Covid-19 related cognitive, structural and functional brain changes among Italian adolescents and young adults: a multimodal longitudinal case-control study.

Coronavirus disease 2019 (COVID-19) has been associated with brain functional, structural, and cognitive changes that persist months after infection. Most studies of the neurologic outcomes related to COVID-19 focus on severe infection and aging populations. Here, we investigated the neural activities underlying COVID-19 related outcomes in a case-control study of mildly infected youth enrolled in a longitudinal study in Lombardy, Italy, a global hotspot of COVID-19. All participants (13 cases, 27 controls, mean age 24 years) completed resting state functional (fMRI), structural MRI, cognitive assessments (CANTAB spatial working memory) at baseline (pre-COVID) and follow-up (post-COVID). Using graph theory eigenvector centrality (EC) and data-driven statistical methods, we examined differences in ECdelta (i.e., the difference in EC values pre- and post-COVID-19) and volumetricdelta (i.e., the difference in cortical volume of cortical and subcortical areas pre- and post-COVID) between COVID-19 cases and controls. We found that ECdeltasignificantly between COVID-19 and healthy participants in five brain regions; right intracalcarine cortex, right lingual gyrus, left hippocampus, left amygdala, left frontal orbital cortex. The left hippocampus showed a significant decrease in volumetricdelta between groups (p=0.041). The reduced ECdelta in the right amygdala associated with COVID-19 status mediated the association between COVID-19 and disrupted spatial working memory. Our results show persistent structural, functional and cognitive brain changes in key brain areas associated with olfaction and cognition. These results may guide treatment efforts to assess the longevity, reversibility and impact of the observed brain and cognitive changes following COVID-19.

Early-Life Critical Windows of Susceptibility to Manganese Exposure and Sex-Specific Changes in Brain Connectivity in Late Adolescence.

Background: Early-life environmental exposures during critical windows (CWs) of development can impact life course health. Exposure to neuroactive metals such as manganese (Mn) during prenatal and early postnatal CWs may disrupt typical brain development, leading to persistent behavioral changes. Males and females may be differentially vulnerable to Mn, presenting distinctive CWs to Mn exposure. Methods: We used magnetic resonance imaging to investigate sex-specific associations between early-life Mn uptake and intrinsic functional connectivity in adolescence. A total of 71 participants (15-23 years old; 53% female) from the Public Health Impact of Manganese Exposure study completed a resting-state functional magnetic resonance imaging scan. We estimated dentine Mn concentrations at prenatal, postnatal, and early childhood periods using laser ablation-inductively coupled plasma-mass spectrometry. We performed seed-based correlation analyses to investigate the moderating effect of sex on the associations between Mn and intrinsic functional connectivity adjusting for age and socioeconomic status. Results: We identified significant sex-specific associations between dentine Mn at all time points and intrinsic functional connectivity in brain regions involved in cognitive and motor function: 1) prenatal: dorsal striatum, occipital/frontal lobes, and middle frontal gyrus; 2) postnatal: right putamen and cerebellum; and 3) early childhood: putamen and occipital, frontal, and temporal lobes. Network associations differed depending on exposure timing, suggesting that different brain networks may present distinctive CWs to Mn. Conclusions: These findings suggest that the developing brain is vulnerable to Mn exposure, with effects lasting through late adolescence, and that females and males are not equally vulnerable to these effects. Future studies should investigate cognitive and motor outcomes related to these associations.

Neuro-Environmental Interactions: a time sensitive matter.

The assessment of resting state (rs) neurophysiological dynamics relies on the control of sensory, perceptual, and behavioral environments to minimize variability and rule-out confounding sources of activation during testing conditions. Here, we investigated how temporally-distal environmental inputs, specifically metal exposures experienced up to several months prior to scanning, affect functional dynamics measured using rs functional magnetic resonance imaging (rs-fMRI). We implemented an interpretable XGBoost-Shapley Additive Explanation (SHAP) model that integrated information from multiple exposure biomarkers to predict rs dynamics in typically developing adolescents. In 124 participants (53% females, ages: 13-25 years) enrolled in the Public Health Impact of Metals Exposure (PHIME) study, we measured concentrations of six metals (manganese, lead, chromium, cupper, nickel and zinc) in biological matrices (saliva, hair, fingernails, toenails, blood and urine) and acquired rs-fMRI scans. Using graph theory metrics, we computed global efficiency (GE) in 111 brain areas (Harvard Oxford Atlas). We used a predictive model based on ensemble gradient boosting to predict GE from metal biomarkers, adjusting for age and biological sex. Model performance was evaluated by comparing predicted versus measured GE. SHAP scores were used to evaluate feature importance. Measured versus predicted rs dynamics from our model utilizing chemical exposures as inputs were significantly correlated ( p < 0.001, r = 0.36). Lead, chromium, and copper contributed most to the prediction of GE metrics. Our results indicate that a significant component of rs dynamics, comprising approximately 13% of observed variability in GE, is driven by recent metal exposures. These findings emphasize the need to estimate and control for the influence of past and current chemical exposures in the assessment and analysis of rs functional connectivity.

