brainlife.io: a decentralized and open-source cloud platform to support neuroscience research.

Neuroscience is advancing standardization and tool development to support rigor and transparency. Consequently, data pipeline complexity has increased, hindering FAIR (findable, accessible, interoperable and reusable) access. brainlife.io was developed to democratize neuroimaging research. The platform provides data standardization, management, visualization and processing and automatically tracks the provenance history of thousands of data objects. Here, brainlife.io is described and evaluated for validity, reliability, reproducibility, replicability and scientific utility using four data modalities and 3,200 participants.

Author Correction: Structure of human GABAB receptor in an inactive state.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Structure of human GABAB receptor in an inactive state.

The human GABAB receptor-a member of the class C family of G-protein-coupled receptors (GPCRs)-mediates inhibitory neurotransmission and has been implicated in epilepsy, pain and addiction1. A unique GPCR that is known to require heterodimerization for function2-6, the GABAB receptor has two subunits, GABAB1 and GABAB2, that are structurally homologous but perform distinct and complementary functions. GABAB1 recognizes orthosteric ligands7,8, while GABAB2 couples with G proteins9-14. Each subunit is characterized by an extracellular Venus flytrap (VFT) module, a descending peptide linker, a seven-helix transmembrane domain and a cytoplasmic tail15. Although the VFT heterodimer structure has been resolved16, the structure of the full-length receptor and its transmembrane signalling mechanism remain unknown. Here we present a near full-length structure of the GABAB receptor, captured in an inactive state by cryo-electron microscopy. Our structure reveals several ligands that preassociate with the receptor, including two large endogenous phospholipids that are embedded within the transmembrane domains to maintain receptor integrity and modulate receptor function. We also identify a previously unknown heterodimer interface between transmembrane helices 3 and 5 of both subunits, which serves as a signature of the inactive conformation. A unique 'intersubunit latch' within this transmembrane interface maintains the inactive state, and its disruption leads to constitutive receptor activity.

MRI of the Lactating Breast.

The breasts undergo marked physiologic changes during lactation that can make conventional imaging evaluation with mammography and US challenging. MRI can be a valuable diagnostic aid to differentiate physiologic and benign processes from malignancy in patients who are lactating. In addition, MRI may allow more accurate delineation of disease involvement than does conventional imaging and assists in locoregional staging, screening of the contralateral breast, assessment of response to neoadjuvant chemotherapy, and surgical planning. Although the American College of Radiology recommends against patients undergoing contrast-enhanced MRI during pregnancy because of fetal safety concerns, contrast-enhanced MRI is safe during lactation. As more women delay childbearing, the incidence of pregnancy-associated breast cancer (PABC) and breast cancer in lactating women beyond the 1st year after pregnancy is increasing. Thus, MRI is increasingly being performed in lactating women for diagnostic evaluation and screening of patients at high risk. PABC is associated with a worse prognosis than that of non-PABCs, with delays in diagnosis contributing to an increased likelihood of advanced-stage disease at diagnosis. Familiarity with the MRI features of the lactating breast and the appearance of various pathologic conditions is essential to avoid diagnostic pitfalls and prevent delays in cancer diagnosis and treatment. The authors review clinical indications for breast MRI during lactation, describe characteristic features of the lactating breast at MRI, and compare MRI features of a spectrum of benign and malignant breast abnormalities. ©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material. See the invited commentary by Chikarmane in this issue.

Symmetric activation and modulation of the human calcium-sensing receptor.

The human extracellular calcium-sensing (CaS) receptor controls plasma Ca2+ levels and contributes to nutrient-dependent maintenance and metabolism of diverse organs. Allosteric modulation of the CaS receptor corrects disorders of calcium homeostasis. Here, we report the cryogenic-electron microscopy reconstructions of a near-full-length CaS receptor in the absence and presence of allosteric modulators. Activation of the homodimeric CaS receptor requires a break in the transmembrane 6 (TM6) helix of each subunit, which facilitates the formation of a TM6-mediated homodimer interface and expansion of homodimer interactions. This transformation in TM6 occurs without a positive allosteric modulator. Two modulators with opposite functional roles bind to overlapping sites within the transmembrane domain through common interactions, acting to stabilize distinct rotamer conformations of key residues on the TM6 helix. The positive modulator reinforces TM6 distortion and maximizes subunit contact to enhance receptor activity, while the negative modulator strengthens an intact TM6 to dampen receptor function. In both active and inactive states, the receptor displays symmetrical transmembrane conformations that are consistent with its homodimeric assembly.

