Hypoxic Brain Damage in Methadone Misuse: Insights from MRI Imaging and Comparative Study

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Methods: Conducted as a cross-sectional comparative study at Kamali Hospital in Karaj, Iran, the research included male participants comprising methadone users, opium users, and controls. Inclusion criteria were stringent, focusing on substance use duration and absence of brain structural disorders. MRI scans were performed using a 1.5T MRI scanner. Qualitative MRI assessments and chi-square tests analyzed associations between substance use and hypoxia, while logistic regression examined potential confounding variables. Results: Significant hypoxia was observed in the methadone group (16.7%, 5/24; p = 0.00057), with no cases in the opium or control groups. Logistic regression analysis showed no significant predictors of hypoxia regarding dose, duration of use, or age. MRI findings in methadone users with hypoxia included varied ADC intensities, high signal intensities on T2-weighted and diffusion-weighted imaging (DWI) sequences, and angiogenesis patterns on TOF sequences. The co-use of methadone and alcohol was noted in three of the five hypoxia cases. Conclusion: Methadone misuse, particularly with alcohol, poses a significant risk of hypoxia, detectable via MRI. This study underscores the need for routine MRI monitoring, stricter regulation of non-prescribed methadone, and enhanced public health education to mitigate misuse risks. Future research should expand sample sizes and incorporate advanced imaging techniques to further elucidate methadone's neurological impact. Methadone Hypoxia MRI Substance Use Brain Disorders Opioids Public Health Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Methadone, a synthetic opioid introduced in the 1960s, plays a critical role in the management of opioid withdrawal symptoms and chronic pain [1, 2]. As a racemic mixture, the (R)-methadone enantiomer is the active component responsible for its therapeutic effects [3]. Despite its common oral administration, methadone can also be delivered via rectal, sublingual, and intravenous routes, enhancing its versatility in clinical settings [4, 5]. Methadone's analgesic properties arise from its multi-faceted mechanisms of action, which include opioid receptor activation, NMDA receptor antagonism, and inhibition of serotonin and norepinephrine reuptake [6, 7]. These mechanisms not only underpin its efficacy as a potent analgesic but also distinguish methadone from other long-acting opioids through its unique pharmacological attributes, such as fat solubility and high plasma protein binding affinity [8]. Consequently, methadone exhibits a prolonged duration of action, albeit with a variable terminal half-life ranging from 15 to 50 hours, necessitating careful dosage titration and frequent monitoring to prevent drug accumulation and adverse effects [9]. Beyond its primary use in opioid withdrawal management, methadone is integral to Methadone Maintenance Treatment (MMT) programs, significantly reducing injection drug use and transmission rates of HIV and hepatitis C virus [10, 11]. Its effectiveness extends to managing various chronic pain conditions, including cancer and neuropathic pain, as well as acute post-operative pain, due to its combined analgesic and antihyperalgesic effects [12–14]. Methadone's therapeutic benefits are counterbalanced by substantial risks, especially in the context of poly-drug use, which increases the potential for adverse interactions and overdose [15–21]. Methadone overdose significantly contributes to opioid-related mortality, often leading to severe outcomes such as respiratory depression and cardiac arrest [22–24]. Imaging studies have revealed methadone-induced neurotoxicity, showing specific brain abnormalities [25–29]. High doses of methadone can cause severe hypoxia, raising the risk of stroke and delay post-hypoxic encephalopathy. MRI scans of affected patients often display diffuse abnormal T2 signals in the corona radiata, centrum semiovale, and subcortical white matter, indicating extensive brain damage [30]. Proton magnetic resonance spectroscopy (MRS) has shown decreased N-acetyl aspartate (NAA) levels and elevated lactate levels, suggesting mitochondrial dysfunction and hypoxia-related processes [25, 29]. These findings highlight the need for vigilant monitoring and precise dosing to prevent severe hypoxic events in patients on methadone therapy [31]. Additionally, methadone maintenance treatment is associated with significant weight gain and increased cardiovascular risk factors, necessitating further research to identify predictors and develop tailored interventions, including nutritional and lifestyle recommendations [32, 33]. Higher doses of methadone are linked to changes in the QTc interval and the prevalence of U waves, which are associated with cardiac arrhythmias and torsade de pointes, emphasizing the need for careful monitoring, especially in patients at risk of arrhythmia [34, 35]. The complex interplay of methadone's pharmacokinetics and pharmacodynamics, coupled with wide interindividual variability, underscores the importance of a cautious approach to its administration [1, 4, 36–44]. Moreover, while methadone aims to alleviate opioid dependency, it often perpetuates a cycle of dependency, highlighting the need for a critical reassessment of its role in addiction treatment [24]. This necessitates the implementation of more effective strategies that address the underlying causes of addiction while minimizing harm [45, 46]. Despite the recognition of methadone's adverse effects, there is a lack of comprehensive studies with substantial sample sizes addressing brain-related disorders associated with high doses of methadone. Most existing research is limited to case reports, underscoring the need for more extensive investigations to understand the full scope and mechanisms of methadone-induced neurological complications. Our study aimed to explore the potential presence of brain disorders via magnetic resonance imaging (MRI) in patients who misuse methadone or combine it with other drugs. Materials and Methods This cross-sectional comparative study was conducted at Kamali Hospital in Karaj, Iran, among three distinct groups: individuals using methadone obtained through non-medical sources, regular opium users, and matched controls. The study included only male participants of Middle Eastern descent. The Methadone Group consisted of individuals using methadone not obtained through a methadone maintenance treatment program, while the Opium Group included individuals with regular, self-reported opium use. The control group consisted of participants who did not use any substances. To ensure consistency and reliability of the data, all participants underwent a comprehensive screening process, which included standardized questionnaires such as the Addiction Severity Index (ASI) to assess psychiatric comorbidities and substance use history (Table 1 ). Trained interviewers conducted these screenings. Participants were recruited over six years through community outreach programs, which included distributing flyers in community centers, posting on social media platforms, and conducting direct outreach through community health workers trained to identify and approach potential participants. Recruitment was challenging due to the strict exclusion criteria and the difficulty in persuading individuals with substance use histories to participate in scientific research and undergo MRI scans. Monetary compensation was provided to participants to incentivize their involvement. Table 1 ASI (Addiction Severity Index) questionnaire Domain Questions Medical Status Do you currently have any medical problems not related to substance use? If yes, please describe. Employment and Support Are you currently employed or receiving any financial assistance? If yes, please describe. Drug Use During the past 30 days, how often have you used [specific drug(s)]? On average, how much do you use each time? Alcohol Use During the past 30 days, how often have you consumed alcohol? Psychiatric Status Have you ever been diagnosed with a mental health disorder (e.g., depression, anxiety)? If yes, please describe Inclusion criteria for