Topological network properties of resting-state functional connectivity patterns are associated with metal mixture exposure in adolescents.

Introduction: Adolescent exposure to neurotoxic metals adversely impacts cognitive, motor, and behavioral development. Few studies have addressed the underlying brain mechanisms of these metal-associated developmental outcomes. Furthermore, metal exposure occurs as a mixture, yet previous studies most often consider impacts of each metal individually. In this cross-sectional study, we investigated the relationship between exposure to neurotoxic metals and topological brain metrics in adolescents. Methods: In 193 participants (53% females, ages: 15-25 years) enrolled in the Public Health Impact of Metals Exposure (PHIME) study, we measured concentrations of four metals (manganese, lead, copper, and chromium) in multiple biological media (blood, urine, hair, and saliva) and acquired resting-state functional magnetic resonance imaging scans. Using graph theory metrics, we computed global and local efficiency (global:GE; local:LE) in 111 brain areas (Harvard Oxford Atlas). We used weighted quantile sum (WQS) regression models to examine association between metal mixtures and each graph metric (GE or LE), adjusted for sex and age. Results: We observed significant negative associations between the metal mixture and GE and LE [ßGE = -0.076, 95% CI (-0.122, -0.031); ßLE= -0.051, 95% CI (-0.095, -0.006)]. Lead and chromium measured in blood contributed most to this association for GE, while chromium measured in hair contributed the most for LE. Discussion: Our results suggest that exposure to this metal mixture during adolescence reduces the efficiency of integrating information in brain networks at both local and global levels, informing potential neural mechanisms underlying the developmental toxicity of metals. Results further suggest these associations are due to combined joint effects to different metals, rather than to a single metal.

Neuro-environmental interactions: a time sensitive matter.

Introduction: The assessment of resting state (rs) neurophysiological dynamics relies on the control of sensory, perceptual, and behavioral environments to minimize variability and rule-out confounding sources of activation during testing conditions. Here, we investigated how temporally-distal environmental inputs, specifically metal exposures experienced up to several months prior to scanning, affect functional dynamics measured using rs functional magnetic resonance imaging (rs-fMRI). Methods: We implemented an interpretable XGBoost-shapley additive explanation (SHAP) model that integrated information from multiple exposure biomarkers to predict rs dynamics in typically developing adolescents. In 124 participants (53% females, ages, 13-25 years) enrolled in the public health impact of metals exposure (PHIME) study, we measured concentrations of six metals (manganese, lead, chromium, copper, nickel, and zinc) in biological matrices (saliva, hair, fingernails, toenails, blood, and urine) and acquired rs-fMRI scans. Using graph theory metrics, we computed global efficiency (GE) in 111 brain areas (Harvard Oxford atlas). We used a predictive model based on ensemble gradient boosting to predict GE from metal biomarkers, adjusting for age and biological sex. Results: Model performance was evaluated by comparing predicted versus measured GE. SHAP scores were used to evaluate feature importance. Measured versus predicted rs dynamics from our model utilizing chemical exposures as inputs were significantly correlated (p < 0.001, r = 0.36). Lead, chromium, and copper contributed most to the prediction of GE metrics. Discussion: Our results indicate that a significant component of rs dynamics, comprising approximately 13% of observed variability in GE, is driven by recent metal exposures. These findings emphasize the need to estimate and control for the influence of past and current chemical exposures in the assessment and analysis of rs functional connectivity.

Targeting Default Mode Network Dysfunction in Persons at Risk of Alzheimer's Disease with Transcranial Magnetic Stimulation (NEST4AD): Rationale and Study Design.

