Deep learning generated lower extremity radiographic measurements are adequate for quick assessment of knee angular alignment and leg length determination.

PURPOSE: Angular and longitudinal deformities of leg alignment create excessive stresses across joints, leading to pain and impaired function. Multiple measurements are used to assess these deformities on anteroposterior (AP) full-length radiographs. An artificial intelligence (AI) software automatically locates anatomical landmarks on AP full-length radiographs and performs 13 measurements to assess knee angular alignment and leg length. The primary aim of this study was to evaluate the agreements in LLD and knee alignment measurements between an AI software and two board-certified radiologists in patients without metal implants. The secondary aim was to assess time savings achieved by AI. METHODS: The measurements assessed in the study were hip-knee-angle (HKA), anatomical-tibiofemoral angle (aTFA), anatomical-mechanical-axis angle (AMA), joint-line-convergence angle (JLCA), mechanical-lateral-proximal-femur-angle (mLPFA), mechanical-lateral-distal-femur-angle (mLDFA), mechanical-medial-proximal-tibia-angle (mMPTA), mechanical-lateral-distal-tibia- angle (mLDTA), femur length, tibia length, full leg length, leg length discrepancy (LLD), and mechanical axis deviation (MAD). These measurements were performed by two radiologists and the AI software on 164 legs. Intraclass-correlation-coefficients (ICC) and Bland-Altman analyses were used to assess the AI's performance. RESULTS: The AI software set incorrect landmarks for 11/164 legs. Excluding these cases, ICCs between the software and radiologists were excellent for 12/13 variables (11/13 with outliers included), and the AI software met performance targets for 11/13 variables (9/13 with outliers included). The mean reading time for the AI algorithm and two readers, respectively, was 38.3, 435.0, and 625.0 s. CONCLUSION: This study demonstrated that, with few exceptions, this AI-based software reliably generated measurements for most variables in the study and provided substantial time savings.

Artificial intelligence-based analyses of varus leg alignment and after high tibial osteotomy show high accuracy and reproducibility.

PURPOSE: The aim of this study was to investigate the performance of an artificial intelligence (AI)-based software for fully automated analysis of leg alignment pre- and postoperatively after high tibial osteotomy (HTO) on long-leg radiographs (LLRs). METHODS: Long-leg radiographs of 95 patients with varus malalignment that underwent medial open-wedge HTO were analyzed pre- and postoperatively. Three investigators and an AI software using deep learning algorithms (LAMA™, ImageBiopsy Lab, Vienna, Austria) evaluated the hip-knee-ankle angle (HKA), mechanical axis deviation (MAD), joint line convergence angle (JLCA), medial proximal tibial angle (MPTA), and mechanical lateral distal femoral angle (mLDFA). All measurements were performed twice and the performance of the AI software was compared with individual human readers using a Bayesian mixed model. In addition, the inter-observer intraclass correlation coefficient (ICC) for inter-observer reliability was evaluated by comparing measurements from manual readers. The intra-reader variability for manual measurements and the AI-based software was evaluated using the intra-observer ICC. RESULTS: Initial varus malalignment was corrected to slight valgus alignment after HTO. Measured by the AI algorithm and manually HKA (5.36° ± 3.03° and 5.47° ± 2.90° to - 0.70 ± 2.34 and - 0.54 ± 2.31), MAD (19.38 mm ± 11.39 mm and 20.17 mm ± 10.99 mm to - 2.68 ± 8.75 and - 2.10 ± 8.61) and MPTA (86.29° ± 2.42° and 86.08° ± 2.34° to 91.6 ± 3.0 and 91.81 ± 2.54) changed significantly from pre- to postoperative, while JLCA and mLDFA were not altered. The fully automated AI-based analyses showed no significant differences for all measurements compared with manual reads neither in native preoperative radiographs nor postoperatively after HTO. Mean absolute differences between the AI-based software and mean manual observer measurements were 0.5° or less for all measurements. Inter-observer ICCs for manual measurements were good to excellent for all measurements, except for JLCA, which showed moderate inter-observer ICCs. Intra-observer ICCs for manual measurements were excellent for all measurements, except for JLCA and for MPTA postoperatively. For the AI-aided analyses, repeated measurements showed entirely consistent results for all measurements with an intra-observer ICC of 1.0. CONCLUSIONS: The AI-based software can provide fully automated analyses of native long-leg radiographs in patients with varus malalignment and after HTO with great accuracy and reproducibility and could support clinical workflows. LEVEL OF EVIDENCE: Diagnostic study, Level III.