the study required participants in the experimental groups (Methadone and Opium) to be male with a mean duration of substance use of 1 year and no history of brain structural disorders. The Control Group included male participants with no history of substance use and no brain structural disorders. Exclusion criteria were stringent and included a documented history of neurological or psychiatric disorders, contraindications to MRI, severe claustrophobia, significant medical conditions affecting brain structure or function, current substance withdrawal (including opioids), enrollment in a methadone maintenance program, recreational substance use, or if motion artifacts degraded MRI image quality. All participants underwent a thorough screening process, including interviews and standardized questionnaires, to ensure they met the inclusion and exclusion criteria. This careful selection process and extensive screening were crucial to focus the study on the effects of substance use on brain structure in otherwise healthy individuals. The study received approval from Shahid Beheshti University of Medical Sciences (Approval Code: IR.sbmu.retech.rec.1396.973). Prior to participation, all individuals provided written informed consent following a comprehensive explanation of the study's procedures, potential risks, and benefits. The study adhered to the ethical principles outlined in the Declaration of Helsinki. Confidentiality and anonymity were strictly upheld throughout the research. Data were anonymized and securely stored in a restricted-access database. Unique identifiers were assigned to participants to ensure anonymity. Informed consent was obtained in a private setting, allowing participants sufficient time to ask questions and address any concerns. All data were securely stored, and personal information was de-identified before analysis. MRI scans were conducted using a Scimedix 1.5T MRI scanner with a 32-channel head coil. A standard brain MRI protocol was employed, including T1-weighted, T2-weighted, FLAIR, and diffusion-weighted imaging (DWI) sequences, along with an ADC map, and Time-of-Flight (TOF) scans. No contrast media was used. The imaging procedure lasted approximately 15 minutes. MRI Protocol Details: T1-weighted Spin-Echo Images (T1WI): TR/TE = 300/12 msec, matrix size = 256 × 256, FOV = 24 × 24 cm², slice thickness = 5 mm, gap = 1 mm. T2-weighted Fast Spin-Echo (T2 WI): TR/TE = 3750/120 msec, matrix size = 256 × 256, FOV = 24 × 24 cm², slice thickness = 5 mm, gap = 1 mm. FLAIR: TR/TE = 6400/71 msec, matrix size = 256 × 256, FOV = 24 × 24 cm², slice thickness = 5 mm, gap = 1 mm. Diffusion-weighted Imaging (DWI): TR/TE = 7600/122 msec, matrix size = 112 × 96, FOV = 24 × 24 cm², slice thickness = 5 mm, gap = 1 mm. Time-of-Flight (TOF): TR/TE = 250/3.6 msec, matrix size = 256 × 200, FOV = 24 × 24 cm², slice thickness = 1 mm. A board-certified radiologist with expertise in MRI interpretation conducted a qualitative assessment by visually examining the MRI images for stroke. The radiologist was blinded to the participants' group status to prevent bias. MRI findings, detailed in Table 2 , involved assessing hyperintense signals on T2-weighted and FLAIR sequences, evaluating diffusion-weighted imaging (DWI) intensity and ADC values for acute ischemic changes, and utilizing Time-of-Flight (TOF) magnetic resonance angiography (MRA) to identify vascular abnormalities relevant to stroke, and T1-weighted images (T1 WI) for assessing anatomical structure and detecting hemorrhage. Table 2 MRI Imaging Assessments MRI Findings Description Assessed (Yes/No) Involvement T2 and FLAIR Hyperintensity Assessment of hyperintense signals on T2-weighted and FLAIR sequences DWI and ADC Intensity Evaluation of diffusion-weighted imaging (DWI) intensity and ADC values for detecting acute ischemic changes Brain Angiography with TOF Utilization of TOF MRA to identify vascular abnormalities relevant to stroke T1-WI Evaluation of T1-weighted images for assessing anatomical structures and detecting hemorrhage Statistical analysis was performed using the chi-square test to examine associations between categorical variables and the presence of neurological disorders identified through MRI imaging. Statistical analysis was performed using the Python programming language, employing libraries such as SciPy for chi-square tests and Pandas for data management. P-values less than 0.05 were considered statistically significant. Potential confounding variables, such as age, duration of substance use, and dose of substance used by individuals, were controlled for by matching participants across groups and using these variables as covariates in the statistical analysis. Additionally, logistic regression was employed using Python to examine the influence of these independent variables on the outcomes. Libraries such as `statsmodels` and `scikit-learn` were utilized to handle the statistical modeling. This approach helped to ensure that observed differences were more likely attributable to substance use rather than other factors, as the regression model could account for the potential influence of the confounding variables. By controlling for these variables, the analysis provided a clearer understanding of the relationship between substance use and the observed outcomes, reducing the likelihood that the results were skewed by extraneous factors. Results This study involved 96 male participants of Middle Eastern descent, categorized into patients and controls. The patient group comprised 38 individuals using Methadone or Opium, while the control group consisted of 58 non-substance users. Methadone users (n = 24) had a mean age of 32.3 years (range: 28–36) and used doses of 2–3 grams for 2–5 years. Opium users (n = 14) had a mean age of 45.7 years (range: 35–50) and used doses of 1–5 grams over 3–15 years. The control group, with a mean age of 33.8 years (range: 24–48), showed an even age distribution (Figs. 1 and 2 ). Logistic regression analysis revealed that dose, duration of use, and age did not significantly predict hypoxia (dose: coefficient − 0.09, p = 0.948; duration: coefficient − 0.13, p = 0.824; age: coefficient 0.20, p = 0.450), suggesting no substantial relationship between these variables and the likelihood of hypoxia (Table 3 ). Additionally, the scatter plot matrix shown in Fig. 3 illustrates the relationships between Age, Dose, Time of Use, and the presence of Hypoxia in methadone patients. Despite thorough regression analysis, no significant correlations were found among these variables (Fig. 3 ). Table 3 Logistic regression results show no significant predictors of hypoxia among Dose, Time of use, and Age variables (p > 0.05) Variable Coefficient p-value Intercept -7.28 0.389 Dose -0.09 0.948 Time of use -0.13 0.824 Age 0.2 0.45 Chi-square analysis indicated significant associations between substance use and hypoxia (χ² = 15.82, p = 0.0012). Methadone users showed a significant association with hypoxia (χ² = 11.87, p = 0.00057), whereas no significant association was found in Opium users (χ² = 0.77, p = 0.38) (Table 4 ). Specifically, 16.7% (5 out of 24) of Methadone users experienced hypoxia (Table 5 ), highlighting a notable correlation between Methadone use and increased risk of hypoxia compared to Opium users and non-substance users. Table 4 Chi-Square Analysis of Substance Use and Hypoxia Group Substance Chi-Square Value (χ²) p-value Total - 15.82 0.0012 Control - 3.19 0.074 Patient Methadone 11.87 0.00057 Patient Opium 0.77 0.38 Table 5 Table presents demographic details and hypoxia incidence rates among study participants categorized into patient groups receiving Methadone or Opium, and a control group. Group Subgroup Number of Participants Age Range (years) Mean Age (years) Hypoxia Incidence (%) Patient Methadone 24 28–36 32.3 16.7 Opium 14 35–50 45.7 - Control - 58 24–48 33.8 - MRI imaging findings in the Methadone group revealed varied ADC intensities, with high intensity in acute cases and low intensity in chronic cases. T2-weighted and DWI sequences consistently showed high signal intensities. FLAIR sequences consistently displayed high signal intensities. TOF sequences indicated angiogenesis patterns, and in chronic cases, reduced vascular flow was observed. Table 6 outlining