Massive cerebral infarction (MCI) occurs in approximately 10.0% of all strokes and has a mortality rate of up to 80.0% (1, 2). MCI is a severe ischemic stroke caused by occlusion of the proximal middle cerebral artery (MCA) or internal carotid artery terminus (ICA). Relative studies have reported on the benefits in clinical practice of early imaging signs of acute cerebral infarction on computed tomography (CT) (3–5). Therefore, it is vital to establish a prediction model based on early clinical and imaging data to facilitate the early diagnosis of MCI caused by anterior circulation occlusion. A prediction model can provide an effective time window and outcome prediction of endovascular therapy in MCI patients.

A nomogram is a graphical representation of a clinical prediction model built on multivariate regression analysis, performed by assigning scores based on predictive variable values, then calculating total scores and converting them to estimate outcome risk. The results of a prediction model have higher readability and practical value. Thus far, there have been few studies on prediction model based on early CT imaging signs and clinical risk factors of MCI. Hence, this study focuses on establishing a prediction model of early CT imaging signs and clinical information in order to help clinicians identify patients with MCI earlier, give timely targeted treatment, and maximize the quality of life and prognosis of patients.

This study demonstrates that the insular ribbon sign can be used as an independent predictor of MCI. The principle of the insular ribbon sign is that the cerebral tissue in the ischemic area begins to become edematous after cerebrovascular occlusion due to narrowing or occlusion of the perforator arteries that supply the insular region. Since perforator arteries are first affected by hemodynamic alterations, ischemia and infarction occur earliest in the insular region. Within 3–6 h after the onset of infarction, CT early low-density changes (insular ribbon signs, obscuration of the lentiform nucleus) exceeded 50.0% of the area supplied by the MCA, with 61.0% sensitivity and 94.0% specificity in predicting massive infarction. The earlier the CT examination is performed, the higher specificity and the lower sensitivity of its findings (13–16). In addition, obscuration of the lentiform nucleus appears within 4–6 h, and the HMCAS appears within 30 min of onset; these findings have a specificity of 85.0%−100.0% (12, 17, 18).

In this study, results of logistic regression analysis showed that the HMCAS was not an independent predictor of MCI, though some relevant studies have shown a close relationship between the HMCAS and the dependent variable. After multiple CT, CTA, MRI, MRA, and autopsy examinations, the study confirmed that the HMCAS had low sensitivity (only 7.0%−69.0%) and high specificity (85.0%−100.0%) in the diagnosis of cerebral infarction (12, 19–21). Cerebral infarction may be diagnosed if the HMCAS is present (14, 22). The appearance of the HMCAS is a transient phenomenon, and its presence may be related to the hypercoagulable state of blood or the formation of emboli. Once the thrombus dissolves or its density gradually changes, the HMCAS will disappear, so the positive rate of the HMCAS is high in the early stage of disease (20, 23). Theoretically, the HMCAS should be present at the early stage of an occlusion that occurs in the MCA area. However, Leys et al. (20) and Manelfe et al. (14) reported that the occurrence rate of HMCAS is low, 30.9 and 17.7% respectively, which is consistent with our results. There are many reasons that contribute to the low occurrence rate of the HMCAS and mainly include the following: (1) the time from onset to the first CT examination in patients with cerebral infarction is different. Numerous studies have shown that the HMCAS detection rate gradually decreases within 3, 6, 12–24 h, and 6–8 days after the onset of the disease (13, 21, 24, 25). Some patients have been confirmed to have MCA infarction by CTA, but the HMCAS does not appear because those patients have not only MCA occlusion but also ICA occlusion, resulting in an extension of the thrombus. Therefore, the HMCAS may not appear immediately after onset. Based on this, CT scans should be performed earlier to help improve the detection rate of the HMCAS; (2) in the ultra-early stage of cerebral infarction, the HMCAS is not obvious, so it is difficult to correctly detect the HMCAS. When the radiologist knows that the patient has a clinical presentation of MCA or detects the HMCAS in one of two CT examination comparisons, the positive rate of the HMCAS tends to increase (18).