Deep Learning to Simulate Contrast-enhanced Breast MRI of Invasive Breast Cancer.

Background There is increasing interest in noncontrast breast MRI alternatives for tumor visualization to increase the accessibility of breast MRI. Purpose To evaluate the feasibility and accuracy of generating simulated contrast-enhanced T1-weighted breast MRI scans from precontrast MRI sequences in biopsy-proven invasive breast cancer with use of deep learning. Materials and Methods Women with invasive breast cancer and a contrast-enhanced breast MRI examination that was performed for initial evaluation of the extent of disease between January 2015 and December 2019 at a single academic institution were retrospectively identified. A three-dimensional, fully convolutional deep neural network simulated contrast-enhanced T1-weighted breast MRI scans from five precontrast sequences (T1-weighted non-fat-suppressed [FS], T1-weighted FS, T2-weighted FS, apparent diffusion coefficient, and diffusion-weighted imaging). For qualitative assessment, four breast radiologists (with 3-15 years of experience) blinded to whether the method of contrast was real or simulated assessed image quality (excellent, acceptable, good, poor, or unacceptable), presence of tumor enhancement, and maximum index mass size by using 22 pairs of real and simulated contrast-enhanced MRI scans. Quantitative comparison was performed using whole-breast similarity and error metrics and Dice coefficient analysis of enhancing tumor overlap. Results Ninety-six MRI examinations in 96 women (mean age, 52 years ± 12 [SD]) were evaluated. The readers assessed all simulated MRI scans as having the appearance of a real MRI scan with tumor enhancement. Index mass sizes on real and simulated MRI scans demonstrated good to excellent agreement (intraclass correlation coefficient, 0.73-0.86; P < .001) without significant differences (mean differences, -0.8 to 0.8 mm; P = .36-.80). Almost all simulated MRI scans (84 of 88 [95%]) were considered of diagnostic quality (ratings of excellent, acceptable, or good). Quantitative analysis demonstrated strong similarity (structural similarity index, 0.88 ± 0.05), low voxel-wise error (symmetric mean absolute percent error, 3.26%), and Dice coefficient of enhancing tumor overlap of 0.75 ± 0.25. Conclusion It is feasible to generate simulated contrast-enhanced breast MRI scans with use of deep learning. Simulated and real contrast-enhanced MRI scans demonstrated comparable tumor sizes, areas of tumor enhancement, and image quality without significant qualitative or quantitative differences. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Slanetz in this issue. An earlier incorrect version appeared online. This article was corrected on January 17, 2023.

US as the Primary Imaging Modality in the Evaluation of Palpable Breast Masses in Breastfeeding Women, Including Those of Advanced Maternal Age.

