Praneeta R. Konduri
Postdoctoral Scholar, Neurology and Neurological Sciences
Bio
Dr. Konduri is a Postdoctoral scholar at the Department of Neurology and Neurological Sciences. With a background in biomedical engineering, she conducted her PhD research as part of a European consortium that developed computational stroke models, while also analyzing post-treatment brain tissue damage from multicenter clinical trials to assess prognosis. After completing her PhD, she continued as a Postdoctoral Researcher within the European consortium GEMINI, that aimed to implement digital twins for personalized stroke treatment. At the Stanford Stroke Center, she now focusses on developing AI tools for stroke diagnosis, treatment evaluation, prognostication, and personalized treatment development.
Honors & Awards
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Paul Dudley White International Scholar Award-Netherlands, American Heart Association (2025)
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Invited Speaker on "Towards digital twins of stroke patients", Society of Neurointerventional Surgery Annual Meeting (2024)
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Invited Speaker on "In silico trials for treatment of acute ischemic stroke", Conference: Thrombolysis and Thrombectomy treatment for AIS (2023)
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Invited speaker: New solutions and innovative study designs to running international clinical trials, European Stroke Organisation Trials Alliance Meeting (2023)
Professional Education
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Doctor of Philosophy, University of Amsterdam (2023)
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Bachelor of Technology, Manipal Institute of Technology (2015)
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Master of Science, Technische Universiteit Delft (2017)
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PhD, University of Amsterdam, Image analysis and in-silico simulation of acute ischemic stroke (2023)
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MSc., Delft University of Technology, Biomedical Engineering - Medical Physics (2017)
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B. Tech, Manipal Institute of Technology, Manipal, Karnataka, India, Biomedical Engineering (2015)
All Publications
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Temporal Net Water Uptake Evolution and its Association with Functional Outcome in Acute Ischemic Stroke.
AJNR. American journal of neuroradiology
2026
Abstract
Subacute lesion growth after acute ischemic stroke is associated with worse functional outcomes. The ischemic lesion severity can be assessed with Net Water Uptake (NWU), a CT-based marker of edema. Pre-treatment NWU has been associated with worse functional outcomes; however, it remains unclear how the temporal changes in NWU influence functional outcomes. In this study, we aimed to determine how associations between NWU and functional outcome vary across imaging times up to 1 week after stroke.We included patients from the MRCLEAN NO-IV trial with anterior circulation large vessel occlusion who were treated with endovascular treatment and had baseline, 24-hour, and 1-week follow-up non-contrast CT scans. Functional outcome at 90 days was evaluated using the modified Rankin Scale (mRS), analyzed both as functional independence (mRS 0-2) and across the full ordinal distribution (mRS 0-6). In the primary analysis, associations between NWU measured at different imaging timepoints and functional independence were examined using univariable and multivariable logistic regression models. To evaluate temporal changes in NWU, ΔNWU was calculated at different time intervals (baseline-24 hours, 24 hours-1 week, and baseline-1 week), and its association with outcomes was analyzed using analogous regression models.Out of 539 MRCLEAN NO-IV patients, 115 were included in this study. The median time from stroke onset to randomization was 92(70-140) minutes. The median NWU evolved from 4.3%(IQR:2.1-6.8%) at baseline to 9.0%(IQR:3.0-13%) at 24 hours and 15%(IQR:11-19%) at 1 week. The median patient-level change (ΔNWU) from baseline to 1 week was 10%(IQR: 5.3-16%). NWU measured at 1 week, but not at baseline or 24 hours, was significantly associated with functional dependence, with an aOR of 0.66(95%CI=0.47-0.90) per 5-percantage-point increase in NWU. Furthermore, a higher increase in NWU from baseline to 1 week imaging was significantly associated with functional dependence, with an aOR of 0.66(95%CI=0.47-0.86) per 5-percentage-point increase in ΔNWU1wk-BL.In our population, NWU measured at 1 week is associated with 90-day clinical outcomes, suggesting that lesion evolution continues in the first week after stroke onset and may therefore represent a target for secondary treatments to improve clinical outcomes.
