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Chen L, Wang X, Li Y, Bao Y, Wang S, Zhao X, Yuan M, Kang J, Sun S. Development of a deep-learning algorithm for etiological classification of subarachnoid hemorrhage using non-contrast CT scans. Eur Radiol 2025:10.1007/s00330-025-11666-2. [PMID: 40382487 DOI: 10.1007/s00330-025-11666-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2024] [Revised: 03/06/2025] [Accepted: 04/13/2025] [Indexed: 05/20/2025]
Abstract
OBJECTIVES This study aims to develop a deep learning algorithm for differentiating aneurysmal subarachnoid hemorrhage (aSAH) from non-aneurysmal subarachnoid hemorrhage (naSAH) using non-contrast computed tomography (NCCT) scans. METHODS This retrospective study included 618 patients diagnosed with SAH. The dataset was divided into a training and internal validation cohort (533 cases: aSAH = 305, naSAH = 228) and an external test cohort (85 cases: aSAH = 55, naSAH = 30). Hemorrhage regions were automatically segmented using a U-Net + + architecture. A ResNet-based deep learning model was trained to classify the etiology of SAH. RESULTS The model achieved robust performance in distinguishing aSAH from naSAH. In the internal validation cohort, it yielded an average sensitivity of 0.898, specificity of 0.877, accuracy of 0.889, Matthews correlation coefficient (MCC) of 0.777, and an area under the curve (AUC) of 0.948 (95% CI: 0.929-0.967). In the external test cohort, the model demonstrated an average sensitivity of 0.891, specificity of 0.880, accuracy of 0.887, MCC of 0.761, and AUC of 0.914 (95% CI: 0.889-0.940), outperforming junior radiologists (average accuracy: 0.836; MCC: 0.660). CONCLUSION The study presents a deep learning architecture capable of accurately identifying SAH etiology from NCCT scans. The model's high diagnostic performance highlights its potential to support rapid and precise clinical decision-making in emergency settings. KEY POINTS Question Differentiating aneurysmal from naSAH is crucial for timely treatment, yet existing imaging modalities are not universally accessible or convenient for rapid diagnosis. Findings A ResNet-variant-based deep learning model utilizing non-contrast CT scans demonstrated high accuracy in classifying SAH etiology and enhanced junior radiologists' diagnostic performance. Clinical relevance AI-driven analysis of non-contrast CT scans provides a fast, cost-effective, and non-invasive solution for preoperative SAH diagnosis. This approach facilitates early identification of patients needing aneurysm surgery while minimizing unnecessary angiography in non-aneurysmal cases, enhancing clinical workflow efficiency.
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Affiliation(s)
- Lingxu Chen
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Department of Radiology, Beijing Neurosurgical Institute, Beijing, China
| | - Xiaochen Wang
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Department of Radiology, Beijing Neurosurgical Institute, Beijing, China
| | - Yuanjun Li
- Department of Radiology, Zhongshan Hospital Affiliated to Xiamen University, Hubinnan Road, Xiamen, China
| | - Yang Bao
- Neusoft Medical Systems, Shenyang, China
| | - Sihui Wang
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xuening Zhao
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Mengyuan Yuan
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jianghe Kang
- Department of Radiology, Zhongshan Hospital Affiliated to Xiamen University, Hubinnan Road, Xiamen, China
| | - Shengjun Sun
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
- Department of Radiology, Beijing Neurosurgical Institute, Beijing, China.
