1
|
Yedavalli VS, Lakhani DA, Koneru M, Balar AB, Greene C, Hoseinyazdi M, Nabi M, Lu H, Xu R, Luna L, Caplan J, Dmytriw AA, Guenego A, Heit JJ, Albers GW, Wintermark M, Urrutia V, Huang J, Nael K, Leigh R, Marsh EB, Hillis AE, Llinas RH. Simplifying venous outflow: Prolonged venous transit as a novel qualitative marker correlating with acute stroke outcomes. Neuroradiol J 2024:19714009241269475. [PMID: 39067016 DOI: 10.1177/19714009241269475] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/30/2024] Open
Abstract
BACKGROUND Prolonged venous transit (PVT), defined as presence of time-to-maximum ≥ 10 s within the superior sagittal sinus (SSS) and/or torcula, is a novel, qualitatively assessed computed tomography perfusion surrogate parameter of venous outflow with potential utility in pretreatment acute ischemic stroke imaging for neuroprognostication. We aim to characterize the correlation between PVT and neurological functional outcomes in thrombectomy-treated patients. METHODS A prospectively-collected database of large vessel occlusion acute ischemic stroke patients treated with thrombectomy was retrospectively analyzed. Spearman's rank correlation coefficient and point-biserial correlations were performed between PVT status (i.e., no region, either SSS or torcula, or both), 90-day modified Rankin score (mRS), mortality (mRS 6), and poor functional outcome (mRS 4-6 vs 0-3). RESULTS Of 128 patients, correlation between PVT and 90-day mRS (ρ = 0.35, p < 0.0001), mortality (r = 0.26, p = 0.002), and poor functional outcome (r = 0.27, p = 0.002) were significant. CONCLUSION There is a modest, significant correlation between PVT and severity of neurological functional outcome. Consequently, PVT is an easily-ascertained, qualitative metric that may be useful as an adjunct for anticipating a patient's clinical course. Future analyses will determine the significance of incorporating PVT in clinical decision-making.
Collapse
Affiliation(s)
- Vivek S Yedavalli
- Department of Radiology and Radiological Sciences, Johns HopkinsSchool of Medicine, USA
| | | | | | - Aneri B Balar
- Department of Radiology and Radiological Sciences, Johns HopkinsSchool of Medicine, USA
| | - Cynthia Greene
- Department of Radiology and Radiological Sciences, Johns HopkinsSchool of Medicine, USA
| | - Meisam Hoseinyazdi
- Department of Radiology and Radiological Sciences, Johns HopkinsSchool of Medicine, USA
| | - Mehreen Nabi
- Department of Radiology and Radiological Sciences, Johns HopkinsSchool of Medicine, USA
| | - Hanzhang Lu
- Department of Radiology and Radiological Sciences, Johns HopkinsSchool of Medicine, USA
| | - Risheng Xu
- Department of Neurosurgery, Johns HopkinsSchool of Medicine, USA
| | - Licia Luna
- Department of Radiology and Radiological Sciences, Johns HopkinsSchool of Medicine, USA
| | - Justin Caplan
- Department of Neurosurgery, Johns HopkinsSchool of Medicine, USA
| | - Adam A Dmytriw
- Department of Neuroradiology, Massachusetts General Hospital & Harvard Medical School, USA
| | - Adrien Guenego
- Department of Radiology, Université Libre De Bruxelles Hospital Erasme, USA
| | - Jeremy J Heit
- Department of Radiology, Stanford UniversitySchool of Medicine, USA
| | - Gregory W Albers
- Department of Neurology, Stanford UniversitySchool of Medicine, USA
| | - Max Wintermark
- Department of Radiology, University of Texas MD Anderson Center, USA
| | - Victor Urrutia
- Department of Neurology, Johns HopkinsSchool of Medicine, USA
| | - Judy Huang
- Department of Neurosurgery, Johns HopkinsSchool of Medicine, USA
| | - Kambiz Nael
- Department of Radiology, David Geffen School of Medicine at University of California - Los Angeles, USA
| | - Richard Leigh
- Department of Neurology, Johns HopkinsSchool of Medicine, USA
| | | | - Argye E Hillis
