Neuroanatomical Features That Predict Response to Electroconvulsive Therapy Combined with Antipsychotics in Schizophrenia: A Magnetic Resonance Imaging Study Using Radiomics Strategy Many patients who have schizophrenia do not receive adequate treatment due to their failure to respond to antipsychotics. With over 30% of patients with schizophrenia demonstrating...
Neuroanatomical Features That Predict Response to Electroconvulsive Therapy Combined with Antipsychotics in Schizophrenia: A Magnetic Resonance Imaging Study Using Radiomics Strategy
Many patients who have schizophrenia do not receive adequate treatment due to their failure to respond to antipsychotics. With over 30% of patients with schizophrenia demonstrating poor response to antipsychotics, there was a need to determine early if a patient would be responsive or not (Xi et al., 2020). Electroconvulsive therapy (ECT) is an effective alternative for treating chronic patients with refractory symptoms. ECT is only used for patients who have demonstrated unsuccessful treatment using antipsychotic medication. ECT can provoke cognitive impairment, and it is invasive compared to pharmacotherapy and costly. Therefore, before it is used for treating the patient, health care professionals should determine if the patient will be responsive to the treatment. The use of neuroimaging tools offers vital insights for assessing the likelihood of a patient responding positively to treatment. The study investigates if brain structure-based signature can be used to predict ECT response in patients with schizophrenia. There was a total of 57 patients used as the sample for the study at baseline. After treatment using ECT and antipsychotics, 28 patients were classified as responders and 29 non-responders (Xi et al., 2020). The authors found that they could accurately determine the responders with an accuracy of 90.91%. Therefore, with the possibility of determining patients who would respond positively to ECT, we can avoid implementing the treatment in patients who would be non-responders saving treatment costs and time. To predict responders and non-responders, the authors extracted features from the inferior frontal gyrus, insula, cingulate cortex, thalamus, temporal and parietal lobes, and hippocampus (Xi et al., 2020).
The study implies that we can avoid unnecessary treatment of a patient who would not be responsive to ECT treatment. Considering the invasiveness of the treatment and cost implication, it would not be fair to allow a patient to undergo treatment only for them not to receive any tangible results. As health care professionals, we have a duty to ensure that the treatment offered will be beneficial to the patient and they can recover if the treatment is administered. Therefore, when it comes to ECT use, we should only use it for patients who are responsive to the treatment (Xi et al., 2020). Having determined the accuracy of the prediction, all ECT health care professionals should only administer the treatment to patients they have analyzed and determined will positively respond to treatment.
The study contributes significantly to future treatment of schizophrenia in that psychiatrists can now determine the impact of treatment before it is administered, reducing the trial-and-error methods for treatment. Evidence-based treatments have additional support, and in case the treatment is still being considered, it can now be fully implemented. Neuroanatomy is effective in treating psychiatric disorders because most of these disorders stem from the brain. Therefore, we should always include neuroanatomy before implementing any treatment regimen. Neuroanatomy can uncover other cerebral makers that can determine treatment efficacy before it is administered to a patient. While other biomarkers are being used to predict other treatment plans, we should endeavor to uncover other alternatives to ensure and confirm the efficacy of a treatment (Schildkrout, 2017). Structural MRI offers vital information on mental disorders like brain structure features. Using data from the structural MRI, we can transform clinical practice by eliminating the use of specific treatments on non-responsive patients. Also, we can be confident that the initiated treatment will assist the patient and only await the recovery or management of the disorder.
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