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Benomar A, Diestro JDB, Darabid H, Saydy K, Tzaneva L, Li J, Zarour E, Tanguay W, El Sayed N, Padilha IG, Létourneau-Guillon L, Bard C, Nelson K, Weill A, Roy D, Eneling J, Boisseau W, Nguyen TN, Abdalkader M, Najjar AA, Nehme A, Lemoine É, Jacquin G, Bergeron D, Brunette-Clément T, Chaalala C, Bojanowski MW, Labidi M, Jabre R, Ignacio KHD, Omar AT, Volders D, Dmytriw AA, Hak JF, Forestier G, Holay Q, Olatunji R, Alhabli I, Nico L, Shankar JJS, Guenego A, Pascual JLR, Marotta TR, Errázuriz JI, Lin AW, Alves AC, Fahed R, Hawkes C, Lee H, Magro E, Sheikhi L, Darsaut TE, Raymond J. Nonaneurysmal perimesencephalic subarachnoid hemorrhage on noncontrast head CT: An accuracy, inter-rater, and intra-rater reliability study. J Neuroradiol 2024; 51:101184. [PMID: 38387650 DOI: 10.1016/j.neurad.2024.02.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Revised: 02/13/2024] [Accepted: 02/15/2024] [Indexed: 02/24/2024]
Abstract
BACKGROUND AND PURPOSE To evaluate the reliability and accuracy of nonaneurysmal perimesencephalic subarachnoid hemorrhage (NAPSAH) on Noncontrast Head CT (NCCT) between numerous raters. MATERIALS AND METHODS 45 NCCT of adult patients with SAH who also had a catheter angiography (CA) were independently evaluated by 48 diverse raters; 45 raters performed a second assessment one month later. For each case, raters were asked: 1) whether they judged the bleeding pattern to be perimesencephalic; 2) whether there was blood anterior to brainstem; 3) complete filling of the anterior interhemispheric fissure (AIF); 4) extension to the lateral part of the sylvian fissure (LSF); 5) frank intraventricular hemorrhage; 6) whether in the hypothetical presence of a negative CT angiogram they would still recommend CA. An automatic NAPSAH diagnosis was also generated by combining responses to questions 2-5. Reliability was estimated using Gwet's AC1 (κG), and the relationship between the NCCT diagnosis of NAPSAH and the recommendation to perform CA using Cramer's V test. Multi-rater accuracy of NCCT in predicting negative CA was explored. RESULTS Inter-rater reliability for the presence of NAPSAH was moderate (κG = 0.58; 95%CI: 0.47, 0.69), but improved to substantial when automatically generated (κG = 0.70; 95%CI: 0.59, 0.81). The most reliable criteria were the absence of AIF filling (κG = 0.79) and extension to LSF (κG = 0.79). Mean intra-rater reliability was substantial (κG = 0.65). NAPSAH weakly correlated with CA decision (V = 0.50). Mean sensitivity and specificity were 58% (95%CI: 44%, 71%) and 83 % (95%CI: 72 %, 94%), respectively. CONCLUSION NAPSAH remains a diagnosis of exclusion. The NCCT diagnosis was moderately reliable and its impact on clinical decisions modest.
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Affiliation(s)
- Anass Benomar
- Department of Radiology, Radiation Oncology and Nuclear Medicine, Centre Hospitalier de l'Université de Montréal (CHUM), Montreal, QC, Canada. https://twitter.com/AnassBenomarMD
| | - Jose Danilo B Diestro
- Division of Diagnostic and Therapeutic Neuroradiology, Department of Radiology, St. Michael's Hospital, University of Toronto, ON, Canada. https://twitter.com/DanniDiestro
| | - Houssam Darabid
- Department of Radiology, Radiation Oncology and Nuclear Medicine, Centre Hospitalier de l'Université de Montréal (CHUM), Montreal, QC, Canada
| | - Karim Saydy
- Department of Radiology, Radiation Oncology and Nuclear Medicine, Centre Hospitalier de l'Université de Montréal (CHUM), Montreal, QC, Canada
| | - Lora Tzaneva
- Department of Experimental Surgery, McGill University, Montreal, QC, Canada
| | - Jimmy Li