Background Women are increasingly delaying childbearing, and thus lactation, into their 30s and 40s, when mammography would typically be the initial imaging modality to evaluate palpable masses in the general population. Current guidelines recommend US as the first-line imaging modality for palpable masses in pregnant and lactating women, but data regarding breastfeeding women age 30 years and older are near nonexistent. Purpose To evaluate the diagnostic performance of targeted US as the primary imaging modality for the evaluation of palpable masses in lactating women, including those of advanced maternal age. Materials and Methods Lactating women with palpable breast masses evaluated at targeted US over a 17-year period (January 2000 to July 2017) were retrospectively identified. All US evaluations were performed at diagnostic evaluation, and mammography was performed at the discretion of the interpreting radiologist. Breast Imaging Reporting and Data System assessments, imaging, and pathology results were collected. Descriptive statistics and 2 × 2 contingency tables were assessed at the patient level. Results There were 167 women (mean age, 35 years ± 5 [standard deviation]), 101 of whom (60%) were of advanced maternal age (≥35 years). All women underwent targeted US, and 98 (59%) underwent mammography in addition to US. The frequency of malignancy was five of 167 (3.0%). Targeted US demonstrated a sensitivity and specificity of five of five (100%; 95% confidence interval [CI]: 48%, 100%) and 114 of 162 (70%; 95% CI: 63%, 77%), respectively. Negative predictive value, positive predictive value of an abnormal examination, and positive predictive value of biopsy were 114 of 114 (100%; 95% CI: 97%, 100%), five of 53 (9.4%; 95% CI: 3%, 21%), and five of 50 (10%; 95% CI: 3%, 22%), respectively. In the subset of 98 women who underwent mammography in addition to US, mammography depicted seven incidental suspicious findings, which lowered the specificity from 62 of 93 (67%; 95% CI: 56%, 76%) to 57 of 93 (61%; 95% CI: 51%, 71%) (P = .02). Conclusion Targeted US depicted all malignancies in lactating women with palpable masses. Adding mammography increased false-positive findings without any additional cancer diagnoses. © RSNA, 2020 See also the editorial by Newell in this issue.

Dynamic reorganization of the frontal parietal network during cognitive control and episodic memory.

Higher cognitive functioning is supported by adaptive reconfiguration of large-scale functional brain networks. Cognitive control (CC), which plays a vital role in flexibly guiding cognition and behavior in accordance with our goals, supports a range of executive functions via distributed brain networks. These networks process information dynamically and can be represented as functional connectivity changes between network elements. Using graph theory, we explored context-dependent network reorganization in 56 healthy adults performing fMRI tasks from two cognitive domains that varied in CC and episodic-memory demands. We examined whole-brain modular structure during the DPX task, which engages proactive CC in the frontal-parietal cognitive-control network (FPN), and the RiSE task, which manipulates CC demands at encoding and retrieval during episodic-memory processing, and engages FPN, the medial-temporal lobe and other memory-related networks in a context dependent manner. Analyses revealed different levels of network integration and segregation. Modularity analyses revealed greater brain-wide integration across tasks in high CC conditions compared to low CC conditions. Greater network reorganization occurred in the RiSE memory task, which is thought to require coordination across multiple brain networks, than in the DPX cognitive-control task. Finally, FPN, ventral attention, and visual systems showed within network connectivity effects of cognitive control; however, these cognitive systems displayed varying levels of network reorganization. These findings provide insight into how brain networks reorganize to support differing task contexts, suggesting that the FPN flexibly segregates during focused proactive control and integrates to support control in other domains such as episodic memory.

Dissociable meta-analytic brain networks contribute to coordinated emotional processing.

Meta-analytic techniques for mining the neuroimaging literature continue to exert an impact on our conceptualization of functional brain networks contributing to human emotion and cognition. Traditional theories regarding the neurobiological substrates contributing to affective processing are shifting from regional- towards more network-based heuristic frameworks. To elucidate differential brain network involvement linked to distinct aspects of emotion processing, we applied an emergent meta-analytic clustering approach to the extensive body of affective neuroimaging results archived in the BrainMap database. Specifically, we performed hierarchical clustering on the modeled activation maps from 1,747 experiments in the affective processing domain, resulting in five meta-analytic groupings of experiments demonstrating whole-brain recruitment. Behavioral inference analyses conducted for each of these groupings suggested dissociable networks supporting: (1) visual perception within primary and associative visual cortices, (2) auditory perception within primary auditory cortices, (3) attention to emotionally salient information within insular, anterior cingulate, and subcortical regions, (4) appraisal and prediction of emotional events within medial prefrontal and posterior cingulate cortices, and (5) induction of emotional responses within amygdala and fusiform gyri. These meta-analytic outcomes are consistent with a contemporary psychological model of affective processing in which emotionally salient information from perceived stimuli are integrated with previous experiences to engender a subjective affective response. This study highlights the utility of using emergent meta-analytic methods to inform and extend psychological theories and suggests that emotions are manifest as the eventual consequence of interactions between large-scale brain networks.