imaging findings across five hypoxia cases. Table 6 MRI imaging findings in a group of methadone patients Patient Number Age Dose (gr) Duration (years) T2 DWI ADC FLAIR T1 TOF Involvement 1 32 2 4 High signal High signal Low signal High signal ISO Angiogenesis Parietal lobe 2 35 2 3 High signal High signal Low signal High signal ISO Angiogenesis Parietal lobe 3 33 3 3 High signal High signal Low signal High signal ISO Angiogenesis Parieto-occipital 4 32 2 3 High signal High signal High signal High signal Low Reduced flow Occipital 5 33 2 2 High signal High signal High signal High signal Low Reduced flow Parieto-occipital Discussion Methadone offers significant therapeutic benefits, but it also comes with considerable risks. These risks are particularly heightened when methadone is used alongside other drugs, as this can lead to dangerous interactions and a higher likelihood of overdose. Consequently, careful monitoring and management are essential to ensure patient safety. This balance of benefits and risks must be meticulously maintained to avoid adverse outcomes [15-21]. Our study aimed to explore the potential presence of brain disorders via magnetic resonance imaging (MRI) in patients who misuse methadone or combine it with other drugs. The main finding indicates a significant occurrence of hypoxia in the methadone group, which is absent in both the opium and control groups. This suggests a unique risk profile associated with methadone misuse, particularly in combination with alcohol. Notably, three out of the five hypoxia cases involved methadone and alcohol co-use, highlighting a potential interaction that exacerbates the risk of hypoxia. Furthermore, all five individuals with hypoxia lacked knowledge about the pharmacodynamics of methadone, suggesting that educational deficits may contribute to unsafe usage patterns. Logistic regression analysis did not reveal any significant predictors of hypoxia in terms of dose, duration of use, or age. The coefficients for dose, time of use, and age indicate that these variables do not substantially contribute to the risk of hypoxia in the studied population. This lack of a dose-response relationship suggests that even low doses and shorter durations of methadone use can pose significant risks. Therefore, it emphasizes the need for cautious prescribing and vigilant monitoring practices to mitigate potential adverse effects. The MRI scans were performed at various times post-hypoxia, which might explain the variability in apparent diffusion coefficient (ADC) signals observed, indicating both chronic and acute hypoxia among the patients [47]. This variability underscores the need for timely and consistent imaging protocols to accurately assess and monitor hypoxia in methadone users. The MRI findings in methadone users revealed distinct patterns associated with hypoxia, including high ADC intensities in acute cases and low in chronic cases [47], consistently high signal intensities on T2-weighted and diffusion-weighted imaging (DWI) sequences, and high signal intensities on fluid-attenuated inversion recovery (FLAIR) sequences [48, 49]. Time-of-flight (TOF) sequences indicated angiogenesis patterns and reduced flow in chronic cases (Figures 4 and 5) [50, 51]. These imaging characteristics can provide valuable insights into the temporal progression of hypoxic brain injury in methadone users and highlight the utility of MRI in detecting and characterizing such injuries [52]. In comparison with previous research, our study is novel in incorporating an opium group alongside a control group, thus providing a more comprehensive analysis. Despite the opium group using higher doses and for longer durations than the methadone group, no hypoxia cases were observed among them. This is consistent with existing literature, which primarily documents encephalopathy in methadone users but does not provide extensive imaging evidence [25-29]. The limited existing studies are mostly case reports [15, 25, 28, 30, 53-59], lacking the breadth of our comparative analysis across different substance use groups. While some prior research suggests methadone-related hypoxia [31, 60-63], They did not employ MRI, a method typically used for diagnosing brain hypoxia, thereby limiting their diagnostic precision. Our findings have significant implications for clinical practice and public health policy. Routine MRI monitoring should be considered for methadone patients presenting with hypoxia symptoms to ensure early detection and intervention. Additionally, there is an urgent need for stricter regulations to prevent the sale of non-prescribed methadone, as its affordability and accessibility contribute to misuse [64]. Public health initiatives should also focus on educating individuals about the distinct and cumulative effects of methadone [9], particularly its differences from opium, to mitigate misuse risks. An important aspect of our study is the identification of educational deficits among the individuals who experienced hypoxia, pointing to a critical gap in understanding that may contribute to unsafe usage patterns. Providing comprehensive education on the risks associated with methadone misuse, especially in combination with other substances like alcohol, could potentially mitigate some of the adverse outcomes observed in this study. This study is not without limitations. The small sample size, stemming from the challenges in recruiting such patients, underscores the need for governmental collaboration in future research. Moreover, self-reported data on drug use are inherently unreliable, and motion artifacts in MRI scans often necessitate the exclusion of non-cooperative subjects, reducing the usable sample size further. Financial incentives required for participant cooperation also highlight the need for adequate funding in addiction research. Additionally, the inclusion of overweight individuals may confound the effects of methadone on respiratory depression and cardiac arrest [32]. Future research should address these limitations by expanding the sample size and incorporating blood tests to verify drug use. Excluding overweight participants could provide clearer insights into methadone’s specific effects. Advances in MRI techniques, including spectroscopy and propeller imaging, could be leveraged to study metabolites and reduce motion artifacts. Additionally, perfusion imaging could be used for diagnosing the penumbra area. Further studies should also explore the effects of polydrug use with methadone compared to high-dose methadone use alone, to better understand the complexities of substance interactions. In conclusion, our study highlights a significant risk of hypoxia in methadone users, particularly when combined with alcohol, and underscores the importance of MRI in diagnosing and monitoring this condition. The findings underscore the need for enhanced education and monitoring to prevent hypoxic brain injuries in this vulnerable population. Future research and policy initiatives should aim to mitigate these risks through better regulation, education, and advanced diagnostic techniques. Declarations Author Contribution Ali Shamooshaki: First author, responsible for analyzing data, writing the main sections of the article, and collecting the data.Fariborz Faeghi: Corresponding author, provided guidance throughout the study and manuscript preparation.Hossein Jomleh: Assisted in data analysis, contributed to writing the manuscript, and provided ideas for the study.Amin Aziziyan: Radiologist, reported the MRI scans, and provided guidance in writing the manuscript.Dayan Amanian: Radiologist, responsible for reporting the MRI scans.Reza Koohi: Assisted in collecting data for the study. Data Availability The data supporting the findings of this study are currently saved on the author’s computer. Due to concerns related to the privacy of study participants, the data cannot be shared openly. However, data will be made available upon reasonable request to qualified researchers. 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Cerase A, Leonini S, Bellini M, Chianese G, Venturi C. Methadone-induced toxic leukoencephalopathy: diagnosis and follow-up by magnetic resonance imaging including diffusion-weighted imaging and apparent diffusion coefficient maps. J Neuroimaging. 