- Division of Neurology, Centre Hospitalier Universitaire de Sherbrooke (CHUS), Sherbrooke, QC, Canada. https://twitter.com/neuroloJimmy
| | - Eleyine Zarour
- Department of Radiology, Radiation Oncology and Nuclear Medicine, Centre Hospitalier de l'Université de Montréal (CHUM), Montreal, QC, Canada. https://twitter.com/eleyine
| | - William Tanguay
- Department of Radiology, Radiation Oncology and Nuclear Medicine, Centre Hospitalier de l'Université de Montréal (CHUM), Montreal, QC, Canada
| | - Nohad El Sayed
- Department of Radiology, McGill University Health Centre (MUHC), Montreal, QC, Canada
| | - Igor Gomes Padilha
- Division of Neuroradiology, Diagnósticos da América SA - DASA, São Paulo, SP, Brazil; Division of Neuroradiology, Santa Casa de São Paulo School of Medical Sciences, São Paulo, SP, Brazil; Division of Neuroradiology, United Health Group, São Paulo, SP, Brazil
| | - Laurent Létourneau-Guillon
- Department of Radiology, Radiation Oncology and Nuclear Medicine, Centre Hospitalier de l'Université de Montréal (CHUM), Montreal, QC, Canada. https://twitter.com/LaurentLetG
| | - Céline Bard
- Department of Radiology, Radiation Oncology and Nuclear Medicine, Centre Hospitalier de l'Université de Montréal (CHUM), Montreal, QC, Canada
| | - Kristoff Nelson
- Department of Radiology, Radiation Oncology and Nuclear Medicine, Centre Hospitalier de l'Université de Montréal (CHUM), Montreal, QC, Canada
| | - Alain Weill
- Department of Radiology, Radiation Oncology and Nuclear Medicine, Centre Hospitalier de l'Université de Montréal (CHUM), Montreal, QC, Canada
| | - Daniel Roy
- Department of Radiology, Radiation Oncology and Nuclear Medicine, Centre Hospitalier de l'Université de Montréal (CHUM), Montreal, QC, Canada
| | - Johanna Eneling
- Department of Neurosurgery, Linköping University Hospital, Linköping, Sweden
| | - William Boisseau
- Department of Interventional Neuroradiology, Fondation Adolphe de Rothschild, Paris, France
| | - Thanh N Nguyen
- Department of Neurology, Neurosurgery, and Radiology, Boston Medical Center, Boston, MA, USA. https://twitter.com/NguyenThanhMD
| | - Mohamad Abdalkader
- Department of Neurology, Neurosurgery, and Radiology, Boston Medical Center, Boston, MA, USA. https://twitter.com/AbdalkaderMD
| | - Ahmed A Najjar
- Division of Neurosurgery, Department of Surgery, College of Medicine, Taibah University, Medina, Saudi Arabia. https://twitter.com/AhmedANajjar
| | - Ahmad Nehme
- Université Caen-Normandie, Neurology, CHU Caen-Normandie, Caen, France. https://twitter.com/ANehme
| | - Émile Lemoine
- Division of Neurology, Department of Medicine, Centre Hospitalier de l'Université de Montréal (CHUM), Montreal, QC, Canada. https://twitter.com/lemoineemile
| | - Gregory Jacquin
- Division of Neurology, Department of Medicine, Centre Hospitalier de l'Université de Montréal (CHUM), Montreal, QC, Canada
| | - David Bergeron
- Division of Neurosurgery, Department of Surgery, Centre Hospitalier de l'Université de Montréal (CHUM), Montreal, QC, Canada. https://twitter.com/David__Bergeron
| | - Tristan Brunette-Clément
- Division of Neurosurgery, Department of Surgery, Centre Hospitalier de l'Université de Montréal (CHUM), Montreal, QC, Canada. https://twitter.com/BrunetteClement
| | - Chiraz Chaalala
- Division of Neurosurgery, Department of Surgery, Centre Hospitalier de l'Université de Montréal (CHUM), Montreal, QC, Canada
| | - Michel W Bojanowski
- Division of Neurosurgery, Department of Surgery, Centre Hospitalier de l'Université de Montréal (CHUM), Montreal, QC, Canada
| | - Moujahed Labidi
- Division of Neurosurgery, Department of Surgery, Centre Hospitalier de l'Université de Montréal (CHUM), Montreal, QC, Canada
| | - Roland Jabre