The results from clinical data of this study showed that the NIHSS score, reperfusion therapy, previous cerebral infarction, and atrial fibrillation are the best predictors of the occurrence of MCI. The NHISS score is highly comprehensive and has been widely used in clinical practice to assess stroke, and a high NIHSS score is now generally accepted in predicting MCI outcome (26). However, some studies (27) have found that an NIHSS score ≥15 in patients with right hemisphere infarction or an NIHSS score ≥20 in patients with left hemisphere infarction is a risk factor for massive occupancy effects. The NIHSS score emphasizes aphasia and therefore may be overestimated in the evaluation of patients with dominant hemispheric infarction. Timely reperfusion therapy in patients with acute ischemic cerebral infarction can revascularize reversibly damaged cerebral tissue around the infarction, or the “ischemic penumbra,” which can reduce the final infarct volume of stroke. The earlier the treatment is performed, the better the prognosis. The speed of development of the ischemic penumbra is mainly influenced by collateral circulation. Timely establishment of collateral circulation is conducive to restore the blood supply of the ischemic penumbra and greatly improve the blood circulation status. In this study, 61.3% of patients in the MCI group were treated with reperfusion, and poor collateral circulation may be the reason for this phenomenon. Cerebral cells are permanent and non-renewable. Patients with previous cerebral infarction do not have a significantly increased risk of secondary cerebral infarction. In this study, only 13.3% of patients in the MCI group had a secondary cerebral infarction; this may be related to timely medication, active control of hypertension, hyperlipidemia, hyperglycemia, and habits (no smoking, no alcohol, and doing exercise). Atrial fibrillation is one of the important risk factors for cerebral infarction. Once the mural thrombus formed by atrial fibrillation detaches and enters the internal carotid artery system, it will lead to sudden interruption of blood flow in the cerebral tissue, and collateral circulation cannot be established in time. Therefore, the lesion infarction area is large, and the disease progress is rapid.

In addition, studies have shown that nausea and vomiting occurring within 24 h of disease onset, increased body temperature, peripheral leukocytes, infarct size ≥MCA blood supply range within 48 h, the Alberta Stroke Program Early CT Score (ASPECTS), early MRI score, and collateral circulation score within 8 h of onset can be used as early predictors of MCI. Among them, infarct size ≥MCA blood supply range and increased body temperature have relatively higher accuracy in predicting MCI (28, 29). Previous studies (30, 31) have demonstrated that aging, hypertension, smoking, alcohol drinking, systolic blood pressure, and diastolic blood pressure at admission are risk factors for the development of MCI. However, these results were not obtained in this study, probably due to the single-center and small sample size. Multicenter and large sample size studies are required in the future.

There are several limitations of this study. First, this study is a retrospective study with small sample size. Second, CT was the only imaging modality. Finally, CT imaging with a 5 mm thickness and a 3 mm reconstruction may result in a reduced positive rate of the HMCAS, obscuration of the lentiform nucleus and insular ribbon sign.

In conclusion, based on early imaging signs and clinical data, this study provided a good prediction model to improve the sensitivity, specificity, and accuracy of early prediction of MCI. In the meantime, it will help clinicians improve patient outcomes and reduce the mortality and disability rate of MCI.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The studies involving human participants were reviewed and approved by the Ethics Committee of the General Hospital of Northern Theater Command. The patients/participants provided their written informed consent to participate in this study.

YD and JC contributed to the idea and manuscript preparation. BY, SQ, XW, and ZC helped perform the analysis with constructive discussions and revise manuscript. JL and LZ collected the imaging data. All authors discussed the results and revised the manuscript.

Funding for this study was provided in part by Project of Natural Science Foundation of Shenyang (grant no. 20-205-4-044), Project of Natural Science Foundation of Liaoning Province (grant no. 201602768), and Project of Scientific Research Foundation for the PhD of Liaoning Province (grant no. 2019-BS-267).

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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