2011;21(3):283-6. Aghabiklooei A, Edalatparvar M, Zamani N, Mostafazadeh B. Prognostic factors in acute methadone toxicity: a 5-year study. J Toxicol. 2014;2014:341826. Zanin A, Masiero S, Severino MS, Calderone M, Da Dalt L, Laverda AM. A delayed methadone encephalopathy: clinical and neuroradiological findings. J Child Neurol. 2010;25(6):748-51. Mills F, MacLennan SC, Devile CJ, Saunders DE. Severe cerebellitis following methadone poisoning. Pediatr Radiol. 2008;38(2):227-9. Anselmo M, Campos Rainho A, do Carmo Vale M, Estrada J, Valente R, Correia M, et al. Methadone intoxication in a child: toxic encephalopathy? J Child Neurol. 2006;21(7):618-20. Madjova C, Chokanov S, Milkov M. CORRELATION BETWEEN SLEEP APNEA AND METHADONE THERAPY. Journal of IMAB - Annual Proceeding (Scientific Papers). 2021. Webster LR, editor Methadone Side Effects: Constipation, Respiratory Depression, Sedation, Sleep-Disordered Breathing, and the Endocrine System2013. Correa D, Farney RJ, Chung F, Prasad A, Lam D, Wong J. Chronic opioid use and central sleep apnea: a review of the prevalence, mechanisms, and perioperative considerations. Anesth Analg. 2015;120(6):1273-85. Charpentier A, Bisac S, Poirot I, Vignau J, Cottencin O. Sleep quality and apnea in stable methadone maintenance treatment. Subst Use Misuse. 2010;45(9):1431-4. De Lima L, Pastrana T, Radbruch L, Wenk R. Cross-sectional pilot study to monitor the availability, dispensed prices, and affordability of opioids around the globe. J Pain Symptom Manage. 2014;48(4):649-59.e1. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 06 Dec, 2024 Read the published version in Acta Neurologica Belgica → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4888396","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":350061136,"identity":"6ee2035e-72b6-4471-9bf2-c743c4cae8cf","order_by":0,"name":"Ali Shamooshaki","email":"","orcid":"","institution":"Shahid Beheshti University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Ali","middleName":"","lastName":"Shamooshaki","suffix":""},{"id":350061137,"identity":"c5c2538f-66c0-4dad-88d6-1f8a1e96d09e","order_by":1,"name":"Fariborz Faeghi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1ElEQVRIiWNgGAWjYBAC9gbGB0DqAA8/Aw9UiJmAFp4DzAZgLZINpGphMDjAQ0ApXAsDM+OHD7/uyBifP3t0Mw+DnTwDO+8DQlqYJWf2PeMxu5GXdpuHIdmwgZndAK8Wewb+A9K8PYeBWnjMgFqYExiY2Qg6jPn3X6AW4/4zIC31RGlhk2b4cZjHgCEHpOUwcVosexsO80gA/XJzjsFxwzZiHHbjx5/D9vz9Z4/deFNRLc/Pfwy/Fgb5BwwMjG0wHjCsCNgBA3+IUzYKRsEoGAUjFAAAET87Bwrx1dcAAAAASUVORK5CYII=","orcid":"","institution":"Shahid Beheshti University of Medical Sciences","correspondingAuthor":true,"prefix":"","firstName":"Fariborz","middleName":"","lastName":"Faeghi","suffix":""},{"id":350061138,"identity":"0301d62a-84aa-454b-a13b-b07cb1c4d8e2","order_by":2,"name":"Hossein Jomleh","email":"","orcid":"","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Hossein","middleName":"","lastName":"Jomleh","suffix":""},{"id":350061139,"identity":"2e0a701c-de05-46dd-9b8e-e1566a4269d0","order_by":3,"name":"Amin Azizian","email":"","orcid":"","institution":"Iran University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Amin","middleName":"","lastName":"Azizian","suffix":""},{"id":350061143,"identity":"5dcedd8e-f31d-47f8-ba8b-cfd3f414591c","order_by":4,"name":"Dayan Amanian","email":"","orcid":"","institution":"Golestan University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Dayan","middleName":"","lastName":"Amanian","suffix":""},{"id":350061145,"identity":"caaafdea-7ba1-4e14-906e-06b7e134ed49","order_by":5,"name":"Reza Kouhi","email":"","orcid":"","institution":"Shahid Beheshti University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Reza","middleName":"","lastName":"Kouhi","suffix":""}],"badges":[],"createdAt":"2024-08-09 16:45:44","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4888396/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4888396/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s13760-024-02678-8","type":"published","date":"2024-12-06T15:57:52+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":65792925,"identity":"b5b3f991-f225-4ed5-bd38-623ee25d46ef","added_by":"auto","created_at":"2024-10-02 18:13:05","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":21301,"visible":true,"origin":"","legend":"\u003cp\u003ekey attributes of the study population\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4888396/v1/8d7bbdbb8f8cbcfe859ed6e8.png"},{"id":65792923,"identity":"67a113bf-5cbc-4c5d-80b4-8b9b437b9eff","added_by":"auto","created_at":"2024-10-02 18:13:05","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":20419,"visible":true,"origin":"","legend":"\u003cp\u003eMean Age and Standard Deviation of Participants\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4888396/v1/b945549bbf91f0049891417f.png"},{"id":65792924,"identity":"d7c0157f-3de3-42d2-afe2-c632e0813ca5","added_by":"auto","created_at":"2024-10-02 18:13:05","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":48588,"visible":true,"origin":"","legend":"\u003cp\u003eThis scatter plot matrix illustrates the relationships between Age, Dose, Time of Use, and the presence of Hypoxia in methadone patients. the regression analysis indicates no significant correlations among them.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4888396/v1/78a601ef2ba983ae634c739c.png"},{"id":65792926,"identity":"8dce2f84-0e12-4091-b094-72331beba07d","added_by":"auto","created_at":"2024-10-02 18:13:05","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":84791,"visible":true,"origin":"","legend":"\u003cp\u003eMRI of hypoxic brain injury post-methadone overdose showing high FLAIR and T2 signals, low T1 signal, high DWI signal, low ADC signal, and angiogenesis on TOF. These indicate edema, tissue damage, restricted diffusion, and vascular response.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4888396/v1/e6328352ebd21ea8b2eb110c.png"},{"id":65792927,"identity":"cf72516a-ef30-45db-9cb2-86e59f29fd25","added_by":"auto","created_at":"2024-10-02 18:13:05","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":69484,"visible":true,"origin":"","legend":"\u003cp\u003eMRI of hypoxic brain injury after methadone overdose displaying high signals on FLAIR, T2, and DWI, low signals on ADC, and reduced TOF flow, indicating edema, tissue damage, restricted diffusion, and decreased blood flow.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-4888396/v1/0bfdcf1e46b0c5de07ae2a68.png"},{"id":70964810,"identity":"cd63d93c-a8d6-4dee-90b2-998d794b6169","added_by":"auto","created_at":"2024-12-09 16:16:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":739077,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4888396/v1/eaebac5c-fe7a-48df-8028-e0d9e1c315e8.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Hypoxic Brain Damage in Methadone Misuse: Insights from MRI Imaging and Comparative Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMethadone, a synthetic opioid introduced in the 1960s, plays a critical role in the management of opioid withdrawal symptoms and chronic pain [1, 2]. As a racemic mixture, the (R)-methadone enantiomer is the active component responsible for its therapeutic effects [3]. Despite its common oral administration, methadone can also be delivered via rectal, sublingual, and intravenous routes, enhancing its versatility in clinical settings [4, 5].\u003c/p\u003e \u003cp\u003eMethadone's analgesic properties arise from its multi-faceted mechanisms of action, which include opioid receptor activation, NMDA receptor antagonism, and inhibition of serotonin and norepinephrine reuptake [6, 7]. These mechanisms not only underpin its efficacy as a potent analgesic but also distinguish methadone from other long-acting opioids through its unique pharmacological attributes, such as fat solubility and high plasma protein binding affinity [8]. Consequently, methadone exhibits a prolonged duration of action, albeit with a variable terminal half-life ranging from 15 to 50 hours, necessitating careful dosage titration and frequent monitoring to prevent drug accumulation and adverse effects [9].