Qualitative Radiogenomics: Association between Oncotype DX Test Recurrence Score and BI-RADS Mammographic and Breast MR Imaging Features.

Purpose To evaluate the association between Breast Imaging Reporting and Data System (BI-RADS) mammographic and magnetic resonance (MR) imaging features and breast cancer recurrence risk in patients with estrogen receptor-positive breast cancer who underwent the Oncotype DX assay. Materials and Methods In this institutional review board-approved and HIPAA-compliant protocol, 408 patients diagnosed with invasive breast cancer between 2004 and 2013 who underwent the Oncotype DX assay were identified. Mammographic and MR imaging features were retrospectively collected according to the BI-RADS lexicon. Linear regression assessed the association between imaging features and Oncotype DX test recurrence score (ODxRS), and post hoc pairwise comparisons assessed ODxRS means by using imaging features. Results Mammographic breast density was inversely associated with ODxRS (P ≤ .05). Average ODxRS for density category A was 24.4 and that for density category D was 16.5 (P < .02). Both indistinct mass margins and fine linear branching calcifications at mammography were significantly associated with higher ODxRS (P < .01 and P < .03, respectively). Masses with indistinct margins had an average ODxRS of 31.3, which significantly differed from the ODxRS of 18.5 for all other mass margins (P < .01). The average ODxRS for fine linear branching calcifications was 29.6, whereas the ODxRS for all other suspicious calcification morphologies was 19.4 (P < .03). Average ODxRS was significantly higher for irregular mass margins at MR imaging compared with spiculated mass margins (24.0 vs 17.6; P < .02). The presence of nonmass enhancement at MR imaging was associated with lower ODxRS than was its absence (16.4 vs 19.9; P < .05). Conclusion The BI-RADS features of mammographic breast density, calcification morphology, mass margins at mammography and MR imaging, and nonmass enhancement at MR imaging have the potential to serve as imaging biomarkers of breast cancer recurrence risk. Further prospective studies involving larger patient cohorts are needed to validate these preliminary findings. © RSNA, 2017 Online supplemental material is available for this article.

Microcalcifications Detected at Screening Mammography: Synthetic Mammography and Digital Breast Tomosynthesis versus Digital Mammography.

Purpose To compare the performance of two-dimensional synthetic mammography (SM) plus digital breast tomosynthesis (DBT) versus conventional full-field digital mammography (FFDM) in the detection of microcalcifications on screening mammograms. Materials and Methods In this retrospective multireader observer study, 72 consecutive screening mammograms recalled for microcalcifications from June 2015 through August 2016 were evaluated with both FFDM and DBT. The data set included 54 mammograms with benign microcalcifications and 18 mammograms with malignant microcalcifications, and 20 additional screening mammograms without microcalcifications used as controls. FFDM alone was compared to synthetic mammography plus DBT. Four readers independently reviewed each data set and microcalcification recalls were tabulated. Sensitivity and specificity for microcalcification detection were calculated for SM plus DBT and for FFDM alone. Interreader agreement was calculated with Fleiss kappa values. Results Reader agreement was kappa value of 0.66 (P < .001) for FFDM and 0.63 (P < .001) for SM plus DBT. For FFDM, the combined reader sensitivity for all microcalcifications was 80% (229 of 288; 95% confidence interval [CI]: 74%, 84%) and for malignant microcalcifications was 92% (66 of 72; 95% CI: 83%, 97%). For SM plus DBT, the combined reader sensitivity for all microcalcifications was 75% (215 of 288; 95% CI: 69%, 80%) and for malignant microcalcifications was 94% (68 of 72; 95% CI: 86%, 98%). For FFDM, the combined reader specificity for all microcalcifications was 98% (78 of 80; 95% CI: 91%, 100%) and for malignant microcalcifications was 98% (78 of 80; 95% CI: 91%, 100%). For SM plus DBT, combined reader specificity for all microcalcifications was 95% (76 of 80; 95% CI: 88%, 99%) and for malignant microcalcifications was 95% (76 of 80; 95% CI: 88%, 99%). Mixed-effects model concluded no differences between modalities (‒0.03; 95% CI: ‒0.08, 0.01; P = .13). Conclusion Relative to full-field digital mammography, synthetic mammography plus digital breast tomosynthesis had similar sensitivity and specificity for the detection of microcalcifications previously identified for recall at screening mammography. © RSNA, 2018 See also the editorial by Bae and Moon in this issue.

