MSTPublications: February 2025
Impact of disease duration and surgical intervention on arousal networks in temporal lobe epilepsy.
Doss DJ, Gummadavelli A, Johnson GW, Makhoul GS, Shless JS, Bibro CE, Jacobs ML, Kang H, Haas KF, Bick SK, Terry DP, Dawant BM, Chang C, Morgan VL, Englot DJ.
J Neurosurg. 2025 Jan 24:1-10. doi: 10.3171/2024.8.JNS241079. Online ahead of print.
PMID: 39854724
Abstract
Objective: Epilepsy is a common neurological disease affecting nearly 1% of the global population, and temporal lobe epilepsy (TLE) is the most common type. Patients experience recurrent seizures and chronic cognitive deficits that can impact their quality of life, ability to work, and independence. These cognitive deficits often extend beyond the temporal lobe and are not well understood. It has been proposed in the extended network inhibition hypothesis that repeated spread of seizure activity to the ascending reticular activating system (ARAS) may contribute to these deficits. Disease duration has been associated with other network changes in patients with TLE, but few studies have investigated the relationship between disease duration, ARAS connectivity, and cognitive deficits in TLE. Furthermore, epilepsy surgery can result in seizure freedom and cognitive improvement in some patients, but it is unclear how the surgery affects ARAS connectivity.
Methods: Resting-state functional MRI data were collected for patients with TLE (preoperatively in 40 and postoperatively in 25), and for 40 age-matched healthy controls. Functional connectivity was computed between all regions. Functional connectivity and segregation, a graph-theory measure of network isolation, were compared across the age spectrum in patients and controls. These same measures were evaluated as a function of epilepsy duration by controlling for age using a linear model built on healthy control data.
Results: The authors found that increases in epilepsy duration were associated with greater segregation of the ARAS and decreased functional connectivity between the pedunculopontine tegmental nucleus and the frontoparietal association cortex. Furthermore, patients with impaired neurocognitive function were noted to have longer epilepsy duration and higher ARAS segregation compared to patients with spared neurocognition. After surgery, completely seizure-free patients demonstrated ARAS connectivity patterns that resembled those found in controls, whereas patients with residual seizures had persistent abnormal connectivity.
Conclusions: These findings suggest that recurrent seizures may contribute to isolation of critical subcortical activating structures, possibly impacting cognitive function. Furthermore, some ARAS functional connectivity abnormalities can be reversed if seizure freedom is achieved after epilepsy surgery. These results provide support for the extended network inhibition hypothesis, may lend insight into the progressive effect of recurrent seizures on arousal networks, and may lead to improved interventions to halt or reverse network impairments in patients with TLE.
Keywords: cognition and epilepsy; connectomics; epilepsy duration; seizure freedom; surgical epilepsy; temporal lobe epilepsy.
Performance of Lung Cancer Prediction Models for Screening-detected, Incidental, and Biopsied Pulmonary Nodules.
Li TZ, Xu K, Krishnan A, Gao R, Kammer MN, Antic S, Xiao D, Knight M, Martinez Y, Paez R, Lentz RJ, Deppen S, Grogan EL, Lasko TA, Sandler KL, Maldonado F, Landman BA.
Radiol Artif Intell. 2025 Feb 5:e230506. doi: 10.1148/ryai.230506. Online ahead of print.
PMID: 39907586
Abstract
“Just Accepted” papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note that during production of the final copyedited article, errors may be discovered which could affect the content. Purpose To evaluate the performance of eight lung cancer prediction models on patient cohorts with screening-detected, incidentally-detected, and bronchoscopically-biopsied pulmonary nodules. Materials and Methods This study retrospectively evaluated promising predictive models for lung cancer prediction in three clinical settings: lung cancer screening with low-dose CT, incidentally, detected pulmonary nodules, and nodules deemed suspicious enough to warrant a biopsy. The area under the receiver operating characteristic curve (AUC) of eight validated models including logistic regressions on clinical variables and radiologist nodule characterizations, artificial intelligence (AI) on chest CTs, longitudinal imaging AI, and multimodal approaches for prediction of lung cancer risk was assessed in 9 cohorts (n = 898, 896, 882, 219, 364, 117, 131, 115, 373) from multiple institutions. Each model was implemented from their published literature, and each cohort was curated from primary data sources collected over periods within 2002 to 2021. Results No single predictive model emerged as the highest-performing model across all cohorts, but certain models performed better in specific clinical contexts. Single timepoint chest CT AI performed well for screening-detected nodules but did not generalize well to other clinical settings. Longitudinal imaging and multimodal models demonstrated comparatively good performance on incidentally-detected nodules. When applied to biopsied nodules, all models showed low performance. Conclusion Eight lung cancer prediction models failed to generalize well across clinical settings and sites outside of their training distributions. ©RSNA, 2025.