\u003c/p\u003e \u003cp\u003eBeyond its primary use in opioid withdrawal management, methadone is integral to Methadone Maintenance Treatment (MMT) programs, significantly reducing injection drug use and transmission rates of HIV and hepatitis C virus [10, 11]. Its effectiveness extends to managing various chronic pain conditions, including cancer and neuropathic pain, as well as acute post-operative pain, due to its combined analgesic and antihyperalgesic effects [12\u0026ndash;14].\u003c/p\u003e \u003cp\u003eMethadone's therapeutic benefits are counterbalanced by substantial risks, especially in the context of poly-drug use, which increases the potential for adverse interactions and overdose [15\u0026ndash;21]. Methadone overdose significantly contributes to opioid-related mortality, often leading to severe outcomes such as respiratory depression and cardiac arrest [22\u0026ndash;24]. Imaging studies have revealed methadone-induced neurotoxicity, showing specific brain abnormalities [25\u0026ndash;29]. High doses of methadone can cause severe hypoxia, raising the risk of stroke and delay post-hypoxic encephalopathy. MRI scans of affected patients often display diffuse abnormal T2 signals in the corona radiata, centrum semiovale, and subcortical white matter, indicating extensive brain damage [30]. Proton magnetic resonance spectroscopy (MRS) has shown decreased N-acetyl aspartate (NAA) levels and elevated lactate levels, suggesting mitochondrial dysfunction and hypoxia-related processes [25, 29]. These findings highlight the need for vigilant monitoring and precise dosing to prevent severe hypoxic events in patients on methadone therapy [31]. Additionally, methadone maintenance treatment is associated with significant weight gain and increased cardiovascular risk factors, necessitating further research to identify predictors and develop tailored interventions, including nutritional and lifestyle recommendations [32, 33]. Higher doses of methadone are linked to changes in the QTc interval and the prevalence of U waves, which are associated with cardiac arrhythmias and torsade de pointes, emphasizing the need for careful monitoring, especially in patients at risk of arrhythmia [34, 35].\u003c/p\u003e \u003cp\u003eThe complex interplay of methadone's pharmacokinetics and pharmacodynamics, coupled with wide interindividual variability, underscores the importance of a cautious approach to its administration [1, 4, 36\u0026ndash;44]. Moreover, while methadone aims to alleviate opioid dependency, it often perpetuates a cycle of dependency, highlighting the need for a critical reassessment of its role in addiction treatment [24]. This necessitates the implementation of more effective strategies that address the underlying causes of addiction while minimizing harm [45, 46].\u003c/p\u003e \u003cp\u003eDespite the recognition of methadone's adverse effects, there is a lack of comprehensive studies with substantial sample sizes addressing brain-related disorders associated with high doses of methadone. Most existing research is limited to case reports, underscoring the need for more extensive investigations to understand the full scope and mechanisms of methadone-induced neurological complications.\u003c/p\u003e \u003cp\u003eOur study aimed to explore the potential presence of brain disorders via magnetic resonance imaging (MRI) in patients who misuse methadone or combine it with other drugs.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eThis cross-sectional comparative study was conducted at Kamali Hospital in Karaj, Iran, among three distinct groups: individuals using methadone obtained through non-medical sources, regular opium users, and matched controls. The study included only male participants of Middle Eastern descent. The Methadone Group consisted of individuals using methadone not obtained through a methadone maintenance treatment program, while the Opium Group included individuals with regular, self-reported opium use. The control group consisted of participants who did not use any substances. To ensure consistency and reliability of the data, all participants underwent a comprehensive screening process, which included standardized questionnaires such as the Addiction Severity Index (ASI) to assess psychiatric comorbidities and substance use history (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Trained interviewers conducted these screenings. Participants were recruited over six years through community outreach programs, which included distributing flyers in community centers, posting on social media platforms, and conducting direct outreach through community health workers trained to identify and approach potential participants. Recruitment was challenging due to the strict exclusion criteria and the difficulty in persuading individuals with substance use histories to participate in scientific research and undergo MRI scans. Monetary compensation was provided to participants to incentivize their involvement.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eASI (Addiction Severity Index) questionnaire\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e Domain\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQuestions\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedical Status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDo you currently have any medical problems not related to substance use? If yes, please describe.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployment and Support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAre you currently employed or receiving any financial assistance? If yes, please describe.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrug Use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDuring the past 30 days, how often have you used [specific drug(s)]? On average, how much do you use each time?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcohol Use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDuring the past 30 days, how often have you consumed alcohol?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePsychiatric Status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHave you ever been diagnosed with a mental health disorder (e.g., depression, anxiety)? If yes, please describe\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eInclusion criteria for the study required participants in the experimental groups (Methadone and Opium) to be male with a mean duration of substance use of 1 year and no history of brain structural disorders. The Control Group included male participants with no history of substance use and no brain structural disorders. Exclusion criteria were stringent and included a documented history of neurological or psychiatric disorders, contraindications to MRI, severe claustrophobia, significant medical conditions affecting brain structure or function, current substance withdrawal (including opioids), enrollment in a methadone maintenance program, recreational substance use, or if motion artifacts degraded MRI image quality. All participants underwent a thorough screening process, including interviews and standardized questionnaires, to ensure they met the inclusion and exclusion criteria. This careful selection process and extensive screening were crucial to focus the study on the effects of substance use on brain structure in otherwise healthy individuals.\u003c/p\u003e \u003cp\u003e The study received approval from Shahid Beheshti University of Medical Sciences (Approval Code: IR.sbmu.retech.rec.1396.973). Prior to participation, all individuals provided written informed consent following a comprehensive explanation of the study's procedures, potential risks, and benefits. The study adhered to the ethical principles outlined in the Declaration of Helsinki. Confidentiality and anonymity were strictly upheld throughout the research. Data were anonymized and securely stored in a restricted-access database. Unique identifiers were assigned to participants to ensure anonymity. Informed consent was obtained in a private setting, allowing participants sufficient time to ask questions and address any concerns. All data were securely stored, and personal information was de-identified before analysis.\u003c/p\u003e \u003cp\u003eMRI scans were conducted using a Scimedix 1.5T MRI scanner with a 32-channel head coil. A standard brain MRI protocol was employed, including T1-weighted, T2-weighted, FLAIR, and diffusion-weighted imaging (DWI) sequences, along with an ADC map, and Time-of-Flight (TOF) scans. No contrast media was used. The imaging procedure lasted approximately 15 minutes.