Effect of Background Parenchymal Enhancement on Breast MR Imaging Interpretive Performance in Community-based Practices.

Purpose To evaluate the effect of background parenchymal enhancement (BPE) on breast magnetic resonance (MR) imaging interpretive performance in a large multi-institutional cohort with independent analysis of screening and diagnostic MR studies. Materials and Methods Analysis of 3770 breast MR studies was conducted. Examinations were performed in 2958 women at six participating facilities in the San Francisco Bay Area from January 2010 to October 2012. Findings were recorded prospectively in the San Francisco Mammography Registry. Performance measures were compared between studies with low BPE (mild or minimal) and those with high BPE (moderate or marked) by using binomial tests of proportions. Results Of 1726 MR imaging studies in the screening group, 1301 were classified as having low BPE and 425 were classified as having high BPE (75% vs 25%, respectively; P < .001). Of 2044 MR imaging studies in the diagnostic group, 1443 were classified as having low BPE and 601 were classified as having high BPE (71% vs 29%, respectively; P < .001). For low versus high BPE groups at screening, abnormal interpretation rate was 157 of 1301 versus 111 of 424 (12% vs 26%, P < .001); biopsy recommendation rate was 85 of 1301 versus 54 of 424 (7% vs 13%, P < .001); and specificity was 89% (95% confidence interval [CI]: 87, 91) versus 75% (95% CI: 71, 80) (P = .01). For the low versus high BPE groups at diagnostic MR imaging, biopsy recommendation rate was 325 of 1443 versus 195 of 601 (23% vs 32%, P < .001); and specificity was 86% (95% CI: 84, 88) versus 75% (95% CI: 74, 82) (P < .001). There were no significant differences between studies with low versus high BPE in sensitivity for screening (76% [95% CI: 55, 91] vs 83% [95% CI: 52, 98]; P = .94) or diagnostic (93% [95% CI: 87, 97] vs 96% [95% CI: 87, 99]; P = .69) MR imaging, nor were there significant differences in cancer detection rate per 1000 patients between the low BPE versus high BPE groups for screening (15 per 1000 vs 24 per 1000, P = .30) or diagnostic (78 per 1000 vs 85 per 1000, P = .64) MR imaging. Conclusion Relative to MR studies with minimal or mild BPE, those with moderate or marked BPE were associated with higher abnormal interpretation and biopsy rates and lower specificity, with no difference in cancer detection rate. © RSNA, 2017 Online supplemental material is available for this article.

Screening Mammography in Women 40-49 Years Old: Current Evidence.

OBJECTIVE: Breast cancer is an important health problem for women 40-49 years old, yet screening mammography for this age group remains controversial. This article reviews recent guidelines and supporting evidence on screening mammography in women of this age group. CONCLUSION: Evidence supports the benefit of annual screening mammography in women 40-49 years old. Models of different breast cancer screening strategies consistently show the greatest breast cancer mortality reduction and life-years gained with annual screening starting when women reach 40 years old.

Sonographic-MRI Correlation After Percutaneous Sampling of Targeted Breast Ultrasound Lesions: Initial Experiences With Limited-Sequence Unenhanced MRI for Postprocedural Clip Localization.