- Department of Neurology, Johns HopkinsSchool of Medicine, USA
| | - Rafael H Llinas
- Department of Neurology, Johns HopkinsSchool of Medicine, USA
| |
Collapse
|
2
|
Koneru M, Hoseinyazdi M, Wang R, Ozkara BB, Hyson NZ, Marsh EB, Llinas RH, Urrutia VC, Leigh R, Gonzalez LF, Xu R, Caplan JM, Huang J, Lu H, Luna L, Wintermark M, Dmytriw AA, Guenego A, Albers GW, Heit JJ, Nael K, Hillis AE, Yedavalli VS. Pretreatment parameters associated with hemorrhagic transformation among successfully recanalized medium vessel occlusions. J Neurol 2024; 271:1901-1909. [PMID: 38099953 DOI: 10.1007/s00415-023-12149-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 11/26/2023] [Accepted: 12/03/2023] [Indexed: 03/28/2024]
Abstract
Although pretreatment radiographic biomarkers are well established for hemorrhagic transformation (HT) following successful mechanical thrombectomy (MT) in large vessel occlusion (LVO) strokes, they are yet to be explored for medium vessel occlusion (MeVO) acute ischemic strokes. We aim to investigate pretreatment imaging biomarkers representative of collateral status, namely the hypoperfusion intensity ratio (HIR) and cerebral blood volume (CBV) index, and their association with HT in successfully recanalized MeVOs. A prospectively collected registry of acute ischemic stroke patients with MeVOs successfully recanalized with MT between 2019 and 2023 was retrospectively reviewed. A multivariate logistic regression for HT of any subtype was derived by combining significant univariate predictors into a forward stepwise regression with minimization of Akaike information criterion. Of 60 MeVO patients successfully recanalized with MT, HT occurred in 28.3% of patients. Independent factors for HT included: diabetes mellitus history (p = 0.0005), CBV index (p = 0.0071), and proximal versus distal occlusion location (p = 0.0062). A multivariate model with these factors had strong diagnostic performance for predicting HT (area under curve [AUC] 0.93, p < 0.001). Lower CBV indexes, distal occlusion location, and diabetes history are significantly associated with HT in MeVOs successfully recanalized with MT. Of note, HIR was not found to be significantly associated with HT.
Collapse
Affiliation(s)
- Manisha Koneru
- Cooper Medical School of Rowan University, Camden, NJ, USA
| | - Meisam Hoseinyazdi
- Johns Hopkins School of Medicine, Phipps B122-D, Baltimore, MD, 21287, USA
| | - Richard Wang
- Johns Hopkins School of Medicine, Phipps B122-D, Baltimore, MD, 21287, USA
| | | | - Nathan Z Hyson
- Johns Hopkins School of Medicine, Phipps B122-D, Baltimore, MD, 21287, USA
| | | | - Rafael H Llinas
- Johns Hopkins School of Medicine, Phipps B122-D, Baltimore, MD, 21287, USA
| | - Victor C Urrutia
- Johns Hopkins School of Medicine, Phipps B122-D, Baltimore, MD, 21287, USA
| | - Richard Leigh
- Johns Hopkins School of Medicine, Phipps B122-D, Baltimore, MD, 21287, USA
| | | | - Risheng Xu
- Johns Hopkins School of Medicine, Phipps B122-D, Baltimore, MD, 21287, USA
| | - Justin M Caplan
- Johns Hopkins School of Medicine, Phipps B122-D, Baltimore, MD, 21287, USA
| | - Judy Huang
- Johns Hopkins School of Medicine, Phipps B122-D, Baltimore, MD, 21287, USA
| | - Hanzhang Lu
- Johns Hopkins School of Medicine, Phipps B122-D, Baltimore, MD, 21287, USA
| | - Licia Luna
- Johns Hopkins School of Medicine, Phipps B122-D, Baltimore, MD, 21287, USA
| | | | | | - Adrien Guenego
- Universite Libre De Bruxelles Hospital Erasme, Anderlecht, Belgium
| | | | - Jeremy J Heit
- Stanford University School of Medicine, Stanford, CA, USA
| | - Kambiz Nael
- David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Argye E Hillis
- Johns Hopkins School of Medicine, Phipps B122-D, Baltimore, MD, 21287, USA
| | - Vivek S Yedavalli
- Johns Hopkins School of Medicine, Phipps B122-D, Baltimore, MD, 21287, USA.