\u003c/p\u003e \u003cp\u003eMRI Protocol Details:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eT1-weighted Spin-Echo Images (T1WI): TR/TE\u0026thinsp;=\u0026thinsp;300/12 msec, matrix size\u0026thinsp;=\u0026thinsp;256 \u0026times; 256, FOV\u0026thinsp;=\u0026thinsp;24 \u0026times; 24 cm\u0026sup2;, slice thickness\u0026thinsp;=\u0026thinsp;5 mm, gap\u0026thinsp;=\u0026thinsp;1 mm.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eT2-weighted Fast Spin-Echo (T2 WI): TR/TE\u0026thinsp;=\u0026thinsp;3750/120 msec, matrix size\u0026thinsp;=\u0026thinsp;256 \u0026times; 256, FOV\u0026thinsp;=\u0026thinsp;24 \u0026times; 24 cm\u0026sup2;, slice thickness\u0026thinsp;=\u0026thinsp;5 mm, gap\u0026thinsp;=\u0026thinsp;1 mm.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eFLAIR: TR/TE\u0026thinsp;=\u0026thinsp;6400/71 msec, matrix size\u0026thinsp;=\u0026thinsp;256 \u0026times; 256, FOV\u0026thinsp;=\u0026thinsp;24 \u0026times; 24 cm\u0026sup2;, slice thickness\u0026thinsp;=\u0026thinsp;5 mm, gap\u0026thinsp;=\u0026thinsp;1 mm.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eDiffusion-weighted Imaging (DWI): TR/TE\u0026thinsp;=\u0026thinsp;7600/122 msec, matrix size\u0026thinsp;=\u0026thinsp;112 \u0026times; 96, FOV\u0026thinsp;=\u0026thinsp;24 \u0026times; 24 cm\u0026sup2;, slice thickness\u0026thinsp;=\u0026thinsp;5 mm, gap\u0026thinsp;=\u0026thinsp;1 mm.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eTime-of-Flight (TOF): TR/TE\u0026thinsp;=\u0026thinsp;250/3.6 msec, matrix size\u0026thinsp;=\u0026thinsp;256 \u0026times; 200, FOV\u0026thinsp;=\u0026thinsp;24 \u0026times; 24 cm\u0026sup2;, slice thickness\u0026thinsp;=\u0026thinsp;1 mm.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eA board-certified radiologist with expertise in MRI interpretation conducted a qualitative assessment by visually examining the MRI images for stroke. The radiologist was blinded to the participants' group status to prevent bias. MRI findings, detailed in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, involved assessing hyperintense signals on T2-weighted and FLAIR sequences, evaluating diffusion-weighted imaging (DWI) intensity and ADC values for acute ischemic changes, and utilizing Time-of-Flight (TOF) magnetic resonance angiography (MRA) to identify vascular abnormalities relevant to stroke, and T1-weighted images (T1 WI) for assessing anatomical structure and detecting hemorrhage.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMRI Imaging Assessments\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMRI Findings\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDescription\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAssessed (Yes/No)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInvolvement\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT2 and FLAIR Hyperintensity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAssessment of hyperintense signals on T2-weighted and FLAIR sequences\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDWI and ADC Intensity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEvaluation of diffusion-weighted imaging (DWI) intensity and ADC values for detecting acute ischemic changes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBrain Angiography with TOF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUtilization of TOF MRA to identify vascular abnormalities relevant to stroke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT1-WI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEvaluation of T1-weighted images for assessing anatomical structures and detecting hemorrhage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eStatistical analysis was performed using the chi-square test to examine associations between categorical variables and the presence of neurological disorders identified through MRI imaging. Statistical analysis was performed using the Python programming language, employing libraries such as SciPy for chi-square tests and Pandas for data management. P-values less than 0.05 were considered statistically significant.\u003c/p\u003e \u003cp\u003ePotential confounding variables, such as age, duration of substance use, and dose of substance used by individuals, were controlled for by matching participants across groups and using these variables as covariates in the statistical analysis. Additionally, logistic regression was employed using Python to examine the influence of these independent variables on the outcomes. Libraries such as `statsmodels` and `scikit-learn` were utilized to handle the statistical modeling. This approach helped to ensure that observed differences were more likely attributable to substance use rather than other factors, as the regression model could account for the potential influence of the confounding variables. By controlling for these variables, the analysis provided a clearer understanding of the relationship between substance use and the observed outcomes, reducing the likelihood that the results were skewed by extraneous factors.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThis study involved 96 male participants of Middle Eastern descent, categorized into patients and controls. The patient group comprised 38 individuals using Methadone or Opium, while the control group consisted of 58 non-substance users. Methadone users (n\u0026thinsp;=\u0026thinsp;24) had a mean age of 32.3 years (range: 28\u0026ndash;36) and used doses of 2\u0026ndash;3 grams for 2\u0026ndash;5 years. Opium users (n\u0026thinsp;=\u0026thinsp;14) had a mean age of 45.7 years (range: 35\u0026ndash;50) and used doses of 1\u0026ndash;5 grams over 3\u0026ndash;15 years. The control group, with a mean age of 33.8 years (range: 24\u0026ndash;48), showed an even age distribution (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eLogistic regression analysis revealed that dose, duration of use, and age did not significantly predict hypoxia (dose: coefficient \u0026minus;\u0026thinsp;0.09, p\u0026thinsp;=\u0026thinsp;0.948; duration: coefficient \u0026minus;\u0026thinsp;0.13, p\u0026thinsp;=\u0026thinsp;0.824; age: coefficient 0.20, p\u0026thinsp;=\u0026thinsp;0.450), suggesting no substantial relationship between these variables and the likelihood of hypoxia (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Additionally, the scatter plot matrix shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e illustrates the relationships between Age, Dose, Time of Use, and the presence of Hypoxia in methadone patients. Despite thorough regression analysis, no significant correlations were found among these variables (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLogistic regression results show no significant predictors of hypoxia among Dose, Time of use, and Age variables (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCoefficient\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-7.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.389\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.948\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime of use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.824\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eChi-square analysis indicated significant associations between substance use and hypoxia (χ\u0026sup2; = 15.82, p\u0026thinsp;=\u0026thinsp;0.0012). Methadone users showed a significant association with hypoxia (χ\u0026sup2; = 11.87, p\u0026thinsp;=\u0026thinsp;0.00057), whereas no significant association was found in Opium users (χ\u0026sup2; = 0.77, p\u0026thinsp;=\u0026thinsp;0.38) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Specifically, 16.7% (5 out of 24) of Methadone users experienced hypoxia (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), highlighting a notable correlation between Methadone use and increased risk of hypoxia compared to Opium users and non-substance users.