BACKGROUND: Default mode network (DMN) dysfunction is well established in Alzheimer's disease (AD) and documented in both preclinical stages and at-risk subjects, thus representing a potential disease target. Multi-sessions of repetitive transcranial magnetic stimulation (rTMS) seem capable of modulating DMN dynamics and memory in healthy individuals and AD patients; however, the potential of this approach in at-risk subjects has yet to be tested. OBJECTIVE: This study will test the effect of rTMS on the DMN in healthy older individuals carrying the strongest genetic risk factor for AD, the Apolipoprotein E (APOE) ɛ4 allele. METHODS: We will recruit 64 older participants without cognitive deficits, 32 APOE ɛ4 allele carriers and 32 non-carriers as a reference group. Participants will undergo four rTMS sessions of active (high frequency) or sham DMN stimulation. Multimodal imaging exam (including structural, resting-state, and task functional MRI, and diffusion tensor imaging), TMS with concurrent electroencephalography (TMS-EEG), and cognitive assessment will be performed at baseline and after the stimulation sessions. RESULTS: We will assess changes in DMN connectivity with resting-state functional MRI and TMS-EEG, as well as changes in memory performance in APOE ɛ4 carriers. We will also investigate the mechanisms underlying DMN modulation through the assessment of correlations with measures of neuronal activity, excitability, and structural connectivity with multimodal imaging. CONCLUSION: The results of this study will inform on the physiological and cognitive outcomes of DMN stimulation in subjects at risk for AD and on the possible mechanisms. These results may outline the design of future non-pharmacological preventive interventions for AD.

On the dependence of quantitative diffusion-weighted imaging on scanner system characteristics and acquisition parameters: A large multicenter and multiparametric phantom study with unsupervised clustering analysis.

PURPOSE: The purpose of this multicenter phantom study was to exploit an innovative approach, based on an extensive acquisition protocol and unsupervised clustering analysis, in order to assess any potential bias in apparent diffusion coefficient (ADC) estimation due to different scanner characteristics. Moreover, we aimed at assessing, for the first time, any effect of acquisition plan/phase encoding direction on ADC estimation. METHODS: Water phantom acquisitions were carried out on 39 scanners. DWI acquisitions (b-value = 0-200-400-600-800-1000 s/mm2) with different acquisition plans (axial, coronal, sagittal) and phase encoding directions (anterior/posterior and right/left, for the axial acquisition plan), for 3 orthogonal diffusion weighting gradient directions, were performed. For each acquisition setup, ADC values were measured in-center and off-center (6 different positions), resulting in an entire dataset of 84 × 39 = 3276 ADC values. Spatial uniformity of ADC maps was assessed by means of the percentage difference between off-center and in-center ADC values (Δ). RESULTS: No significant dependence of in-center ADC values on acquisition plan/phase encoding direction was found. Ward unsupervised clustering analysis showed 3 distinct clusters of scanners and an association between Δ-values and manufacturer/model, whereas no association between Δ-values and maximum gradient strength, slew rate or static magnetic field strength was revealed. Several acquisition setups showed significant differences among groups, indicating the introduction of different biases in ADC estimation. CONCLUSIONS: Unsupervised clustering analysis of DWI data, obtained from several scanners using an extensive acquisition protocol, allows to reveal an association between measured ADC values and manufacturer/model of scanner, as well as to identify suboptimal DWI acquisition setups for accurate ADC estimation.

Automatic multispectral MRI segmentation of human hippocampal subfields: an evaluation of multicentric test-retest reproducibility.

Accurate and reproducible automated segmentation of human hippocampal subfields is of interest to study their roles in cognitive functions and disease processes. Multispectral structural MRI methods have been proposed to improve automated hippocampal subfield segmentation accuracy, but the reproducibility in a multicentric setting is, to date, not well characterized. Here, we assessed test-retest reproducibility of FreeSurfer 6.0 hippocampal subfield segmentations using multispectral MRI analysis pipelines (22 healthy subjects scanned twice, a week apart, at four 3T MRI sites). The harmonized MRI protocol included two 3D-T1, a 3D-FLAIR, and a high-resolution 2D-T2. After within-session T1 averaging, subfield volumes were segmented using three pipelines with different multispectral data: two longitudinal ("long_T1s" and "long_T1s_FLAIR") and one cross-sectional ("long_T1s_FLAIR_crossT2"). Volume reproducibility was quantified in magnitude (reproducibility error-RE) and space (DICE coefficient). RE was lower in all hippocampal subfields, except for hippocampal fissure, using the longitudinal pipelines compared to long_T1s_FLAIR_crossT2 (average RE reduction of 0.4-3.6%). Similarly, the longitudinal pipelines showed a higher spatial reproducibility (1.1-7.8% of DICE improvement) in all hippocampal structures compared to long_T1s_FLAIR_crossT2. Moreover, long_T1s_FLAIR provided a small but significant RE improvement in comparison to long_T1s (p = 0.015), whereas no significant DICE differences were found. In addition, structures with volumes larger than 200 mm3 had better RE (1-2%) and DICE (0.7-0.95) than smaller structures. In summary, our study suggests that the most reproducible hippocampal subfield FreeSurfer segmentations are derived from a longitudinal pipeline using 3D-T1s and 3D-FLAIR. Adapting a longitudinal pipeline to include high-resolution 2D-T2 may lead to further improvements.