Can brain network analyses guide epilepsy surgery?
Makhoul GS, Doss DJ, Englot DJ.
Curr Opin Neurol. 2025 Feb 3. doi: 10.1097/WCO.0000000000001346. Online ahead of print.
PMID: 39886890
Abstract
Purpose of review: Epilepsy surgery is a potentially curative intervention for medically refractory epilepsy. In the last several decades, epilepsy has been studied as a network disorder. How has this disease model influenced surgical interventions?
Recent findings: Surgical outcomes for resection are increasingly being tied to network features, such as node hubness score. These findings imply that measuring network features may augment epileptologist seizure onset zone designation for surgical planning. Network models are also leveraged for neuromodulation, specifically in studies with thalamic targets. Recent findings suggest that the thalamus may function as a reasonable target for neuromodulation because of its role in the seizure propagation networks.
Summary: In this review, we discuss the degree these models of epilepsy are influencing surgery today and barriers for the widespread adoption of network models when planning epilepsy surgery.
TET2-loss enhances immediate and time-resolved interferon-γ signaling responses across myeloid differentiation.
Jenkins MT, Chu YE, Franceski AM, Potts CR, Dubin R, Dickerson KM, Lee SC, Lu R, Welner RS, Ferrell PB.
Exp Hematol. 2025 Jan 22;144:104727. doi: 10.1016/j.exphem.2025.104727. Online ahead of print.
PMID: 39855457
Application of an Externally Developed Algorithm to Identify Research Cases and Controls from Electronic Health Record Data: Failures and Successes.
Garduno Rapp NE, Herzberg SD, Ong HH, Kao C, Lehmann CU, Gangireddy S, Jain NB, Giri A.
Appl Clin Inform. 2025 Jan 24. doi: 10.1055/a-2524-5216. Online ahead of print.
PMID: 39855267 Free article.
Evolving adeno-associated viruses for gene transfer to the kidney via cross-species cycling of capsid libraries.
Rosales A, Blondel LO, Hull J, Gao Q, Aykun N, Peek JL, Vargas A, Fergione S, Song M, Wilson MH, Barbas AS, Asokan A.
Nat Biomed Eng. 2025 Feb 5. doi: 10.1038/s41551-024-01341-0. Online ahead of print.
PMID: 39910375
Genome-wide association study of prostate-specific antigen levels in 392,522 men identifies new loci and improves prediction across ancestry groups.
Hoffmann TJ, Graff RE, Madduri RK, Rodriguez AA, Cario CL, Feng K, Jiang Y, Wang A, Klein RJ, Pierce BL, Eggener S, Tong L, Blot W, Long J, Goss LB, Darst BF, Rebbeck T, Lachance J, Andrews C, Adebiyi AO, Adusei B, Aisuodionoe-Shadrach OI, Fernandez PW, Jalloh M, Janivara R, Chen WC, Mensah JE, Agalliu I, Berndt SI, Shelley JP, Schaffer K, Machiela MJ, Freedman ND, Huang WY, Li SA, Goodman PJ, Till C, Thompson I, Lilja H, Ranatunga DK, Presti J, Van Den Eeden SK, Chanock SJ, Mosley JD, Conti DV, Haiman CA, Justice AC, Kachuri L, Witte JS.
Nat Genet. 2025 Feb;57(2):334-344. doi: 10.1038/s41588-024-02068-z. Epub 2025 Feb 10.
PMID: 39930085 Free PMC article.
Early Division of the Paramedian Forehead Flap: A Systematic Review and Retrospective Analysis.
Ma CC, Si C, Adegboye F, Lee J, Lee I, Stephan SJ, Patel PN, Yang SF.
Laryngoscope. 2025 Jan 27. doi: 10.1002/lary.32009. Online ahead of print.
PMID: 39871421 Review.
Longitudinal Symptom Burden and Pharmacologic Management of Catatonia in Autism With Intellectual Disability: An Observational Study.
Smith JR, Lim S, Bindra S, Marler S, Rajah B, Williams ZJ, Baldwin I, Hossain N, Wilson JE, Fuchs DC, Luccarelli J.
Autism Res. 2025 Feb;18(2):449-462. doi: 10.1002/aur.3315. Epub 2025 Jan 27.
PMID: 39866085 Free PMC article.