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eChi-Square Analysis of Substance Use and Hypoxia\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSubstance\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChi-Square Value (χ\u0026sup2;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e15.82\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.0012\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMethadone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.00057\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOpium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTable presents demographic details and hypoxia incidence rates among study participants categorized into patient groups receiving Methadone or Opium, and a control group.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSubgroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber of Participants\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAge Range (years)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean Age (years)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHypoxia Incidence (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMethadone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28\u0026ndash;36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e32.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOpium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35\u0026ndash;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e45.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24\u0026ndash;48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e33.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMRI imaging findings in the Methadone group revealed varied ADC intensities, with high intensity in acute cases and low intensity in chronic cases. T2-weighted and DWI sequences consistently showed high signal intensities. FLAIR sequences consistently displayed high signal intensities. TOF sequences indicated angiogenesis patterns, and in chronic cases, reduced vascular flow was observed. Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e outlining imaging findings across five hypoxia cases.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMRI imaging findings in a group of methadone patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient Number\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDose (gr)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDuration (years)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eT2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDWI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eADC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eFLAIR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eT1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eTOF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eInvolvement\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHigh signal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHigh signal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLow signal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eHigh signal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eISO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eAngiogenesis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eParietal lobe\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHigh signal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHigh signal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLow signal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eHigh signal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eISO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eAngiogenesis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eParietal lobe\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHigh signal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHigh signal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLow signal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eHigh signal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eISO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eAngiogenesis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eParieto-occipital\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHigh signal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHigh signal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eHigh signal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eHigh signal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eReduced flow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eOccipital\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHigh signal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHigh signal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eHigh signal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eHigh signal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eReduced flow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eParieto-occipital\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eMethadone offers significant therapeutic benefits, but it also comes with considerable risks. These risks are particularly heightened when methadone is used alongside other drugs, as this can lead to dangerous interactions and a higher likelihood of overdose. Consequently, careful monitoring and management are essential to ensure patient safety. This balance of benefits and risks must be meticulously maintained to avoid adverse outcomes \u0026nbsp;[15-21].\u003c/p\u003e\n\u003cp\u003eOur study aimed to explore the potential presence of brain disorders via magnetic resonance imaging (MRI) in patients who misuse methadone or combine it with other drugs. The main finding indicates a significant occurrence of hypoxia in the methadone group, which is absent in both the opium and control groups. This suggests a unique risk profile associated with methadone misuse, particularly in combination with alcohol. Notably, three out of the five hypoxia cases involved methadone and alcohol co-use, highlighting a potential interaction that exacerbates the risk of hypoxia. Furthermore, all five individuals with hypoxia lacked knowledge about the pharmacodynamics of methadone, suggesting that educational deficits may contribute to unsafe usage patterns. Logistic regression analysis did not reveal any significant predictors of hypoxia in terms of dose, duration of use, or age. The coefficients for dose, time of use, and age indicate that these variables do not substantially contribute to the risk of hypoxia in the studied population. This lack of a dose-response relationship suggests that even low doses and shorter durations of methadone use can pose significant risks. Therefore, it emphasizes the need for cautious prescribing and vigilant monitoring practices to mitigate potential adverse effects.\u003c/p\u003e\n\u003cp\u003eThe MRI scans were performed at various times post-hypoxia, which might explain the variability in apparent diffusion coefficient (ADC) signals observed, indicating both chronic and acute hypoxia among the patients [47]. This variability underscores the need for timely and consistent imaging protocols to accurately assess and monitor hypoxia in methadone users. The MRI findings in methadone users revealed distinct patterns associated with hypoxia, including high ADC intensities in acute cases and low in chronic cases [47], consistently high signal intensities on T2-weighted and diffusion-weighted imaging (DWI) sequences, and high signal intensities on fluid-attenuated inversion recovery (FLAIR) sequences [48, 49]. Time-of-flight (TOF) sequences indicated angiogenesis patterns and reduced flow in chronic cases (Figures 4 and 5) \u0026nbsp;[50, 51]. These imaging characteristics can provide valuable insights into the temporal progression of hypoxic brain injury in methadone users and highlight the utility of MRI in detecting and characterizing such injuries [52].\u003c/p\u003e\n\u003cp\u003eIn comparison with previous research, our study is novel in incorporating an opium group alongside a control group, thus providing a more comprehensive analysis. Despite the opium group using higher doses and for longer durations than the methadone group, no hypoxia cases were observed among them. This is consistent with existing literature, which primarily documents encephalopathy in methadone users but does not provide extensive imaging evidence \u0026nbsp;[25-29]. The limited existing studies are mostly case reports\u0026nbsp;[15, 25, 28, 30, 53-59], lacking the breadth of our comparative analysis across different substance use groups. While some prior research suggests methadone-related hypoxia\u0026nbsp;[31, 60-63], They did not employ MRI, a method typically used for diagnosing brain hypoxia, thereby limiting their diagnostic precision.