Two months of radiation oncology in the heart of Italian "red zone" during COVID-19 pandemic: paving a safe path over thin ice.

BACKGROUND: Coronavirus Disease 2019 (COVID-19) pandemic had an overwhelming impact on healthcare worldwide. Outstandingly, the aftermath on neoplastic patients is still largely unknown, and only isolated cases of COVID-19 during radiotherapy have been published. We will report the two-months experience of our Department, set in Lombardy "red-zone". METHODS: Data of 402 cancer patients undergoing active treatment from February 24 to April 24, 2020 were retrospectively reviewed; several indicators of the Department functioning were also analyzed. RESULTS: Dedicated measures allowed an overall limited reduction of the workload. Decrease of radiotherapy treatment number reached 17%, while the number of administration of systemic treatment and follow up evaluations kept constant. Conversely, new treatment planning faced substantial decline. Considering the patients, infection rate was 3.23% (13/402) and mortality 1.24% (5/402). Median age of COVID-19 patients was 69.7 years, the large majority were male and smokers (84.6%); lung cancer was the most common tumor type (61.5%), 84.6% of subjects were stage III-IV and 92.3% had comorbidities. Remarkably, 92.3% of the cases were detected before March 24. Globally, only 2.5% of ongoing treatments were suspended due to suspect or confirmed COVID-19 and 46.2% of positive patients carried on radiotherapy without interruption. Considering only the last month, infection rate among patients undergoing treatment precipitated to 0.43% (1/232) and no new contagions were reported within our staff. CONCLUSIONS: Although mortality rate in COVID-19 cancer patients is elevated, our results support the feasibility and safety of continuing anticancer treatment during SARS-Cov-2 pandemic by endorsing consistent preventive measures.

Early-life dentine manganese concentrations and intrinsic functional brain connectivity in adolescents: A pilot study.

Maturational processes in the developing brain are disrupted by exposure to environmental toxicants, setting the stage for deviant developmental trajectories. Manganese (Mn) is an essential nutrient that is neurotoxic at high levels of exposure, particularly affecting the basal ganglia and prefrontal cortex. Both the intensity and timing of exposure matter; deciduous teeth can be used to retrospectively and objectively determine early-life windows of vulnerability. The aim of this pilot study was to examine associations between prenatal, early postnatal and childhood dentine Mn concentrations and intrinsic functional connectivity (iFC) of adolescents' brains. 14 adolescents (12-18 years; 6 girls) from northern Italian regions with either current, historic or no Mn contamination, completed a 10-minute resting state functional Magnetic Resonance Imaging (MRI) scan in an 1.5T MRI scanner. We estimated prenatal, early postnatal and childhood Mn concentrations in deciduous teeth using laser ablation-inductively coupled plasma-mass spectrometry. We performed seed-based correlation analyses, focusing on six subcortical seeds (left and right caudate, putamen, pallidum) and one cortical seed (bilateral middle frontal gyrus) from Harvard-Oxford atlases. We examined linear and quadratic correlations between log-transformed Mn concentrations and seed-based iFC (Bonferroni-corrected p<0.0023), controlling for either socio-economic status, sex or age. Dentine Mn concentrations (Mn:Calcium ratio) were highest during the prenatal period (median = 0.48) and significantly declined during the early postnatal (median = 0.14) and childhood periods (median = 0.006). Postnatal Mn concentrations were associated with: 1) increased iFC between the middle frontal gyrus and medial prefrontal cortex; 2) decreased iFC between the right putamen and pre- and postcentral gyrus. Together, these findings suggest that early postnatal Mn concentrations are associated with increased iFC within cognitive control brain areas, but decreased iFC between motor areas in adolescents. Future studies should replicate these findings in larger samples, and link brain connectivity measures to cognitive and motor outcomes.