- Division of Neurosurgery, Department of Surgery, Centre Hospitalier de l'Université de Montréal (CHUM), Montreal, QC, Canada
| | - Katrina H D Ignacio
- Calgary Stroke Program, Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Foothills Medical Centre, Calgary, AB, Canada. https://twitter.com/Katha_MD
| | - Abdelsimar T Omar
- Division of Neurosurgery, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada; Division of Neurosurgery, McMaster University, Hamilton, ON, Canada. https://twitter.com/atomar_md
| | - David Volders
- Department of Diagnostic Radiology, Queen Elizabeth II Health Sciences Centre, Dalhousie University, Halifax, NS, Canada
| | - Adam A Dmytriw
- Division of Diagnostic and Therapeutic Neuroradiology, Department of Radiology, St. Michael's Hospital, University of Toronto, ON, Canada; Neuroendovascular Program, Massachusetts General Hospital & Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA. https://twitter.com/AdamDmytriw
| | - Jean-François Hak
- Department of Medical Imaging, University Hospital Timone APHM, Marseille, France. https://twitter.com/JFHak
| | - Géraud Forestier
- Department of neuroradiology, University Hospital of Limoges, Limoges, France. https://twitter.com/GeraudForestier
| | - Quentin Holay
- Department of Radiology, Sainte-Anne Military Hospital, Toulon, France
| | - Richard Olatunji
- Department of Radiology, College of Medicine, University of Ibadan, Ibadan, Nigeria. https://twitter.com/RICHARDOlat
| | - Ibrahim Alhabli
- Calgary Stroke Program, Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Foothills Medical Centre, Calgary, AB, Canada. https://twitter.com/ialhabli
| | - Lorena Nico
- Department of Neuroradiology, University Hospital Of Padova, Padova, Italy
| | - Jai J S Shankar
- Department of Radiology, Health Sciences Centre, Winnipeg, MB, Canada. https://twitter.com/shivajai1
| | - Adrien Guenego
- Department of Interventional Neuroradiology, Erasme University Hospital, Brussels, Belgium. https://twitter.com/GuenegoAdrien
| | - Jose L R Pascual
- Department of Anatomy, College of Medicine and Philippine General Hospital, University of the Philippines Manila, Manila, Philippines. https://twitter.com/drbrainhacker
| | - Thomas R Marotta
- Division of Diagnostic and Therapeutic Neuroradiology, Department of Radiology, St. Michael's Hospital, University of Toronto, ON, Canada. https://twitter.com/trmarot
| | - Juan I Errázuriz
- Department of Radiology, McGill University Health Centre (MUHC), Montreal, QC, Canada
| | - Amy W Lin
- Division of Diagnostic and Therapeutic Neuroradiology, Department of Radiology, St. Michael's Hospital, University of Toronto, ON, Canada
| | - Aderaldo Costa Alves
- Division of Neurosurgery, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada. https://twitter.com/jr_aderaldo
| | - Robert Fahed
- Division of Neurology, The Ottawa Hospital, Ottawa, ON, Canada
| | - Christine Hawkes
- Division of Neurology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada. https://twitter.com/CMHawkes
| | - Hubert Lee
- Division of Neurosurgery, Trillium Health Partners, Toronto, ON, Canada
| | - Elsa Magro
- Department of Neurosurgery, Hôpital de la Cavale Blanche, CHRU de Brest, Brest, France
| | - Lila Sheikhi
- Department of Neurology, University of Kentucky, Lexington, KY, USA. https://twitter.com/lila_sheikhi
| | - Tim E Darsaut
- Department of Surgery, Division of Neurosurgery, Walter C. Mackenzie Health Sciences Centre, University of Alberta Hospital, Edmonton, AB, Canada. https://twitter.com/tdarsaut
| | - Jean Raymond
- Department of Radiology, Radiation Oncology and Nuclear Medicine, Centre Hospitalier de l'Université de Montréal (CHUM), Montreal, QC, Canada.