Beyond Sharing Unpleasant Affect-Evidence for Pain-Specific Opioidergic Modulation of Empathy for Pain.

It is not known how specific the neural mechanisms underpinning empathy for different domains are. In the present study, we set out to test whether shared neural representations between first-hand pain and empathy for pain are pain-specific or extend to empathy for unpleasant affective touch as well. Using functional magnetic resonance imaging and psychopharmacological experiments, we investigated if placebo analgesia reduces first-hand and empathic experiences of affective touch, and compared them with the effects on pain. Placebo analgesia also affected the first-hand and empathic experience of unpleasant touch, implicating domain-general effects. However, and in contrast to pain and pain empathy, administering an opioid antagonist did not block these effects. Moreover, placebo analgesia reduced neural activity related to both modalities in the bilateral insular cortex, while it specifically modulated activity in the anterior midcingulate cortex for pain and pain empathy. These findings provide causal evidence that one of the major neurochemical systems for pain regulation is involved in pain empathy, and crucially substantiates the role of shared representations in empathy.

Fully automated deep learning for knee alignment assessment in lower extremity radiographs: a cross-sectional diagnostic study.

OBJECTIVES: Accurate assessment of knee alignment and leg length discrepancy is currently measured manually from standing long-leg radiographs (LLR), a process that is both time consuming and poorly reproducible. The aim was to assess the performance of a commercial available AI software by comparing its outputs with manually performed measurements. MATERIALS AND METHODS: The AI was trained on over 15,000 radiographs to measure various clinical angles and lengths from LLRs. We performed a retrospective single-center analysis on 295 LLRs obtained between 2015 and 2020 from male and female patients over 18 years. AI and expert measurements were performed independently. Kellgren-Lawrence score and reading time were assessed. All measurements were compared and non-inferiority, mean-absolute-deviation (sMAD), and intra-class-correlation (ICC) were calculated. RESULTS: A total of 295 LLRs from 284 patients (mean age, 65 years (18; 90); 97 (34.2%) men) were analyzed. The AI model produces outputs on 98.0% of the LLRs. Manually annotations were considered as 100% accurate. For each measurement, its divergence was calculated, resulting in an overall accuracy of 89.2% when comparing the AI outputs to the manually measured. AI vs. mean observer revealed an sMAD between 0.39 and 2.19° for angles and 1.45-5.00 mm for lengths. AI showed good reliability in all lengths and angles (ICC ≥ 0.87). Non-inferiority comparing AI to the mean observer revealed an equivalence-index (γ) between 0.54 and 3.03° for angles and - 0.70-1.95 mm for lengths. On average, AI was 130 s faster than clinicians. CONCLUSION: Automated measurements of knee alignment and length measurements produced with an AI tool result in reproducible, accurate measures with a time savings compared to manually acquired measurements.

Combining stimulus types for improved coverage in population receptive field mapping.

Retinotopy experiments using population receptive field (pRF) mapping are ideal for assigning regions in the visual field to cortical brain areas. While various designs for visual stimulation were suggested in the literature, all have specific shortcomings regarding visual field coverage. Here we acquired high-resolution 7 Tesla fMRI data to compare pRF-based coverage maps obtained with the two most commonly used stimulus variants: moving bars; rotating wedges and expanding rings. We find that stimulus selection biases the spatial distribution of pRF centres. In addition, eccentricity values and pRF sizes obtained from wedge/ring or bar stimulation runs show systematic differences. Wedge/ring stimulation results show lower eccentricity values and strongly reduced pRF sizes compared to bar stimulation runs. Statistical comparison shows significantly higher pRF centre numbers in the foveal 2° region of the visual field for wedge/ring compared to bar stimuli. We suggest and evaluate approaches for combining pRF data from different visual stimulus patterns to obtain improved mapping results.

Placebo-induced pain reduction is associated with negative coupling between brain networks at rest.

