Treatment decision in ruptured intracranial aneurysms: comparison between multi-detector row CT angiography and digital subtraction angiography

Cost-Effective Analysis of Different Diagnostic Strategies in Screening for Aneurysms After Spontaneous Subarachnoid Hemorrhage

PURPOSE

With an increasing number of patients being treated by coiling for aneurysms, using computed tomographic angiography (CTA) or magnetic resonance angiography (MRA) as an initial screening test becomes less important because digital subtraction angiography (DSA) is the first step of endovascular treatment procedure. The objective of this study is to investigate whether CTA or MRA remained to be the optimal screening strategy in patients with spontaneous subarachnoid hemorrhage (SAH).

METHODS

CTA, MRA, and DSA strategy were evaluated in a decision tree model created with TreeAge Pro Suite 2011. Input parameters were derived from published literature and our institutional database. Base case and sensitivity analyses were conducted to assess the cost-effectiveness of each strategy. A Monte Carlo simulation was performed with all parameters ranged among their distributions to evaluate the validation of results.

RESULTS

The base case scenario showed that MRA was the most cost-effective strategy. Using a willingness-to-pay threshold of ¥70,892/quality adjusted life year, MRA remained to be most cost-effective when its sensitivity is >0.907. DSA was not cost-effective compared to CTA or MRA unless over 91.56% of patients were treated by coiling. The Monte Carlo simulation reported DSA not to be a cost-effective strategy at willingness-to-pay of ¥70,892 in 99.99% of the iterations.

CONCLUSION

DSA is not cost-effective compared to CTA or MRA and should not be used as the initial diagnostic tool for spontaneous SAH.

Deep learning assistance increases the detection sensitivity of radiologists for secondary intracranial aneurysms in subarachnoid hemorrhage

Purpose

To evaluate whether a deep learning model (DLM) could increase the detection sensitivity of radiologists for intracranial aneurysms on CT angiography (CTA) in aneurysmal subarachnoid hemorrhage (aSAH).

Methods

Three different DLMs were trained on CTA datasets of 68 aSAH patients with 79 aneurysms with their outputs being combined applying ensemble learning (DLM-Ens). The DLM-Ens was evaluated on an independent test set of 104 aSAH patients with 126 aneuryms (mean volume 129.2 ± 185.4 mm³, 13.0% at the posterior circulation), which were determined by two radiologists and one neurosurgeon in consensus using CTA and digital subtraction angiography scans. CTA scans of the test set were then presented to three blinded radiologists (reader 1: 13, reader 2: 4, and reader 3: 3 years of experience in diagnostic neuroradiology), who assessed them individually for aneurysms. Detection sensitivities for aneurysms of the readers with and without the assistance of the DLM were compared.

Results

In the test set, the detection sensitivity of the DLM-Ens (85.7%) was comparable to the radiologists (reader 1: 91.2%, reader 2: 86.5%, and reader 3: 86.5%; Fleiss κ of 0.502). DLM-assistance significantly increased the detection sensitivity (reader 1: 97.6%, reader 2: 97.6%,and reader 3: 96.0%; overall P=.024; Fleiss κ of 0.878), especially for secondary aneurysms (88.2% of the additional aneurysms provided by the DLM).

Conclusion

Deep learning significantly improved the detection sensitivity of radiologists for aneurysms in aSAH, especially for secondary aneurysms. It therefore represents a valuable adjunct for physicians to establish an accurate diagnosis in order to optimize patient treatment.