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Slonimsky E, Upham K, Pepley S, Ouyang T, King T, Fiorelli M, Thamburaj K. Multiplanar CT evaluation of aneurysm rupture signs in subarachnoid hemorrhage. Emerg Radiol 2022; 29:427-435. [PMID: 35067812 DOI: 10.1007/s10140-022-02020-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Accepted: 01/06/2022] [Indexed: 10/19/2022]
Abstract
PURPOSE In subarachnoid hemorrhage, noncontrast CT features are used to guide the localization of ruptured aneurysms on CT angiography and DSA. Multiplanar CT may improve the localization of aneurysm rupture sites over axial plane CT alone. METHODS Multiplanar CT in three orthogonal planes was used to evaluate 94 cases of SAH. Two investigators independently evaluated each imaging plane for focal thick SAH with mass effect, intracerebral hemorrhage, focal edema, filling defect, subdural hemorrhage, and dominant intraventricular hemorrhage. Also, rupture site was qualitatively identified by combining these variables in each plane and combination of three planes. DSA served as the gold standard to locate the rupture sites. RESULTS Interobserver agreement was k 0.60 to 0.79 for axial, k 0.43 to 0.86 for coronal and k 0.43 to 0.74 for sagittal planes. Good to substantial agreement was observed for the localization of rupture site in three planes (focal SAH with mass effect - k 0.78 to 0.85; filling defect - k 0.95 to 1.0; intracerebral hemorrhage - k 1.0; focal edema k 1.0; subdural hemorrhage - k 0.61 to 0.83). Dominant intraventricular hemorrhage revealed significant association with DSA to locate ruptured aneurysms (Fisher's exact test - Pr < = P (< 0.001)). With non-missing data, frequency of correct ratings to locate rupture site was 66/67 (99%) in axial plane, 59/66 (89%) in coronal plane, 64/67 (96%) in sagittal plane and 77/77 (100%) in combined 3 planes. CONCLUSIONS Multiplanar CT head is more successful than axial plane CT alone for the localization of aneurysm rupture sites in SAH.
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Affiliation(s)
- Einat Slonimsky
- Department of Radiology, Penn State Health Milton Hershey Medical Center, Hershey, PA, 17036, USA
| | - Kent Upham
- Department of Imaging Sciences, University of Rochester Medical Center, Rochester, NY, USA
| | - Sarah Pepley
- Department of Radiology, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Tao Ouyang
- Department of Radiology, Penn State Health Milton Hershey Medical Center, Hershey, PA, 17036, USA
| | - Tonya King
- Department of Biostatistics, Penn State Health College of Medicine, Hershey, PA, USA
| | - Marco Fiorelli
- Department of Human Neuroscience, Sapienza University of Rome, Rome, Italy
| | - Krishnamoorthy Thamburaj
- Department of Radiology, Penn State Health Milton Hershey Medical Center, Hershey, PA, 17036, USA.
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Alimohammadi E, Ahadi P, Karbasforoushan A, Rahmani S, Bagheri SR, Abdi A. Nontraumatic Nonaneurysmal Subarachnoid Hemorrhage: Risk Factors, Complications, and Clinical Outcomes. INDIAN JOURNAL OF NEUROSURGERY 2021. [DOI: 10.1055/s-0040-1714302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022] Open
Abstract
Abstract
Background The present study aimed to investigate the risk factors, complications, and clinical outcomes of patients with nontraumatic, nonaneurysmal subarachnoid hemorrhage (NNSAH).
Methods We retrospectively evaluated 78 consecutive patients with NNSAH admitted to our center between April 2009 and April 2019. Patients were divided into two groups based on the distribution of blood in the CT scan, perimesencephalic subarachnoid hemorrhage ( PM-SAH) and nonperimesencephalic subarachnoid hemorrhage (nPM-SAH) groups. The outcome was assessed according to the Glasgow outcome scale (GOS). The demographic data and clinical records including age, sex, smoking history, hypertension, diabetes, history of anticoagulant medication, Glasgow coma score (GCS), Hunt–Hess (HH) grades, and in-hospital complications and clinical outcomes were retrospectively reviewed and compared between the two groups.
Results There were 45 patients (57.69%) in the PM-SAH group and 33 cases (42.30%) in the nPM-SAH group with the mean age of 53.98 ± 7.7 years. There were no significant differences between the two groups based on age, sex, smoking history, diabetes, hypertension, anticoagulation medication history, and HH grade at admission. The nPM-SAH group was significantly associated with a higher incidence of radiological and clinical vasospasm (p < 0.05). Moreover, the need for external ventricular drainage (EVD) placement because of the development of hydrocephalus was significantly higher in the nPM group (p < 0.05). Patients with PM-SAH had better clinical outcomes than those with nPM-SAH (p = 0.037).