Dependence of apparent diffusion coefficient measurement on diffusion gradient direction and spatial position - A quality assurance intercomparison study of forty-four scanners for quantitative diffusion-weighted imaging.

PURPOSE: To propose an MRI quality assurance procedure that can be used for routine controls and multi-centre comparison of different MR-scanners for quantitative diffusion-weighted imaging (DWI). MATERIALS AND METHODS: 44 MR-scanners with different field strengths (1 T, 1.5 T and 3 T) were included in the study. DWI acquisitions (b-value range 0-1000 s/mm2), with three different orthogonal diffusion gradient directions, were performed for each MR-scanner. All DWI acquisitions were performed by using a standard spherical plastic doped water phantom. Phantom solution ADC value and its dependence with temperature was measured using a DOSY sequence on a 600 MHz NMR spectrometer. Apparent diffusion coefficient (ADC) along each diffusion gradient direction and mean ADC were estimated, both at magnet isocentre and in six different position 50 mm away from isocentre, along positive and negative AP, RL and HF directions. RESULTS: A good agreement was found between the nominal and measured mean ADC at isocentre: more than 90% of mean ADC measurements were within 5% from the nominal value, and the highest deviation was 11.3%. Away from isocentre, the effect of the diffusion gradient direction on ADC estimation was larger than 5% in 47% of included scanners and a spatial non uniformity larger than 5% was reported in 13% of centres. CONCLUSION: ADC accuracy and spatial uniformity can vary appreciably depending on MR scanner model, sequence implementation (i.e. gradient diffusion direction) and hardware characteristics. The DWI quality assurance protocol proposed in this study can be employed in order to assess the accuracy and spatial uniformity of estimated ADC values, in single- as well as multi-centre studies.

Action Observation Treatment Improves Upper Limb Motor Functions in Children with Cerebral Palsy: A Combined Clinical and Brain Imaging Study.

The aim of the present study was to assess the role of action observation treatment (AOT) in the rehabilitation of upper limb motor functions in children with cerebral palsy. We carried out a two-group, parallel randomized controlled trial. Eighteen children (aged 5-11 yr) entered the study: 11 were treated children, and 7 served as controls. Outcome measures were scores on two functional scales: Melbourne Assessment of Unilateral Upper Limb Function Scale (MUUL) and the Assisting Hand Assessment (AHA). We collected functional scores before treatment (T1), at the end of treatment (T2), and at two months of follow-up (T3). As compared to controls, treated children improved significantly in both scales at T2 and this improvement persisted at T3. AOT has therefore the potential to become a routine rehabilitation practice in children with CP. Twelve out of 18 enrolled children also underwent a functional magnetic resonance study at T1 and T2. As compared to controls, at T2, treated children showed stronger activation in a parieto-premotor circuit for hand-object interactions. These findings support the notion that AOT contributes to reorganize brain circuits subserving the impaired function rather than activating supplementary or vicariating ones.

Validation of a free software for unsupervised assessment of abdominal fat in MRI.

PURPOSE: To demonstrate the accuracy of an unsupervised (fully automated) software for fat segmentation in magnetic resonance imaging. The proposed software is a freeware solution developed in ImageJ that enables the quantification of metabolically different adipose tissues in large cohort studies. METHODS: The lumbar part of the abdomen (19cm in craniocaudal direction, centered in L3) of eleven healthy volunteers (age range: 21-46years, BMI range: 21.7-31.6kg/m2) was examined in a breath hold on expiration with a GE T1 Dixon sequence. Single-slice and volumetric data were considered for each subject. The results of the visceral and subcutaneous adipose tissue assessments obtained by the unsupervised software were compared to supervised segmentations of reference. The associated statistical analysis included Pearson correlations, Bland-Altman plots and volumetric differences (VD%). RESULTS: Values calculated by the unsupervised software significantly correlated with corresponding supervised segmentations of reference for both subcutaneous adipose tissue - SAT (R=0.9996, p<0.001) and visceral adipose tissue - VAT (R=0.995, p<0.001). Bland-Altman plots showed the absence of systematic errors and a limited spread of the differences. In the single-slice analysis, VD% were (1.6±2.9)% for SAT and (4.9±6.9)% for VAT. In the volumetric analysis, VD% were (1.3±0.9)% for SAT and (2.9±2.7)% for VAT. CONCLUSIONS: The developed software is capable of segmenting the metabolically different adipose tissues with a high degree of accuracy. This free add-on software for ImageJ can easily have a widespread and enable large-scale population studies regarding the adipose tissue and its related diseases.