\u003c/p\u003e\n\u003cp\u003eOur findings have significant implications for clinical practice and public health policy. Routine MRI monitoring should be considered for methadone patients presenting with hypoxia symptoms to ensure early detection and intervention. Additionally, there is an urgent need for stricter regulations to prevent the sale of non-prescribed methadone, as its affordability and accessibility contribute to misuse\u0026nbsp;[64]. Public health initiatives should also focus on educating individuals about the distinct and cumulative effects of methadone\u0026nbsp;[9], particularly its differences from opium, to mitigate misuse risks. An important aspect of our study is the identification of educational deficits among the individuals who experienced hypoxia, pointing to a critical gap in understanding that may contribute to unsafe usage patterns. Providing comprehensive education on the risks associated with methadone misuse, especially in combination with other substances like alcohol, could potentially mitigate some of the adverse outcomes observed in this study.\u003c/p\u003e\n\u003cp\u003eThis study is not without limitations. The small sample size, stemming from the challenges in recruiting such patients, underscores the need for governmental collaboration in future research. Moreover, self-reported data on drug use are inherently unreliable, and motion artifacts in MRI scans often necessitate the exclusion of non-cooperative subjects, reducing the usable sample size further. Financial incentives required for participant cooperation also highlight the need for adequate funding in addiction research. Additionally, the inclusion of overweight individuals may confound the effects of methadone on respiratory depression and cardiac arrest\u0026nbsp;[32].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFuture research should address these limitations by expanding the sample size and incorporating blood tests to verify drug use. Excluding overweight participants could provide clearer insights into methadone\u0026rsquo;s specific effects. Advances in MRI techniques, including spectroscopy and propeller imaging, could be leveraged to study metabolites and reduce motion artifacts. Additionally, perfusion imaging could be used for diagnosing the penumbra area. Further studies should also explore the effects of polydrug use with methadone compared to high-dose methadone use alone, to better understand the complexities of substance interactions.\u003c/p\u003e\n\u003cp\u003eIn conclusion, our study highlights a significant risk of hypoxia in methadone users, particularly when combined with alcohol, and underscores the importance of MRI in diagnosing and monitoring this condition. The findings underscore the need for enhanced education and monitoring to prevent hypoxic brain injuries in this vulnerable population. Future research and policy initiatives should aim to mitigate these risks through better regulation, education, and advanced diagnostic techniques.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAli Shamooshaki: First author, responsible for analyzing data, writing the main sections of the article, and collecting the data.Fariborz Faeghi: Corresponding author, provided guidance throughout the study and manuscript preparation.Hossein Jomleh: Assisted in data analysis, contributed to writing the manuscript, and provided ideas for the study.Amin Aziziyan: Radiologist, reported the MRI scans, and provided guidance in writing the manuscript.Dayan Amanian: Radiologist, responsible for reporting the MRI scans.Reza Koohi: Assisted in collecting data for the study.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data supporting the findings of this study are currently saved on the author\u0026rsquo;s computer. Due to concerns related to the privacy of study participants, the data cannot be shared openly. However, data will be made available upon reasonable request to qualified researchers. For access to the data or any further inquiries, please contact the corresponding author at [email protected]\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eDinis-Oliveira RJ. Metabolomics of methadone: clinical and forensic toxicological implications and variability of dose response. Drug Metab Rev. 2016;48(4):568-76.\u003c/li\u003e\n\u003cli\u003eDole VP, Nyswander M. A MEDICAL TREATMENT FOR DIACETYLMORPHINE (HEROIN) ADDICTION. A CLINICAL TRIAL WITH METHADONE HYDROCHLORIDE. Jama. 1965;193:646-50.\u003c/li\u003e\n\u003cli\u003eKristensen K, Christensen CB, Christrup LL. The mu1, mu2, delta, kappa opioid receptor binding profiles of methadone stereoisomers and morphine. Life Sci. 1995;56(2):Pl45-50.\u003c/li\u003e\n\u003cli\u003ePeng PW, Tumber PS, Gourlay D. 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J Pain Symptom Manage. 2014;48(4):649-59.e1.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Methadone, Hypoxia, MRI, Substance Use, Brain Disorders, Opioids, Public Health","lastPublishedDoi":"10.21203/rs.3.rs-4888396/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4888396/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eThis study aimed to investigate the potential presence of brain disorders, particularly hypoxia, via magnetic resonance imaging (MRI) in patients misusing methadone, with a comparison to regular opium users and a control group.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eConducted as a cross-sectional comparative study at Kamali Hospital in Karaj, Iran, the research included male participants comprising methadone users, opium users, and controls. Inclusion criteria were stringent, focusing on substance use duration and absence of brain structural disorders. MRI scans were performed using a 1.5T MRI scanner. Qualitative MRI assessments and chi-square tests analyzed associations between substance use and hypoxia, while logistic regression examined potential confounding variables.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eSignificant hypoxia was observed in the methadone group (16.7%, 5/24; p = 0.00057), with no cases in the opium or control groups. Logistic regression analysis showed no significant predictors of hypoxia regarding dose, duration of use, or age. MRI findings in methadone users with hypoxia included varied ADC intensities, high signal intensities on T2-weighted and diffusion-weighted imaging (DWI) sequences, and angiogenesis patterns on TOF sequences. The co-use of methadone and alcohol was noted in three of the five hypoxia cases.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eMethadone misuse, particularly with alcohol, poses a significant risk of hypoxia, detectable via MRI. This study underscores the need for routine MRI monitoring, stricter regulation of non-prescribed methadone, and enhanced public health education to mitigate misuse risks. Future research should expand sample sizes and incorporate advanced imaging techniques to further elucidate methadone's neurological impact.\u003c/p\u003e","manuscriptTitle":"Hypoxic Brain Damage in Methadone Misuse: Insights from MRI Imaging and Comparative Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-02 18:13:00","doi":"10.21203/rs.3.rs-4888396/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b7c5f699-24ce-4c31-8b9c-3e3c2e00b9a0","owner":[],"postedDate":"October 2nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-12-09T16:04:37+00:00","versionOfRecord":{"articleIdentity":"rs-4888396","link":"https://doi.org/10.1007/s13760-024-02678-8","journal":{"identity":"acta-neurologica-belgica","isVorOnly":false,"title":"Acta Neurologica Belgica"},"publishedOn":"2024-12-06 15:57:52","publishedOnDateReadable":"December 6th, 2024"},"versionCreatedAt":"2024-10-02 18:13:00","video":"","vorDoi":"10.1007/s13760-024-02678-8","vorDoiUrl":"https://doi.org/10.1007/s13760-024-02678-8","workflowStages":[]},"version":"v1","identity":"rs-4888396","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4888396","identity":"rs-4888396","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}