Placebos can reduce pain by inducing beliefs in the effectiveness of an actually inert treatment. Such top-down effects on pain typically engage lateral and medial prefrontal regions, the insula, somatosensory cortex, as well as the thalamus and brainstem during pain anticipation or perception. Considering the level of large-scale brain networks, these regions spatially align with fronto-parietal/executive control, salience, and sensory-motor networks, but it is unclear if and how placebos alter interactions between them during rest. Here, we investigated how placebo analgesia affected intrinsic network coupling. Ninety-nine human participants were randomly assigned to a placebo or control group and underwent resting-state fMRI after pain processing. Results revealed inverse coupling between two resting-state networks in placebo but not control participants. Specifically, networks comprised the bilateral somatosensory cortex and posterior insula, as well as the brainstem, thalamus, striatal regions, dorsal and rostral anterior cingulate cortex, and the anterior insula, respectively. Across participants, more negative between-network coupling was associated with lower individual pain intensity as assessed during a preceding pain task, and there was no significant relation with expectations of medication effectiveness in the placebo group. Altogether, these findings provide initial evidence that placebo analgesia affects the intrinsic communication between large-scale brain networks, even in the absence of pain. We suggest a theoretical model where placebo analgesia might affect processing within a descending pain-modulatory network, potentially segregating it from somatosensory regions that may code for painful experiences.

Placebo analgesia and its opioidergic regulation suggest that empathy for pain is grounded in self pain.

Empathy for pain activates brain areas partially overlapping with those underpinning the first-hand experience of pain. It remains unclear, however, whether such shared activations imply that pain empathy engages similar neural functions as first-hand pain experiences. To overcome the limitations of previous neuroimaging research, we pursued a conceptually novel approach: we used the phenomenon of placebo analgesia to experimentally reduce the first-hand experience of pain, and assessed whether this results in a concomitant reduction of empathy for pain. We first carried out a functional MRI experiment (n = 102) that yielded results in the expected direction: participants experiencing placebo analgesia also reported decreased empathy for pain, and this was associated with reduced engagement of anterior insular and midcingulate cortex: that is, areas previously associated with shared activations in pain and empathy for pain. In a second step, we used a psychopharmacological manipulation (n = 50) to determine whether these effects can be blocked via an opioid antagonist. The administration of the opioid antagonist naltrexone blocked placebo analgesia and also resulted in a corresponding "normalization" of empathy for pain. Taken together, these findings suggest that pain empathy may be associated with neural responses and neurotransmitter activity engaged during first-hand pain, and thus might indeed be grounded in our own pain experiences.

Towards understanding rTMS mechanism of action: Stimulation of the DLPFC causes network-specific increase in functional connectivity.

Transcranial magnetic stimulation (TMS) is a powerful non-invasive technique for the modulation of brain activity. While the precise mechanism of action is still unknown, TMS is applied in cognitive neuroscience to establish causal relationships between stimulation and subsequent changes in cerebral function and behavioral outcome. In addition, TMS is an FDA-approved therapeutic agent in psychiatric disorders, especially major depression. Successful repetitive TMS in such disorders is usually applied over the left dorso-lateral prefrontal cortex (DLPFC) and treatment response mechanism was therefore supposed to be based on modulations in functional networks, particularly the meso-cortico-limbic reward circuit. However, mechanistic evidence for the direct effects of rTMS over DLPFC is sparse. Here we show the specificity and temporal evolution of rTMS effects by comparing connectivity changes within 20 common independent components in a sham-controlled study. Using an unbiased whole-brain resting-state network (RSN) approach, we successfully demonstrate that stimulation of left DLPFC modulates anterior cingulate cortex (ACC) connectivity in one specific meso-cortico-limbic network, while all other networks are neither influenced by rTMS nor by sham treatment. The results of this study show that the neural correlates of TMS treatment response are also traceable in DLPFC stimulation of healthy brains and therefore represent direct effects of the stimulation procedure.

Effects of sex hormone treatment on white matter microstructure in individuals with gender dysphoria.