| |
Collapse
|
3
|
Koneru M, Hoseinyazdi M, Lakhani DA, Greene C, Copeland K, Wang R, Xu R, Luna L, Caplan JM, Dmytriw AA, Guenego A, Heit JJ, Albers GW, Wintermark M, Gonzalez LF, Urrutia VC, Huang J, Nael K, Leigh R, Marsh EB, Hillis AE, Llinas RH, Yedavalli VS. Redefining CT perfusion-based ischemic core estimates for the ghost core in early time window stroke. J Neuroimaging 2024; 34:249-256. [PMID: 38146065 DOI: 10.1111/jon.13180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Revised: 12/05/2023] [Accepted: 12/05/2023] [Indexed: 12/27/2023] Open
Abstract
BACKGROUND AND PURPOSE In large vessel occlusion (LVO) stroke patients, relative cerebral blood flow (rCBF)<30% volume thresholds are commonly used in treatment decisions. In the early time window, nearly infarcted but salvageable tissue volumes may lead to pretreatment overestimates of infarct volume, and thus potentially exclude patients who may otherwise benefit from intervention. Our multisite analysis aims to explore the strength of relationships between widely used pretreatment CT parameters and clinical outcomes for early window stroke patients. METHODS Patients from two sites in a prospective registry were analyzed. Patients with LVOs, presenting within 3 hours of last known well, and who were successfully reperfused were included. Primary short-term neurological outcome was percent National Institutes of Health Stroke Scale (NIHSS) change from admission to discharge. Secondary long-term outcome was 90-day modified Rankin score. Spearman's correlations were performed. Significance was attributed to p-value ≤.05. RESULTS Among 73 patients, median age was 66 (interquartile range 54-76) years. Among all pretreatment imaging parameters, rCBF<30%, rCBF<34%, and rCBF<38% volumes were significantly, inversely correlated with percentage NIHSS change (p<.048). No other parameters significantly correlated with outcomes. CONCLUSIONS Our multisite analysis shows that favorable short-term neurological recovery was significantly correlated with rCBF volumes in the early time window. However, modest strength of correlations provides supportive evidence that the applicability of general ischemic core estimate thresholds in this subpopulation is limited. Our results support future larger-scale efforts to liberalize or reevaluate current rCBF parameter thresholds guiding treatment decisions for early time window stroke patients.
Collapse
Affiliation(s)
- Manisha Koneru
- Cooper Medical School of Rowan University, Camden, New Jersey, USA
| | | | | | - Cynthia Greene
- Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | | | - Richard Wang
- Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Risheng Xu
- Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Licia Luna
- Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | | | - Adam A Dmytriw
- Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Adrien Guenego
- Université Libre De Bruxelles Hospital Erasme, Brussels, Belgium
| | - Jeremy J Heit
- Stanford University School of Medicine, Stanford, California, USA
| | - Gregory W Albers
- Stanford University School of Medicine, Stanford, California, USA
| | - Max Wintermark
- University of Texas MD Anderson Center, Houston, Texas, USA
| | | | | | - Judy Huang
- Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Kambiz Nael
- David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Richard Leigh
- Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | | | - Argye E Hillis
- Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | | | | |
Collapse
|