Modified Computed Tomography Classification for Chronic Subdural Hematoma Features Good Interrater Agreement: A Single-Center Retrospective Cohort Study

Takei, Jun; Hirotsu, Tatsuya; Hatano, Keisuke; Ishibashi, Toshiyuki; Inomata, Takayuki; Noda, Yasuto; Morooka, Satoru; Murayama, Yuichi

doi:10.1016/j.wneu.2021.04.052

Cited by 13 publications

(11 citation statements)

References 31 publications

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“…Although we calculated a 2.397-fold risk increase for the Nakaguchi classification, this was spread out over four levels of hematoma organization. The eight subtypes within the extended classification allow for a more precise and adequate recurrence risk estimation compared to the Nakaguchi and more recently published classification systems [ 25 ]. Inter-rater reliability in imaging classification is often high but proved lower in the eight-subtype extended classification compared to the Nakaguchi classification.…”

Section: Discussionmentioning

confidence: 99%

Risk factors of recurrence in chronic subdural hematoma and a proposed extended classification of internal architecture as a predictor of recurrence

et al. 2022

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Chronic subdural hematomas (cSDHs) constitute one of the most prevalent intracranial disease entities requiring surgical treatment. Although mostly taking a benign course, recurrence after treatment is common and associated with additional morbidity and costs. Aim of this study was to develop hematoma-specific characteristics associated with risk of recurrence. All consecutive patients treated for cSDH in a single university hospital between 2015 and 2019 were retrospectively considered for inclusion. Size, volume, and midline shift were noted alongside relevant patient-specific factors. We applied an extended morphological classification system based on internal architecture in CT imaging consisting of eight hematoma subtypes. A logistic regression model was used to assess the classification’s performance on predicting hematoma recurrence. Recurrence was observed in 122 (32.0%) of 381 included patients. Apart from postoperative depressed brain volume (OR 1.005; 95% CI 1.000 to 1.010; p = 0.048), neither demographic nor factors related to patient comorbidity affected recurrence. The extended hematoma classification was identified as a significant predictor of recurrence (OR 1.518; 95% CI 1.275 to 1.808; p < 0.001). The highest recurrence rates were observed in hematomas of the homogenous (isodense: 41.4%; hypodense: 45.0%) and sedimented (50.0%) types. Our results support that internal architecture subtypes might represent stages in the natural history of chronic subdural hematoma. Detection and treatment at a later stage of spontaneous repair can result in a reduced risk of recurrence. Based on their high risk of recurrence, we advocate follow-up after treatment of sedimented and homogenous hematomas.

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Section: Discussionmentioning

confidence: 99%

Risk factors of recurrence in chronic subdural hematoma and a proposed extended classification of internal architecture as a predictor of recurrence

et al. 2022

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“…Gandhoke et al [9] Nagahori et al [18] CT Homogenous laminar Homogenous laminar Separated Trabecular Nakaguchi et al [19] Takei et al [25]…”

Section: Scar Inflammatorymentioning

confidence: 99%

“…e mass lesion and symptoms spontaneously turn to the resolution phase, which is promoted by corticosteroids. [23] e active healing processes of CSDH are observed and staged by histopathology, [9,18] CT, [19,20,25] and endoscopy. [13,26] Nagahori et al [18] classified the histopathological findings of the outer membrane into four stages: I, noninflammatory; II, inflammatory; III, hemorrhagic inflammatory; and IV, scar inflammatory stages.…”

Section: Introductionmentioning

confidence: 99%

“…[13,26] Nagahori et al [18] classified the histopathological findings of the outer membrane into four stages: I, noninflammatory; II, inflammatory; III, hemorrhagic inflammatory; and IV, scar inflammatory stages. Nakaguchi et al [19,25] classified the CT findings into four groups, namely, the homogenous, laminar, separated, and trabecular types. ey indicated the relationship between the CT findings and hematoma age; the homogenous and laminar types were seen in the early phase of the CSDH, the separated type was seen in the following most active phase, and the trabecular type was seen in the later resolving phase.…”

Section: Introductionmentioning

confidence: 99%

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Endoscopically observed outer membrane of chronic subdural hematoma after endovascular embolization of middle meningeal artery