Sex steroid hormones such as estradiol and testosterone are known to have organizing, as well as activating effects on neural tissue in animals and humans. This study investigated the effects of transgender hormone replacement therapy on white matter microstructure using diffusion tensor imaging. Female-to-male and male-to-female transgender participants were measured at baseline, four weeks and four months past treatment start and compared to female and male controls. We observed androgenization-related reductions in mean diffusivity and increases in fractional anisotropy. We also observed feminization-related increases in mean diffusivity and reductions in fractional anisotropy. In both transgender participants and controls, hormonal fluctuations were correlated with changes in white matter microstructure. Although the present study does not preclude regression to the mean as a potential contributing factor, the results indicate that sex hormones are - at least in part - responsible for white matter variability in the human brain. Studies investigating the effects of sex hormones on adult human brain structure may be an important route for greater understanding of the psychological differences between females and males.

Testosterone affects language areas of the adult human brain.

Although the sex steroid hormone testosterone is integrally involved in the development of language processing, ethical considerations mostly limit investigations to single hormone administrations. To circumvent this issue we assessed the influence of continuous high-dose hormone application in adult female-to-male transsexuals. Subjects underwent magnetic resonance imaging before and after 4 weeks of testosterone treatment, with each scan including structural, diffusion weighted and functional imaging. Voxel-based morphometry analysis showed decreased gray matter volume with increasing levels of bioavailable testosterone exclusively in Broca's and Wernicke's areas. Particularly, this may link known sex differences in language performance to the influence of testosterone on relevant brain regions. Using probabilistic tractography, we further observed that longitudinal changes in testosterone negatively predicted changes in mean diffusivity of the corresponding structural connection passing through the extreme capsule. Considering a related increase in myelin staining in rodents, this potentially reflects a strengthening of the fiber tract particularly involved in language comprehension. Finally, functional images at resting-state were evaluated, showing increased functional connectivity between the two brain regions with increasing testosterone levels. These findings suggest testosterone-dependent neuroplastic adaptations in adulthood within language-specific brain regions and connections. Importantly, deteriorations in gray matter volume seem to be compensated by enhancement of corresponding structural and functional connectivity. Hum Brain Mapp 37:1738-1748, 2016. © 2016 Wiley Periodicals, Inc.

Structural Connectivity Networks of Transgender People.

Although previous investigations of transsexual people have focused on regional brain alterations, evaluations on a network level, especially those structural in nature, are largely missing. Therefore, we investigated the structural connectome of 23 female-to-male (FtM) and 21 male-to-female (MtF) transgender patients before hormone therapy as compared with 25 female and 25 male healthy controls. Graph theoretical analysis of whole-brain probabilistic tractography networks (adjusted for differences in intracranial volume) showed decreased hemispheric connectivity ratios of subcortical/limbic areas for both transgender groups. Subsequent analysis revealed that this finding was driven by increased interhemispheric lobar connectivity weights (LCWs) in MtF transsexuals and decreased intrahemispheric LCWs in FtM patients. This was further reflected on a regional level, where the MtF group showed mostly increased local efficiencies and FtM patients decreased values. Importantly, these parameters separated each patient group from the remaining subjects for the majority of significant findings. This work complements previously established regional alterations with important findings of structural connectivity. Specifically, our data suggest that network parameters may reflect unique characteristics of transgender patients, whereas local physiological aspects have been shown to represent the transition from the biological sex to the actual gender identity.

White matter microstructure in transsexuals and controls investigated by diffusion tensor imaging.

Biological causes underpinning the well known gender dimorphisms in human behavior, cognition, and emotion have received increased attention in recent years. The advent of diffusion-weighted magnetic resonance imaging has permitted the investigation of the white matter microstructure in unprecedented detail. Here, we aimed to study the potential influences of biological sex, gender identity, sex hormones, and sexual orientation on white matter microstructure by investigating transsexuals and healthy controls using diffusion tensor imaging (DTI). Twenty-three female-to-male (FtM) and 21 male-to-female (MtF) transsexuals, as well as 23 female (FC) and 22 male (MC) controls underwent DTI at 3 tesla. Fractional anisotropy, axial, radial, and mean diffusivity were calculated using tract-based spatial statistics (TBSS) and fiber tractography. Results showed widespread significant differences in mean diffusivity between groups in almost all white matter tracts. FCs had highest mean diffusivities, followed by FtM transsexuals with lower values, MtF transsexuals with further reduced values, and MCs with lowest values. Investigating axial and radial diffusivities showed that a transition in axial diffusivity accounted for mean diffusivity results. No significant differences in fractional anisotropy maps were found between groups. Plasma testosterone levels were strongly correlated with mean, axial, and radial diffusivities. However, controlling for individual estradiol, testosterone, or progesterone plasma levels or for subjects' sexual orientation did not change group differences. Our data harmonize with the hypothesis that fiber tract development is influenced by the hormonal environment during late prenatal and early postnatal brain development.