View details for DOI 10.3174/ajnr.A9330
View details for PubMedID 41935978
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Deep learning-based non-contrast CT imaging markers enhance post-transfer DWI core volume prediction.
AJNR. American journal of neuroradiology
2026
Abstract
BACKGROUND: Deep learning enables the extraction of ischemic lesion size and hypodensity imaging markers from noncontrast CT (DLNCCT) in patients with acute ischemic stroke, but it remains unclear whether those markers can predict post-transfer core volume.METHODS: We performed a post-hoc analysis of prospectively enrolled patients transferred from a primary to a comprehensive center (PSC/CSC) for endovascular treatment (EVT). Using a validated deep-learning NCCT segmentation method, we quantified total lesion volume (per 10mL), modified net water uptake (mNWU %), and severely hypodense volume (≤26 HU per 10mL) and compared these markers with core-lab-rated ASPECTS (per point decrease) and CTP-based evaluation for their association with (adjusted regression coefficient [95%CI]) and predictive performance in addition to baseline variables (R2±SE) for post-transfer CSC-admission DWI core volume.RESULTS: We included 420 patients (239[57%] males) with a median age of 72 years (IQR:61;80). We observed 11.2mL (95%CI:8.3;14.1] larger post-transfer core volumes per point decrease in ASPECTS, 10.0mL (95%CI:6.8;13.3) and 20.0mL (95%CI:12.7;27.2) larger post-transfer core volumes per 10 mL increase in total and severely hypodense DLNCCT volume, respectively. mNWU was not associated with post-transfer core volume (p=0.63). In addition to clinical baseline and CTA variables, post-transfer core volume prediction with ASPECTS (R2:0.49±0.02) and DLNCCT (R2:0.50±0.02) did not differ significantly (p=0.58). Compared with using CTP imaging markers (R2:0.56±0.02), adding ASPECTS (R2:0.63±0.02, p<0.01) and DLNCCT (R2:0.65±0.01, p<0.01) improved performance for post-transfer core volume prediction.CONCLUSION: Total and severely hypodense DLNCCT volumes are independent predictors for post-transfer core volume. These DLNCCT markers improved CTP-based post-transfer core volume prediction.
View details for DOI 10.3174/ajnr.A9311
View details for PubMedID 41916751
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Macrovascular angiographic and tissue-level perfusion collateral scoring to predict inter-hospital infarct growth rate
LIPPINCOTT WILLIAMS & WILKINS. 2026
View details for DOI 10.1161/str.57.suppl_1.DP136
View details for Web of Science ID 001690953100039
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Aggregate Multi-tiered Normalization to Enhance Detection of Impairment in Dynamic BOLD-CVR for Assessment of Hemodynamic Impairment
LIPPINCOTT WILLIAMS & WILKINS. 2026
View details for DOI 10.1161/str.57.suppl_1.WP265
View details for Web of Science ID 001690949600028
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Automated Quantification of Infarct Growth in Endovascular Thrombectomy Using Deep Learning
LIPPINCOTT WILLIAMS & WILKINS. 2026
View details for DOI 10.1161/str.57.suppl_1.WP259
View details for Web of Science ID 001690949600020
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Deep generative models for vessel segmentation in CT angiography of the brain.
