Impact of CT slice thickness on hematoma volume estimation by planimetry and ABC/2 in acute intracerebral hemorrhage

Feigin VL, Lawes CM, Bennett DA, Barker-Collo SL, Parag V (2009) Worldwide stroke incidence and early case fatality reported in 56 population-based studies: a systematic review. Lancet Neurol 8:355–369. https://doi.org/10.1016/S1474-4422(09)70025-0

Article  PubMed  Google Scholar 

Al-Mufti F, Thabet AM, Singh T, El-Ghanem M, Amuluru K, Gandhi CD (2018) Clinical and radiographic predictors of intracerebral hemorrhage outcome. Interv Neurol 7:118–136. https://doi.org/10.1159/000484571

Article  PubMed  PubMed Central  Google Scholar 

Broderick JP, Brott TG, Duldner JE, Tomsick T, Huster G (1993) Volume of intracerebral hemorrhage. A powerful and easy-to-use predictor of 30-day mortality. Stroke 24:987–993. https://doi.org/10.1161/01.str.24.7.987

Article  CAS  PubMed  Google Scholar 

Falcone GJ, Biffi A, Brouwers HB et al (2013) Predictors of hematoma volume in deep and lobar supratentorial intracerebral hemorrhage. JAMA Neurol 70:988–994. https://doi.org/10.1001/jamaneurol.2013.98

Article  PubMed  PubMed Central  Google Scholar 

Lin F, He Q, Tong Y et al (2021) Early deterioration and long-term prognosis of patients with intracerebral hemorrhage along with hematoma volume more than 20 ml: who needs surgery? Front Neurol 12:789060. https://doi.org/10.3389/fneur.2021.789060

Article  PubMed  Google Scholar 

LoPresti MA, Bruce SS, Camacho E et al (2014) Hematoma volume as the major determinant of outcomes after intracerebral hemorrhage. J Neurol Sci 345:3–7. https://doi.org/10.1016/j.jns.2014.06.057

Article  PubMed  Google Scholar 

Al-Shahi Salman R, Frantzias J, Lee RJ et al (2018) Absolute risk and predictors of the growth of acute spontaneous intracerebral haemorrhage: a systematic review and meta-analysis of individual patient data. Lancet Neurol 17:885–894. https://doi.org/10.1016/S1474-4422(18)30253-9

Article  PubMed  PubMed Central  Google Scholar 

Blacquiere D, Demchuk AM, Al-Hazzaa M et al (2015) Intracerebral hematoma morphologic appearance on noncontrast computed tomography predicts significant hematoma expansion. Stroke 46:3111–3116. https://doi.org/10.1161/STROKEAHA.115.010566

Article  CAS  PubMed  Google Scholar 

Boulouis G, Morotti A, Brouwers HB et al (2016) Association between hypodensities detected by computed tomography and hematoma expansion in patients with intracerebral hemorrhage. JAMA Neurol 73:961–968. https://doi.org/10.1001/jamaneurol.2016.1218

Article  PubMed  PubMed Central  Google Scholar 

Brouwers HB, Chang Y, Falcone GJ et al (2014) Predicting hematoma expansion after primary intracerebral hemorrhage. JAMA Neurol 71:158–164. https://doi.org/10.1001/jamaneurol.2013.5433

Article  PubMed  PubMed Central  Google Scholar 

Greenberg SM, Ziai WC, Cordonnier C et al (2022) 2022 guideline for the management of patients with spontaneous intracerebral hemorrhage: a guideline from the American Heart Association/American Stroke Association. Stroke 53:e282–e361. https://doi.org/10.1161/STR.0000000000000407

Article  CAS  PubMed  Google Scholar 

Huttner HB, Steiner T, Hartmann M et al (2006) Comparison of ABC/2 estimation technique to computer-assisted planimetric analysis in warfarin-related intracerebral parenchymal hemorrhage. Stroke 37:404–408. https://doi.org/10.1161/01.STR.0000198806.67472.5c

Article  PubMed  Google Scholar 

Webb AJ, Ullman NL, Morgan TC et al (2015) Accuracy of the ABC/2 score for intracerebral hemorrhage: systematic review and analysis of MISTIE, CLEAR-IVH, and CLEAR III. Stroke 46:2470–2476. https://doi.org/10.1161/STROKEAHA.114.007343

Article  PubMed  PubMed Central  Google Scholar 

Pradilla G, Ratcliff JJ, Hall AJ et al (2024) Trial of early minimally invasive removal of intracerebral hemorrhage. N Engl J Med 390:1277–1289. https://doi.org/10.1056/NEJMoa2308440