(S)-citalopram influences amygdala modulation in healthy subjects: a randomized placebo-controlled double-blind fMRI study using dynamic causal modeling.

Citalopram and Escitalopram are gold standard pharmaceutical treatment options for affective, anxiety, and other psychiatric disorders. However, their neurophysiologic function on cortico-limbic circuits is incompletely characterized. Here we studied the neuropharmacological influence of Citalopram and Escitalopram on cortico-limbic regulatory processes by assessing the effective connectivity between orbitofrontal cortex (OFC) and amygdala using dynamic causal modeling (DCM) applied to functional MRI data. We investigated a cohort of 15 healthy subjects in a randomized, crossover, double-blind design after 10days of Escitalopram (10mg/d (S)-citalopram), Citalopram (10mg/d (S)-citalopram and 10mg/d (R)-citalopram), or placebo. Subjects performed an emotional face discrimination task, while undergoing functional magnetic resonance imaging (fMRI) scanning at 3 Tesla. As hypothesized, the OFC, in the context of the emotional face discrimination task, exhibited a down-regulatory effect on amygdala activation. This modulatory effect was significantly increased by (S)-citalopram, but not (R)-citalopram. For the first time, this study shows that (1) the differential effects of the two enantiomers (S)- and (R)-citalopram on cortico-limbic connections can be demonstrated by modeling effective connectivity methods, and (2) one of their mechanisms can be linked to an increased inhibition of amygdala activation by the orbitofrontal cortex.

Voxel-based morphometry at ultra-high fields. a comparison of 7T and 3T MRI data.

Recent technological progress enables MRI recordings at ultra-high fields of 7 T and above leading to brain images of higher resolution and increased signal-to-noise ratio. Despite these benefits, imaging at 7 T exhibits distinct challenges due to B1 field inhomogeneities, causing decreased image quality and problems in data analysis. Although several strategies have been proposed, a systematic investigation of bias-corrected 7 T data for voxel-based morphometry (VBM) is still missing and it is an ongoing matter of debate if VBM at 7 T can be carried out properly. Here, an optimized VBM study was conducted, evaluating the impact of field strength (3T vs. 7 T) and pulse sequence (MPRAGE vs. MP2RAGE) on gray matter volume (GMV) estimates. More specifically, twenty-two participants were measured under the conditions 3T MPRAGE, 7 T MPRAGE and 7 T MP2RAGE. Due to the fact that 7 T MPRAGE data exhibited strong intensity inhomogeneities, an alternative preprocessing pipeline was proposed and applied for that data. VBM analysis revealed higher GMV estimates for 7 T predominantly in superior cortical areas, caudate nucleus, cingulate cortex and the hippocampus. On the other hand, 3T yielded higher estimates especially in inferior cortical areas of the brain, cerebellum, thalamus and putamen compared to 7 T. Besides minor exceptions, these results were observed for 7 T MPRAGE as well for the 7 T MP2RAGE measurements. Results gained in the inferior parts of the brain should be taken with caution, as native GM segmentations displayed misclassifications in these regions for both 7 T sequences. This was supported by the test-retest measurements showing highest variability in these inferior regions of the brain for 7 T and also for the advanced MP2RAGE sequence. Hence, our data support the use of 7 T MRI for VBM analysis in cortical areas, but direct comparison between field strengths and sequences requires careful assessment. Similarly, analysis of the inferior cortical regions, cerebellum and subcortical regions still remains challenging at 7 T even if the advanced MP2RAGE sequence is used.

Uncertainty during pain anticipation: the adaptive value of preparatory processes.