Computers in biology and medicine
2026; 202: 111432
Abstract
Automated vessel segmentation in brain CT angiography (CTA) remains challenging despite the potential benefits of its applications. Expert acquisition of reference vessel segmentations is a laborious task. We propose an unsupervised generative deep learning approach that can be trained for vessel segmentation in brain CTA using a large dataset (n=908) of unlabelled brain CTAs and non-contrast enhanced CTs (NCCTs). Our semi-supervised approach uses a conditional generative adversarial network (GAN) for CTA to NCCT translation by generating a contrast map that allows for automatic extraction of vessel segmentations. Furthermore, we propose a 3D Frangi filter-based loss function to enhance tubular structures in the contrast map to improve vessel segmentations. We used a hold-out test set of 9 CTA volumes with manually annotated reference segmentations. We compared our semi-supervised approach with a state-of-the-art supervised nnUnet, trained and evaluated with test set using 9-fold nested cross-validation. Evaluation metrics included voxel-wise Dice similarity coefficient (DSC), true positive rate (TPR), and false positive rate (FPR). The DSC was 4 % lower for the semi-supervised approach (DSC: 0.74) compared to the supervised nnUnet (DSC: 0.78). Both the TPR and FPR were higher for the semi-supervised approach (TPR: 0.75, FPR/1000 voxels:2.05) compared to the supervised nnUnet (TPR:0.71, FPR/1000 voxels:0.87). Hence, the quantitative results showed that our semi-supervised method approaches a supervised state-of-the-art segmentation network. The results demonstrate that a semi-supervised generative deep learning approach for the segmentation of intracranial vessels is feasible without laborious manual segmentations.
View details for DOI 10.1016/j.compbiomed.2025.111432
View details for PubMedID 41494368
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Subacute edema progression after acute ischemic stroke: impact of intravenous alteplase administration and reperfusion degree
FRONTIERS IN NEUROLOGY
2025; 16
View details for DOI 10.3389/fneur.2025.1698480
View details for Web of Science ID 001632373000001
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Subacute edema progression after acute ischemic stroke: impact of intravenous alteplase administration and reperfusion degree.
Frontiers in neurology
2025; 16: 1698480
Abstract
Alteplase is known to increase the risk of blood-brain barrier integrity disruption, potentiating hemorrhage and edema. Evolving edema reduces chances of good functional outcomes. There is a paucity of studies that investigate the role of alteplase administration in subacute edema progression. Here we aim to associate alteplase administration in combination with the degree of reperfusion on edema, measured by net water uptake.We included 115 patients from the MRCLEAN NO-IV trial with baseline, 24-h and 1-week follow-up non-contrast CT scans. The cohort consisted of patients who received intravenous thrombolysis (IVT)+ endovascular treatment (EVT) vs. EVT alone. Net water uptake (NWU) was calculated as a ratio of mean lesion density compared to its homologous, contralateral region-of-interest. Unadjusted linear regression analysis was performed to assess the association between NWU progression and alteplase administration, successful reperfusion [expanded Thrombolysis in Cerebral Infarction (eTICI)2B/3], and excellent reperfusion (eTICI2C/3). Adjusted regression analysis was performed to correct for potential confounders.IVT administration was not statistically significantly associated with NWU progression. Regardless of treatment arm, there was substantial increase in NWU during the first 24 h and 1 week post-stroke. In adjusted analysis, successful reperfusion was significantly associated with reduced NWU progression at 24 h (β = -4.6; 95% CI: -8.4, -0.80) and 1 week (β = -6.5; 95% CI: -11, -2.3).Alteplase administration prior to EVT did not impact the subacute edema progression in our cohort, whereas successful reperfusion was strongly associated with reduced edema progression, particularly at later timepoints. These results suggest that alteplase administration according to current guidelines is unlikely to contribute to accelerated edema progression and emphasize that achieving high-grade reperfusion is crucial for reducing secondary injury.
View details for DOI 10.3389/fneur.2025.1698480
View details for PubMedID 41376769
View details for PubMedCentralID PMC12685625
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White matter lesion effect modification of aspirin and unfractionated heparin during endovascular stroke treatment.