Article  CAS  PubMed  Google Scholar 

Butcher KS, Buck B, Dowlatshahi D et al (2025) Acute blood pressure lowering and risk of ischemic lesions on mri after intracerebral hemorrhage. JAMA Neurol 82:543–550. https://doi.org/10.1001/jamaneurol.2025.0586

Article  PubMed  PubMed Central  Google Scholar 

Beck J, Fung C, Strbian D et al (2024) Decompressive craniectomy plus best medical treatment versus best medical treatment alone for spontaneous severe deep supratentorial intracerebral haemorrhage: a randomised controlled clinical trial. Lancet 403:2395–2404. https://doi.org/10.1016/S0140-6736(24)00702-5

Article  PubMed  Google Scholar 

Divani AA, Majidi S, Luo X et al (2011) The ABCs of accurate volumetric measurement of cerebral hematoma. Stroke 42:1569–1574. https://doi.org/10.1161/STROKEAHA.110.607861

Article  PubMed  Google Scholar 

Dowlatshahi D, Demchuk AM, Flaherty ML et al (2011) Defining hematoma expansion in intracerebral hemorrhage: relationship with patient outcomes. Neurology 76:1238–1244. https://doi.org/10.1212/WNL.0b013e3182143317

Article  CAS  PubMed  PubMed Central  Google Scholar 

Kothari RU, Brott T, Broderick JP et al (1996) The ABCs of measuring intracerebral hemorrhage volumes. Stroke 27:1304–1305. https://doi.org/10.1161/01.str.27.8.1304

Article  CAS  PubMed  Google Scholar 

Barras CD, Tress BM, Christensen S et al (2009) Density and shape as CT predictors of intracerebral hemorrhage growth. Stroke 40:1325–1331. https://doi.org/10.1161/STROKEAHA.108.536888

Article  PubMed  Google Scholar 

Yushkevich PA, Yang G, Gerig G (2016) ITK-SNAP: An interactive tool for semi-automatic segmentation of multi-modality biomedical images. Annu Int Conf IEEE Eng Med Biol Soc 2016:3342–3345. https://doi.org/10.1109/EMBC.2016.7591443

Article  PubMed  PubMed Central  Google Scholar 

Fedorov A, Beichel R, Kalpathy-Cramer J et al (2012) 3D Slicer as an image computing platform for the quantitative imaging network. Magn Reson Imaging 30:1323–1341. https://doi.org/10.1016/j.mri.2012.05.001

Article  PubMed  PubMed Central  Google Scholar 

Weissflog JS, Keller EJ, Neymeyer ML, Morotti A, Dowlatshahi D, Nawabi J (2026) Systematic review of commercial artificial intelligence tools for the detection and volume quantification in intracerebral hemorrhage. Eur Radiol 36:367–395. https://doi.org/10.1007/s00330-025-11834-4

Article  PubMed  Google Scholar 

Kiewitz J, Aydin OU, Hilbert A et al (2024) Deep learning-based multiclass segmentation in aneurysmal subarachnoid hemorrhage. Front Neurol 15:1490216. https://doi.org/10.3389/fneur.2024.1490216

Article  PubMed  PubMed Central  Google Scholar 

Anderson CS, Heeley E, Huang Y et al (2013) Rapid blood-pressure lowering in patients with acute intracerebral hemorrhage. N Engl J Med 368:2355–2365. https://doi.org/10.1056/NEJMoa1214609

Article  CAS  PubMed  Google Scholar 

Anderson CS, Huang Y, Wang JG et al (2008) Intensive blood pressure reduction in acute cerebral haemorrhage trial (INTERACT): a randomised pilot trial. Lancet Neurol 7:391–399. https://doi.org/10.1016/S1474-4422(08)70069-3

Article  PubMed  Google Scholar 

Mendelow AD, Gregson BA, Fernandes HM et al (2005) Early surgery versus initial conservative treatment in patients with spontaneous supratentorial intracerebral haematomas in the International Surgical Trial in Intracerebral Haemorrhage (STICH): a randomised trial. Lancet 365:387–397. https://doi.org/10.1016/S0140-6736(05)17826-X

Article  PubMed  Google Scholar 

Mendelow AD, Gregson BA, Rowan EN, Murray GD, Gholkar A, Mitchell PM (2013) Early surgery versus initial conservative treatment in patients with spontaneous supratentorial lobar intracerebral haematomas (STICH II): a randomised trial. Lancet 382:397–408. https://doi.org/10.1016/s0140-6736(13)60986-1

Article  PubMed  PubMed Central  Google Scholar 

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