OBJECTIVE: The purpose of this study is to determine the frequency of correlation of sonographic and MRI findings after percutaneous sampling of presumed ultrasound correlates to suspicious lesions detected on breast MRI and to describe our initial experiences with limited-sequence MRI for postprocedural clip verification. MATERIALS AND METHODS: Between January 1, 2014, and March 31, 2016, a total of 1947 contrast-enhanced breast MRI examinations were performed, and 245 targeted ultrasound examinations were conducted to identify correlates to suspicious MRI findings. We retrospectively identified all lesions that underwent ultrasound-guided sampling of a presumed sonographic correlate and for which a subsequent postprocedural limited-sequence unenhanced MR image for clip localization was available. This consisted of a T1-weighted non-fat-saturated and a T2-weighted fat-saturated sequence. Frequencies of sonographic-MRI correlation were quantified. RESULTS: The study cohort consisted of 35 patients with 38 presumed correlates that underwent ultrasound-guided sampling with postprocedural MRI for clip verification. The mean time from percutaneous sampling to postprocedural MRI examination was 1 day. Ten presumed sonographic correlates (26%) were found to localize to a site distinct from the lesion originally identified on MRI. One of these discordant cases revealed malignancy on subsequent MRI-guided biopsy, whereas the presumed sonographic correlate was found to be benign. No patient or lesion characteristics were associated with significantly different frequencies of correlation. CONCLUSION: In our initial experiences with MRI performed for postprocedural clip verification, 26% of presumed correlates to suspicious lesions detected on MRI were not the actual correlate, and 10% of these discordant cases ultimately revealed malignancy. Radiologists should take caution presuming that lesions identified on ultrasound actually represent the suspicious lesions detected on MRI. MRI for clip verification may be useful if ultrasound-guided sampling is pursued.

Paraneoplastic neurologic syndrome as a presentation of underlying breast malignancy.

While breast cancer most commonly presents as a screen-detected mammographic finding or a breast symptom, in very rare instances it may first present as a paraneoplastic neurologic syndrome (PNS; Surg Case Rep, 2015;1:59; Ann Neurol 2004;56:715). Fewer than 1% of breast cancer patients have PNS, and an even smaller percentage initially present with neurologic symptoms (J Neurol Neurosurg Psychiatry, 2004;75:ii43). We report a case series of three patients who presented with neurological disorders suspicious for PNS, and were subsequently found to have underlying breast cancer. We follow this with a discussion of key clinical features of management considerations in paraneoplastic syndromes secondary to breast malignancy.

Heterogeneous fractionation profiles of meta-analytic coactivation networks.

Computational cognitive neuroimaging approaches can be leveraged to characterize the hierarchical organization of distributed, functionally specialized networks in the human brain. To this end, we performed large-scale mining across the BrainMap database of coordinate-based activation locations from over 10,000 task-based experiments. Meta-analytic coactivation networks were identified by jointly applying independent component analysis (ICA) and meta-analytic connectivity modeling (MACM) across a wide range of model orders (i.e., d=20-300). We then iteratively computed pairwise correlation coefficients for consecutive model orders to compare spatial network topologies, ultimately yielding fractionation profiles delineating how "parent" functional brain systems decompose into constituent "child" sub-networks. Fractionation profiles differed dramatically across canonical networks: some exhibited complex and extensive fractionation into a large number of sub-networks across the full range of model orders, whereas others exhibited little to no decomposition as model order increased. Hierarchical clustering was applied to evaluate this heterogeneity, yielding three distinct groups of network fractionation profiles: high, moderate, and low fractionation. BrainMap-based functional decoding of resultant coactivation networks revealed a multi-domain association regardless of fractionation complexity. Rather than emphasize a cognitive-motor-perceptual gradient, these outcomes suggest the importance of inter-lobar connectivity in functional brain organization. We conclude that high fractionation networks are complex and comprised of many constituent sub-networks reflecting long-range, inter-lobar connectivity, particularly in fronto-parietal regions. In contrast, low fractionation networks may reflect persistent and stable networks that are more internally coherent and exhibit reduced inter-lobar communication.

Radiologic-Pathologic Correlation for Benign Results After MRI-Guided Breast Biopsy.

OBJECTIVE: The majority of MRI-guided breast biopsies yield benign pathology. The purpose of this article is to provide a comprehensive overview of benign pathologic entities commonly encountered at MRI-guided breast biopsy. CONCLUSION: Proper radiologic-pathologic correlation is an integral component of MRI-guided breast biopsy. Familiarity with the spectrum of MRI findings and key histopathologic features of common benign entities will enhance the radiologist's confidence in determining concordance and lead to improved patient management recommendations.