OBJECTIVES: Anticipatory processes prepare the organism for upcoming experiences. The aim of this study was to investigate neural responses related to anticipation and processing of painful stimuli occurring with different levels of uncertainty. EXPERIMENTAL DESIGN: Twenty-five participants (13 females) took part in an electroencephalography and functional magnetic resonance imaging (fMRI) experiment at separate times. A visual cue announced the occurrence of an electrical painful or nonpainful stimulus, delivered with certainty or uncertainty (50% chance), at some point during the following 15 s. PRINCIPAL OBSERVATIONS: During the first 2 s of the anticipation phase, a strong effect of uncertainty was reflected in a pronounced frontal stimulus-preceding negativity (SPN) and increased fMRI activation in higher visual processing areas. In the last 2 s before stimulus delivery, we observed stimulus-specific preparatory processes indicated by a centroparietal SPN and posterior insula activation that was most pronounced for the certain pain condition. Uncertain anticipation was associated with attentional control processes. During stimulation, the results revealed that unexpected painful stimuli produced the strongest activation in the affective pain processing network and a more pronounced offset-P2. CONCLUSIONS: Our results reflect that during early anticipation uncertainty is strongly associated with affective mechanisms and seems to be a more salient event compared to certain anticipation. During the last 2 s before stimulation, attentional control mechanisms are initiated related to the increased salience of uncertainty. Furthermore, stimulus-specific preparatory mechanisms during certain anticipation also shaped the response to stimulation, underlining the adaptive value of stimulus-targeted preparatory activity which is less likely when facing an uncertain event.

P300 amplitude variation is related to ventral striatum BOLD response during gain and loss anticipation: an EEG and fMRI experiment.

The anticipation of favourable or unfavourable events is a key component in our daily life. However, the temporal dynamics of anticipation processes in relation to brain activation are still not fully understood. A modified version of the monetary incentive delay task was administered during separate functional magnetic resonance imaging (fMRI) and electroencephalogram (EEG) sessions in the same 25 participants to assess anticipatory processes with a multi-modal neuroimaging set-up. During fMRI, gain and loss anticipation were both associated with heightened activation in ventral striatum and reward-related areas. EEG revealed most pronounced P300 amplitudes for gain anticipation, whereas CNV amplitudes distinguished neutral from gain and loss anticipation. Importantly, P300, but not CNV amplitudes, were correlated to neural activation in the ventral striatum for both gain and loss anticipation. Larger P300 amplitudes indicated higher ventral striatum blood oxygen level dependent (BOLD) response. Early stimulus evaluation processes indexed by EEG seem to be positively related to higher activation levels in the ventral striatum, indexed by fMRI, which are usually associated with reward processing. The current results, however, point towards a more general motivational mechanism processing salient stimuli during anticipation.

Retinotopic cortical mapping in objective functional monitoring of macular therapy.

BACKGROUND/AIMS: To determine the suitability of functional MRI (fMRI) as an objective measure of macular function following therapeutic intervention; conventional psychophysical measures rely heavily on patient compliance. METHODS: Twenty patients with neovascular age-related macular degeneration (nAMD) were studied with high-resolution fMRI, visual acuity, reading accuracy and speed, contrast sensitivity (CS) and microperimetry (MP) before and after 3 monthly intravitreal injections of ranibizumab. Population-receptive field retinotopic maps calculated from fMRI data were compared with psychophysical measures and optical coherence tomography. RESULTS: Best-corrected visual acuity (BCVA) responders (≥5 letters) showed an increase of 29.5% in activated brain area, while non-responders showed a decrease of 0.8%. Radial histograms over eccentricity allowed quantification of the absolute number of significant voxels and thus differences before and after treatment. Responders showed increases in foveal (α<0.5°) activation, while non-responders did not. Absence of intraretinal fluid and preservation of outer retinal layers was associated with higher numbers of active V1 voxels and better BCVA. Higher voxel numbers were associated with improved reading performance and, less marked, with BCVA, CS and MP. CONCLUSION: The data show that retinotopic mapping using fMRI can successfully be applied objectively to evaluate the therapeutic response in nAMD patients treated with anti-vascular endothelial growth factor therapy. This demonstrates the ability of retinotopic mapping to provide an objective assessment of functional recovery at a cortical level; the technique can therefore be applied, in other degenerative macular diseases, to the assessment of potential therapeutic interventions such as gene therapy or cell replacement therapy.

Comparing neural response to painful electrical stimulation with functional MRI at 3 and 7 T.