Insights into imaging
2025; 16 (1): 224
Abstract
Periprocedural aspirin or unfractionated heparin during endovascular treatment in acute ischemic stroke increases symptomatic intracranial hemorrhage (sICH) risk without improving functional outcome. White matter lesions (WMLs) are associated with higher sICH risk and poor functional outcome following stroke. We aimed to assess whether WML volume modifies the effect of aspirin or heparin.In this post-hoc analysis of the MR CLEAN-MED trial, WML volume was automatically determined using deep learning-based segmentation on baseline non-contrast CT scans. Outcomes included good functional outcome (modified Rankin Scale 0-2 at 90 days), any ICH, asymptomatic ICH (aICH), and sICH. Patients received either aspirin or not, and either heparin or not. Multivariable logistic regression evaluated treatment effect and effect modification.Of 628 patients, 614 with baseline CT were included. Median WML volume was 0.59 mL without significant differences between treatment arms. WML volume significantly modified the effect of aspirin on sICH (p = 0.01), but not on functional outcome (p = 0.95), any ICH (p = 0.52), or aICH (p = 0.30). Aspirin was associated with increased sICH risk, which decreased with increasing WML volume (aOR 0.96 [95% CI: 0.93-0.99] per 1 mL). For patients with large WML volumes, aspirin showed no significant effect on sICH risk. The effect of heparin on functional outcome, any ICH, aICH, and sICH was not modified by WML volume (p = 0.53, p = 0.26, p = 0.08, p = 0.63, respectively).WML volume significantly modified the effect of aspirin on sICH risk, with aspirin-associated risk decreasing as WML volume increased. WML volume did not modify the effect of aspirin or heparin on other outcomes.WML volume on non-contrast CT modifies the effect of aspirin during endovascular thrombectomy on sICH risk, yet no WML-based patient subgroup showed save benefits from periprocedural aspirin or heparin treatment.Periprocedural aspirin and unfractionated heparin during endovascular treatment cause a higher hemorrhage risk. WML volume is associated with worse functional outcome and WML volume significantly modifies the effect of aspirin on symptomatic hemorrhage risk, with aspirin-associated risk decreasing with increasing WML volume. No WML-volume-based patient subgroup was identified where aspirin or heparin treatment demonstrated safe clinical benefit.
View details for DOI 10.1186/s13244-025-02095-2
View details for PubMedID 41123765
View details for PubMedCentralID PMC12546164
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Hypodensity Beyond the Ischemic Core: Penumbral Changes Detected With Relative Noncontrast Computed Tomography.
Stroke
2025
Abstract
BACKGROUND: In acute ischemic stroke, infarcted tissue gradually becomes detectable on noncontrast computed tomography (NCCT) as a hypodensity representing vasogenic edema. We studied whether subtle NCCT density changes are also present in penumbral tissue.METHODS: This observational cohort study included patients with stroke with anterior circulation occlusions from the CRISP2 study (CT Perfusion to Predict Response to Recanalization in Ischemic Stroke Project 2) who were transferred from a primary to a comprehensive stroke center for consideration of endovascular thrombectomy. Patients received baseline NCCT and computed tomography perfusion at the referring hospital and magnetic resonance imaging at the receiving hospital. We created baseline relative NCCT images, which compare voxel density to the corresponding area in the contralateral hemisphere. We analyzed the relative density of rNCCT in the core and penumbra (based on computed tomography perfusion in referring hospitals). We also assessed the correlation between relative density and the degree of hypoperfusion in the penumbra, defined as the time-to-maximum of the tissue residue function. We studied the association between penumbral changes and functional outcomes on the full distribution of the modified Rankin Scale score at 90 days.RESULTS: From the 314 patients, 162 met inclusion criteria with a median (interquartile range) age of 73 (61-83) years, penumbra volume of 78 (52-113) mL, and core volume of 0.6 (0-13.0) mL; 54% were men. The relative density was reduced by a median of 1.8% (P<0.0001) in the penumbra and 3.3% in the core (P<0.0001). Relative hypodensity in the penumbra was more profound with increasing hypoperfusion: 1.5% in regions with time-to-maximum of 6- to 8-s region, 1.8% in time-to-maximum of 8- to 10-s v, and 2.2% in time-to-maximum >10-s region (P<0.0001). We identified a trend toward worse outcomes with more hypodense penumbra (odds ratio, 1.193 [95% CI, 0.996-1.430]).CONCLUSIONS: In patients with anterior circulation acute ischemic stroke, we identified relative hypodensity in penumbral tissue on NCCT with potential clinical relevance on 90-day functional outcomes. The hypodensity was more pronounced with increasing hypoperfusion severity.
View details for DOI 10.1161/STROKEAHA.124.050317
View details for PubMedID 40557487
https://orcid.org/0000-0002-9911-2090