Conclusions Our results showed that patients with nonaneurysmal subarachnoid hemorrhage (NSAH) had favorable clinical outcomes. The PM group had better clinical outcomes and lower complication rates in comparison with the nPM group. Repeated digital subtraction angiography (DSA) examinations are strongly recommended for patients with nPM-SAH.
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Affiliation(s)
- Ehsan Alimohammadi
- Department of Neurosurgery, Kermanshah University of Medical Sciences, Imam Reza Hospital, Kermanshah, Iran
| | - Paniz Ahadi
- Clinical Research Development Center of Taleghani and Imam Ali Hospital, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Ali Karbasforoushan
- Department of Anesthesiology, Kermanshah University of Medical Sciences, Imam Reza Hospital, Kermanshah, Iran
| | - Shamsoddin Rahmani
- Department of Neurosurgery, Kermanshah University of Medical Sciences, Imam Reza Hospital, Kermanshah, Iran
| | - Seyed Reza Bagheri
- Department of Neurosurgery, Kermanshah University of Medical Sciences, Imam Reza Hospital, Kermanshah, Iran
| | - Alireza Abdi
- Nursing and Midwifery School, Kermanshah University of Medical Sciences, Imam Reza Hospital, Kermanshah, Iran
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Wallace AN, Vyhmeister R, Viets R, Whisenant JT, Chatterjee AR, Kansagra AP, Cross DT, Moran CJ, Derdeyn CP. Quadrigeminal perimesencephalic subarachnoid hemorrhage. Clin Neurol Neurosurg 2015; 137:67-71. [PMID: 26151343 DOI: 10.1016/j.clineuro.2015.06.018] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2015] [Revised: 06/23/2015] [Accepted: 06/24/2015] [Indexed: 10/23/2022]
Abstract
OBJECTIVE A variant of perimesencephalic subarachnoid hemorrhage (PSAH) has been described characterized by blood centered in the quadrigeminal cistern and limited to the superior vermian and perimesencephalic cisterns. Herein, three cases of quadrigeminal PSAH are presented. MATERIALS AND METHODS Medical records of all patients who underwent digital subtraction angiography for evaluation of non-traumatic SAH between July 2002 and April 2012 were reviewed. Patients with anterior circulation aneurysms were excluded. Two blinded reviewers identified admission noncontrast CT scans with pretruncal and quadrigeminal patterns of PSAH. RESULTS The total cohort included 106 patients: 53% (56/106) with one or more negative digital subtraction angiograms and 47% (50/106) with posterior circulation or posterior communicating artery aneurysms. Three patients with quadrigeminal PSAH were identified, two with nonaneurysmal SAH and one with a posterior circulation aneurysm. Seventeen patients (16%; 17/106) with pretruncal PSAH were identified, none of whom were found to have an aneurysm. The quadrigeminal pattern comprised 11% (2/19) of cases of pretruncal or quadrigeminal nonaneurysmal PSAH. CONCLUSION A small subset of patients with nonaneurysmal PSAH present with blood centered in the quadrigeminal cistern, and the etiology of this pattern may be similar to that of the classic pretruncal variant. However, patients with quadrigeminal PSAH must still undergo thorough vascular imaging, including at least two digital subtraction angiograms, to exclude a ruptured aneurysm.
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Affiliation(s)
- Adam N Wallace
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 South Kingshighway Boulevard, Saint Louis, MO 63110, United States.
| | - Ross Vyhmeister
- Washington University School of Medicine, Saint Louis, MO, United States
| | - Ryan Viets
- Sharp Grossmont Hospital, San Diego, CA, United States
| | | | - Arindam R Chatterjee
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 South Kingshighway Boulevard, Saint Louis, MO 63110, United States
| | - Akash P Kansagra
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 South Kingshighway Boulevard, Saint Louis, MO 63110, United States
| | - DeWitte T Cross
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 South Kingshighway Boulevard, Saint Louis, MO 63110, United States
| | - Christopher J Moran
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 South Kingshighway Boulevard, Saint Louis, MO 63110, United States
| | - Colin P Derdeyn
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 South Kingshighway Boulevard, Saint Louis, MO 63110, United States
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