Nomura¹,

Haji²,

Fujiyama³

et al. 2022

Surgical Neurology International

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Background: Embolization of the middle meningeal artery (MMA) has been established for chronic subdural hematoma (CSDH). Neuroendoscopic observation of the outer membrane of the hematoma was carried out after embolization. The treatment mechanism of embolization is discussed, focusing on the vasculature and inflammation of the membrane. Methods: Four patients with recurrent CSDH were included in this study. The MMA was embolized using Embosphere® particles in three patients. The outer membrane was observed with normal and narrow band images (NBIs). Results: The net-like vessels were not obstructed in the whole area of the outer membrane, but in a patchy fashion of embolized areas surrounded by nonembolized areas. In two patients, the nonembolized areas showed a hemorrhagic inflammatory red color. Histopathological examination confirmed hypertrophic dura with leukocyte infiltration. Dilated dural arteries and proliferated sinusoid arteries were located in the deep and superficial border cell layers. These arteries were visualized as green and brown on NBI, respectively. In the embolized area, the red membrane turned pink, indicating ischemia and subsiding inflammatory hyperemia. In the third patient, the outer membrane was white in both the nonembolized and embolized areas in endoscopic view, and the net-like vessels were sparse in both endoscopy and histology, indicating a scar inflammatory phase. The membrane transition was not observed in the patient that did not undergo embolization. Conclusion: Endoscopic observation revealed that embolization of the MMA blocked both the dural and sinusoidal arteries. Ischemic transformation causing the suppression of inflammation of the outer membrane is a suggested mechanism of MMA embolization.

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“…In addition, different definitions of predictors could have contributed to observed differences in the effects of predictors. For example, the inter-rater variability concerning the classification of hematoma types is considered low [ 47 ], but assessing septations on a CT-scan is prone to inter-rater variability because membranes cannot always be clearly recognized on CT-scans [ 39 ]. If the predictor “septations” was not specifically scored in patients, trabecular hematomas were marked as “septations present.” All other hematoma types (homogenous, mixed, and separated) were marked as “septations absent.” This restraint in detecting septations in the validation cohort is expected to lead to an underestimation of septations in our population, because septations can also occur in homogenous, mixed, and separated hematoma types.…”

Section: Discussionmentioning

confidence: 99%

External validation of prognostic models predicting outcome after chronic subdural hematoma

et al. 2022

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Background Several prognostic models for outcomes after chronic subdural hematoma (CSDH) treatment have been published in recent years. However, these models are not sufficiently validated for use in daily clinical practice. We aimed to assess the performance of existing prediction models for outcomes in patients diagnosed with CSDH. Methods We systematically searched relevant literature databases up to February 2021 to identify prognostic models for outcome prediction in patients diagnosed with CSDH. For the external validation of prognostic models, we used a retrospective database, containing data of 2384 patients from three Dutch regions. Prognostic models were included if they predicted either mortality, hematoma recurrence, functional outcome, or quality of life. Models were excluded when predictors were absent in our database or available for < 150 patients in our database. We assessed calibration, and discrimination (quantified by the concordance index C) of the included prognostic models in our retrospective database. Results We identified 1680 original publications of which 1656 were excluded based on title or abstract, mostly because they did not concern CSDH or did not define a prognostic model. Out of 18 identified models, three could be externally validated in our retrospective database: a model for 30-day mortality in 1656 patients, a model for 2 months, and another for 3-month hematoma recurrence both in 1733 patients. The models overestimated the proportion of patients with these outcomes by 11% (15% predicted vs. 4% observed), 1% (10% vs. 9%), and 2% (11% vs. 9%), respectively. Their discriminative ability was poor to modest (C of 0.70 [0.63–0.77]; 0.46 [0.35–0.56]; 0.59 [0.51–0.66], respectively). Conclusions None of the examined models showed good predictive performance for outcomes after CSDH treatment in our dataset. This study confirms the difficulty in predicting outcomes after CSDH and emphasizes the heterogeneity of CSDH patients. The importance of developing high-quality models by using unified predictors and relevant outcome measures and appropriate modeling strategies is warranted.

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Modified Computed Tomography Classification for Chronic Subdural Hematoma Features Good Interrater Agreement: A Single-Center Retrospective Cohort Study

Cited by 13 publications

References 31 publications

Risk factors of recurrence in chronic subdural hematoma and a proposed extended classification of internal architecture as a predictor of recurrence

Risk factors of recurrence in chronic subdural hematoma and a proposed extended classification of internal architecture as a predictor of recurrence

Endoscopically observed outer membrane of chronic subdural hematoma after endovascular embolization of middle meningeal artery

External validation of prognostic models predicting outcome after chronic subdural hematoma

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