Fully automated detection and segmentation of intracranial aneurysms in subarachnoid hemorrhage on CTA using deep learning

In aneurysmal subarachnoid hemorrhage (aSAH), accurate diagnosis of aneurysm is essential for subsequent treatment to prevent rebleeding. However, aneurysm detection proves to be challenging and time-consuming. The purpose of this study was to develop and evaluate a deep learning model (DLM) to automatically detect and segment aneurysms in patients with aSAH on computed tomography angiography. In this retrospective single-center study, three different DLMs were trained on 68 patients with 79 aneurysms treated for aSAH (2016–2017) using five-fold-cross-validation. Their outputs were combined to a single DLM via ensemble-learning. The DLM was evaluated on an independent test set consisting of 185 patients with 215 aneurysms (2010–2015). Independent manual segmentations of aneurysms in a 3D voxel-wise manner by two readers (neurosurgeon, radiologist) provided the reference standard. For aneurysms > 30 mm³ (mean diameter of ~ 4 mm) on the test set, the DLM provided a detection sensitivity of 87% with false positives (FPs)/scan of 0.42. Automatic segmentations achieved a median dice similarity coefficient (DSC) of 0.80 compared to the reference standard. Aneurysm location (anterior vs. posterior circulation; P = .07) and bleeding severity (Fisher grade ≤ 3 vs. 4; P = .33) did not impede detection sensitivity or segmentation performance. For aneurysms > 100 mm³ (mean diameter of ~ 6 mm), a sensitivity of 96% with DSC of 0.87 and FPs/scan of 0.14 were obtained. In the present study, we demonstrate that the proposed DLM detects and segments aneurysms > 30 mm³ in patients with aSAH with high sensitivity independent of cerebral circulation and bleeding severity while producing FP findings of less than one per scan. Hence, the DLM can potentially assist treating physicians in aSAH by providing automated detection and segmentations of aneurysms.

Subarachnoid hemorrhage in ten questions

Traumatic subarachnoid hemorrhage (SAH) has an annual incidence of 9 per 100 000 people. It is a rare but serious event, with an estimated mortality rate of 40% within the first 48hours. In 85% of cases, it is due to rupture of an intracranial aneurysm. In the early phase, during the first 24hours, cerebral CT, combined with intracranial CT angiography is recommended to make a positive diagnosis of SAH, to identify the cause and to investigate for an intracranial aneurysm. Cerebral MRI may be proposed if the patient's clinical condition allows it. FLAIR imaging is more sensitive than CT to demonstrate a subarachnoid hemorrhage and offers greater degrees of sensitivity for the diagnosis of restricted subarachnoid hemorrhage in cortical sulcus. A lumbar puncture should be performed if these investigations are normal while clinical suspicion is high.

Postoperative Assessment of Clipped Aneurysms With 64-Slice Computerized Tomography Angiography

BACKGROUND

Multidetector computerized tomography angiography (MDCTA) is now a widely accepted technique for the management of intracranial aneurysms.

OBJECTIVE

To evaluate its accuracy for the postoperative assessment of clipped intracranial aneurysms.

METHODS

We analyzed a consecutive series of 31 patients that underwent direct surgical clipping procedures of 38 aneurysms. A 64 slice MDCT scanner (Aquilion 64, Toshiba) was used and results were compared with digital subtraction angiographies (DSA). Two independent neuroradiologists analyzed the following data: examination quality, artifacts, aneurysm remnant, and patency of collateral branches. Interobserver agreement, sensitivity, and specificity were calculated.

RESULTS

Seventy-nine percent of the aneurysms were located in the anterior circulation. Significant artifacts were found with multiple and cobalt-alloy clips. According to DSA, remnants >2 mm were found in 21% of the cases, and 2 patients had one collateral branch occluded. Sensitivity and specificity of 64-MDCTA for the detection of aneurysm remnants were 50% and 100%, respectively. Sensitivity and specificity of 64-MDCTA for the detection of a significant remnant (>2 mm) and the detection of the occlusion of a collateral branch were, respectively, 67% and 100% and 50% and 100%. No relationship was found with the location, type, shape, size, or number of clips, but missed remnants tended to be larger with cobalt-alloy clips.

CONCLUSIONS

64-MDCTA is a valuable technique to assess the presence of a significant postoperative remnant in single titanium clip application cases and might be useful for long-term follow-up. DSA remains the most accurate postoperative radiological examination.