRA method. The reference phase and the number of phases used for RRA did not affect the quantification which was similar on static acquisitions but different on ungated images. The results showed that the maximum standard uptake value (SUV_max) restoration is majored for the smallest spheres (≤2.1 ml).

PATIENTS

SUV_max on RRA and ungated acquisitions were statistically different to the SUV_max on whole-body images (p = 0.05) but not different from each other (mean SUV_max: 7.0 ± 7.8 vs 6.9 ± 7.8, p = 0.23 on RRA and ungated images, respectively). We observed a statistically significant correlation between SUV restoration and lesion displacement, with a real SUV quantitation improvement for lesion with movement >1.2 mm.

CONCLUSION

According to the results obtained using phantoms, RRA method is promising, showing a real impact on the lesion quantification on phantom data. With regard to the patient study, our results showed a trend towards an increase in the SUVs and a decrease in the volume between the ungated and RRA data. We also noticed a statistically significant correlation between the quantitative restoration obtained with RRA compared with ungated data and lesion displacement, indicating that the RRA approach should be reserved to patients with small lesions or nodes moving with a displacement larger than 1.2 cm. Advances in knowledge: This article investigates the performances of motion correction software recently introduced in PET. The conclusion revealed that such respiratory motion correction approach shows a real impact on the lesion quantification but must be reserved to the patient for whom lesion displacement was confirmed and high enough to clearly impact lesion evaluation.

[Prognostic value of pretherapeutic 18F-FDG PET/CT in cancer of the uterine cervix: a retrospective study of 53 patients]

OBJECTIVES

Assessment of prognostic value of pretherapeutic (18)F-FDG PET/CT (PET).

PATIENTS AND METHODS

Retrospective study of 53 patients with invasive uterine cervix carcinoma. Each patient has been evaluated with pretherapeutic whole-body FDG PET/CT and pelvic MRI. Minimal follow-up lasted for 1 year. On PET/CT, we have visually analyzed metabolism of primary tumor, pelvic and para-aortic lymph nodes in comparison with surrounding structures. We have compared prognostic factors as pretherapeutic haemoglobin rate, FIGO staging, MRI and PET/CT data using Mann-Whitney univariate analysis and Cox multivariate analysis.

RESULTS

Para-aortic lymph node abnormal uptake on PET/CT was the only independent predictor of progression-free survival. Pelvic lymph node involvement on PET/CT was the only independent predictor of overall survival. MRI did not provide any additional information.

DISCUSSION AND CONCLUSION

Lymph node involvement visually assessed by (18)F-FDG PET/CT was the most significant prognostic factor for overall and progression-free survival.