Progressing from 3T to 7 T functional MRI enables marked improvements of human brain imaging in vivo. Although direct comparisons demonstrated advantages concerning blood oxygen level dependent (BOLD) signal response and spatial specificity, these mostly focused on single brain regions with rather simple tasks. Considering that physiological noise also increases with higher field strength, it is not entirely clear whether the advantages of 7T translate equally to the entire brain during tasks which elicit more complex neuronal processing. Therefore, we investigated the difference between 3T and 7 T in response to transcutaneous electrical painful and non-painful stimulation in 22 healthy subjects. For painful stimuli vs. baseline, stronger activations were observed at 7 T in several brain regions including the insula and supplementary motor area, but not the secondary somatosensory cortex (p<0.05 FWE-corrected). Contrasting painful vs. non-painful stimulation limited the differences between the field strengths to the periaqueductal gray (PAG, p<0.001 uncorrected) due to a similar signal increase at 7 T for both the target and specific control condition in most brain regions. This regional specificity obtained for the PAG at higher field strengths was confirmed by an additional spatial normalization strategy optimized for the brainstem. Here, robust BOLD responses were obtained in the dorsal PAG at 7 T (p<0.05 FWE-corrected), whereas at 3T activation was completely missing for the contrast against non-painful stimuli. To summarize, our findings support previously reported benefits obtained at ultra-high field strengths also for complex activation patterns elicited by painful electrical stimulation. However, this advantage depends on the region and even more on the contrast of interest. The greatest gain at 7 T was observed within the small brainstem region of the PAG, where the increased field strength offered marked improvement for the localization of activation foci with high spatial specificity.

Deep Learning for Fully Automated Radiographic Measurements of the Pelvis and Hip.

The morphometry of the hip and pelvis can be evaluated in native radiographs. Artificial-intelligence-assisted analyses provide objective, accurate, and reproducible results. This study investigates the performance of an artificial intelligence (AI)-based software using deep learning algorithms to measure radiological parameters that identify femoroacetabular impingement and hip dysplasia. Sixty-two radiographs (124 hips) were manually evaluated by three observers and fully automated analyses were performed by an AI-driven software (HIPPO™, ImageBiopsy Lab, Vienna, Austria). We compared the performance of the three human readers with the HIPPO™ using a Bayesian mixed model. For this purpose, we used the absolute deviation from the median ratings of all readers and HIPPO™. Our results indicate a high probability that the AI-driven software ranks better than at least one manual reader for the majority of outcome measures. Hence, fully automated analyses could provide reproducible results and facilitate identifying radiographic signs of hip disorders.

Comparison of Stimulus Types for Retinotopic Cortical Mapping of Macular Disease.

Purpose: Retinotopic maps acquired using functional magnetic resonance imaging (fMRI) provide a valuable adjunct in the assessment of macular function at the level of the visual cortex. The present study quantitatively assessed the performance of different visual stimulation approaches for mapping visual field coverage. Methods: Twelve patients with geographic atrophy (GA) secondary to age-related macular degeneration (AMD) were examined using high-resolution ultra-high field fMRI (Siemens Magnetom 7T) and microperimetry (MP; Nidek MP-3). The population receptive field (pRF)-based coverage maps obtained with two different stimulus techniques (moving bars, and rotating wedges and expanding rings) were compared with the results of MP. Correspondence between MP and pRF mapping was quantified by calculating the simple matching coefficient (SMC). Results: Stimulus choice is shown to bias the spatial distribution of pRF centers and eccentricity values with pRF sizes obtained from wedge/ring or bar stimulation showing systematic differences. Wedge/ring stimulation results show a higher number of pRF centers in foveal areas and strongly reduced pRF sizes compared to bar stimulation runs. A statistical comparison shows significantly higher pRF center numbers in the foveal 2.5 degrees region of the visual field for wedge/ring compared to bar stimuli. However, these differences do not significantly influence SMC values when compared to MP (bar <2.5 degrees: 0.88 ± 0.13; bar >2.5 degrees: 0.88 ± 0.11; wedge/ring <2.5 degrees: 0.89 ± 0.12 wedge/ring; >2.5 degrees: 0.86 ± 0.10) for the peripheral visual field. Conclusions: Both visual stimulation designs examined can be applied successfully in patients with GA. Although the two designs show systematic differences in the distribution of pRF center locations, this variability has minimal impact on the SMC when compared to the MP outcome.