Can sinogram-affirmed iterative reconstruction improve the detection of small hypervascular liver nodules with dual-energy CT?

OBJECTIVE: To optimize a dual-energy computed tomographic protocol with sinogram-affirmed iterative reconstruction algorithms for improving small nodules detection. METHODS: The raw data of a dual-energy computed tomographic arterial acquisition of a cirrhotic patient were reconstructed with a standard filtered back projection (B20f) and 3 iterative (I26, I30, I31) kernels with different strength (S3-S5). The 80-kilovolt (peak) (kVp) and the linear blended (DE_0.5) images (80-140 kVp) were analyzed. For each series, 8-subcentimeter low-contrast lesions were simulated within the liver. Four radiologists performed a detectability test and rated the image quality (5-point scales) in all images. RESULTS: The sensitivity increased from 31% (B20f) to 87.5% with sinogram-affirmed iterative reconstruction S5 kernels without a difference between 80-kVp and DE_0.5 series (W test, P = 0.062). The highest image quality rating was 3.8 (B20 DE_0.5), without difference from DE_0.5 I30-S5 and I26-S3. CONCLUSIONS: Iterative reconstructions increase the sensitivity for detecting abdominal lesions, even in the 80-kVp series. The kernel I30-S5 was considered the best.

Congenital cystic lung disease: prenatal ultrasound and postnatal multidetector computer tomography evaluation. Correlation with surgical and pathological data.

PURPOSE: The aim of this study was to evaluate the diagnostic accuracy of postnatal multidetector computed tomography (MDCT) compared with prenatal ultrasound (US), surgical findings, and histology, in 33 patients with congenital cystic lung disease. METHODS: Thirty-three patients, 17 males and 16 females, were evaluated by MDCT. Twenty-seven of these patients underwent prenatal US between week 18 and 22, and between week 32 and 35 of gestation. Lung lobectomy, segmentectomy, atypical resection, lesion resection were performed in 31 patients and surgical specimens were analysed. RESULTS: Prenatal US and MDCT correctly diagnosed 76.9 and 94 % of the lesions, respectively. Disagreement occurred in six lesions with prenatal US and in two lesions with MDCT. No statistically significant differences were observed between the two techniques (P = 0.122). CONCLUSIONS: As most surgeons consider the surgical resection of these lesions mandatory, our study underscores the essential role of imaging, in particular CT, in providing invaluable preoperative information on congenital cystic lung diseases recognised in uterus.

Early aphasia rehabilitation is associated with functional reactivation of the left inferior frontal gyrus: a pilot study.

BACKGROUND AND PURPOSE: Early poststroke aphasia rehabilitation effects and their functional MRI (fMRI) correlates were investigated in a pilot, controlled longitudinal study. METHODS: Twelve patients with mild/moderate aphasia (8 Broca, 3 anomic, and 1 Wernicke) were randomly assigned to daily language rehabilitation for 2 weeks (starting 2.2 [mean] days poststroke) or no rehabilitation. The Aachen Aphasia Test and fMRI recorded during an auditory comprehension task were performed at 3 time intervals: mean 2.2 (T1), 16.2 (T2), and 190 (T3) days poststroke. RESULTS: Groups did not differ in terms of age, education, aphasia severity, lesions volume, baseline fMRI activations, and in task performance during fMRI across examinations. Rehabilitated patients significantly improved in naming and written language tasks (P<0.05) compared with no rehabilitation group both at T2 and T3. Functional activity at T1 was reduced in language-related cortical areas (right and left inferior frontal gyrus and middle temporal gyrus, right inferior parietal lobule and superior temporal gyrus) in patients compared with controls. T2 and T3 follow-ups revealed a cortical activation increase, with significantly greater activation in the left hemisphere areas in rehabilitated patients at T2 and T3, and a time×treatment effect at T2 in the left inferior Broca area after rehabilitation. Left inferior frontal gyrus activation at T2 significantly correlated with naming improvement. CONCLUSIONS: Early poststroke aphasia treatment is useful, has durable effects, and may lead to early enhanced recruitment of brain areas, particularly the left inferior frontal gyrus, which persists in the chronic phase.