Literature DB >> 34194058

A comparative diffusion tensor imaging study of patients with and without treatment-resistant schizophrenia.

Anisha Aggarwal1, Sandeep Grover1, Chirag Ahuja2, Subho Chakrabarti1, Niranjan Khandelwal2, Ajit Avasthi1.   

Abstract

AIM: The aim was to study the brain connectivity using diffusion tensor imaging (DTI) among patients with treatment-resistant schizophrenia (TRS) and compare the same with a group of patients without TRS.
METHODS: Twenty-three patients with TRS and 15 patients without TRS underwent DTI using a 3T magnetic resonance imaging machine. DTI data were processed with the calculation of fractional anisotropy (FA) and apparent diffusion coefficient. Patients were also assessed on Brief Psychiatric Rating Scale, Positive and Negative Symptom Scale, Global Assessment of Functioning Scale, and Clinical Global Impression severity scale.
RESULTS: Patients with TRS and non-TRS differed significantly in the FA values in the region of right superior longitudinal fasciculus and right uncinate fasciculus, with more integrity of tracts in the non-TRS group. However, these differences disappeared when Bonferroni correction was used for multiple comparisons.
CONCLUSION: The present study suggests lack of significant difference in DTI findings between patients with TRS and non-TRS. Copyright:
© 2021 Indian Journal of Psychiatry.

Entities:  

Keywords:  Diffusion tensor imaging; schizophrenia; treatment resistance

Year:  2021        PMID: 34194058      PMCID: PMC8214122          DOI: 10.4103/psychiatry.IndianJPsychiatry_147_20

Source DB:  PubMed          Journal:  Indian J Psychiatry        ISSN: 0019-5545            Impact factor:   1.759


INTRODUCTION

Schizophrenia is arguably the most puzzling of psychiatric syndromes and one of the most debilitating psychiatric disorders. Despite the numerous studies aimed at understanding the disorder, its pathophysiology is largely unknown, with available treatments showing only partial efficacy in treating this disorder.[1] Available data suggest that about one-third of patients with schizophrenia do not respond to adequate treatment and are known to be suffering from treatment-resistant schizophrenia (TRS).[2] Patients with TRS are found to be highly symptomatic, require extensive periods of hospitalization, and are responsible for the high share of total cost toward treating schizophrenia.[34] As one-third of patients do not respond or show minimal response to available treatments, clinicians and investigators have attempted to predict nonresponse to treatment as early as possible, with an aim to possibly start clozapine before the treatment resistance evolves. One of the ways via which this prediction has been made in literature is through neuroimaging, which highlights the structural or functional changes in brain, possibly contributing to etiopathogenesis of treatment resistance in schizophrenia. Most of the available studies have focused on patients with chronic schizophrenia using techniques such as computed tomography (CT), magnetic resonance imaging (MRI), or functional MRI, with meager data on studying cases of TRS using diffusion tensor imaging (DTI).[45] Among the various neuroimaging techniques, DTI can be considered as more useful than CT and MRI in schizophrenia as it provides direct information about the white-matter neuroanatomical connectivity between different areas of the brain. These neuroanatomical connections could, therefore, be directly studied to understand the etiopathogenesis of schizophrenia and the etiopathogenesis of treatment resistance as well. A recent systematic review evaluated the neuroimaging findings of patients refractory to treatment and compared the available data with healthy controls and those responding to treatment.[4] In contrast to healthy controls, patients with TRS showed gray-matter reductions, which is consistent with findings seen in schizophrenia in general. When patients with treatment resistance/refractoriness were compared with those responding to treatment, the finding, which was most, replicated included a greater reduction in gray matter in resistant patients, predominantly in the frontal areas. However, none of the studies included in the review, compared patients with treatment resistance with treatment responders or healthy controls, was based on DTI.[4] Another systematic review published in 2015, also dealt with neuroimaging findings in patients with TRS.[5] CT-based studies showed prefrontal atrophy in patients with TRS.[5] MRI studies showed that compared to healthy controls, patients with TRS have more widespread reduction in cortical thickness in all the lobes of brain than patients with non-TRS, who had reduced cortical thickness only in frontal area of the brain.[5] As per this review, only one study was based on DTI, which compared patients with TRS and healthy controls. This study showed that compared to healthy controls, patients with TRS showed lower fractional anisotropy (FA) in multiple white-matter bundles. The areas involved included the genu, body, and splenium of the corpus callosum; inferior longitudinal fasciculus; superior longitudinal fasciculus (SLF); external capsule; uncinate fasciculus (UF); posterior limb of the internal capsule; the left anterior limb of internal capsule; fornix; cerebellar peduncles; and the corticospinal tract at the level of the brainstem. There was no voxel of increased FA in patients compared with controls.[5] A recently published study based on 1.5 T, voxel-based statistical analysis using the tract-based spatial statistics (TBSSv1.2) approach compared patients with treatment refractory schizophrenia and nonrefractory schizophrenia. This study showed no differences in FA of white-matter integrity between the two groups.[6] Considering the limited DTI data for patients with TRS, this study aimed to compare the brain connectivity using DTI among patients with and without TRS. It was hypothesized that individuals with TRS would not differ significantly in terms of brain circuitry involving the white matter compared to patients with non-TRS.

METHODS

This study was carried out in a tertiary care teaching hospital in North India. The ethics committee of the institute approved the study, and all the study participants were recruited after obtaining written informed consent. The study followed a cross-sectional design, in which all the patients were assessed only once. The study sample comprised of two groups, that is, Group I comprised of 23 patients with TRS, whereas Group II comprised of 15 patients who did not fulfill the criteria of TRS (non-TRS Group). Both the study groups were matched for age, gender, and total duration of illness. For this study, TRS was defined on the basis of: (i) insufficient response to two clinical trials of two different antipsychotics for at least 6 weeks' duration and no period of good functioning in the previous 2 years as determined by Global Assessment for Functional Scale (GAF)[7] score of <59, score of ≥4 on 2 of the 4 Brief Psychiatric Rating Scale (BPRS)[8] items of conceptual disorganization, suspiciousness, hallucinatory behavior, and unusual thought content, total BPRS-18 score ≥45, and Clinical Global Impression (CGI)[9] score of ≥4 at the time of assessment. To be included in the study, the participants were required to be aged 18–65 years and fulfill the diagnosis of schizophrenia as per the Diagnostic and Statistical Manual, fourth revision (DSM-IV) criteria, as confirmed by using the Mini International Neuropsychiatric Interview (MINI).[10] Additionally, to be considered for the non-TRS group, participants were required to have a period of good functioning in the previous 2 years and total BPRS-18 item scale score ≤35, CGI score of ≤3, score of <4 on 2 of the 4 BPRS items of conceptual disorganization, suspiciousness, hallucinatory behavior, and unusual thought content. Patients with the presence of organic brain syndrome, intellectual disability, comorbid drug dependence (other than tobacco dependence), history of any brain disorder (e.g., head injury, stroke, epilepsy, and Parkinson's disease), history of any illness which can cause white-matter damage (e.g., multiple sclerosis), comorbid severe medical conditions which could influence the neuroimaging findings (e.g., poorly controlled diabetes or symptomatic coronary artery disease), and those receiving clozapine for more than 1 week just prior to assessment or have received clozapine in the past were excluded from the study. Similarly, patients with contraindication for MRI (i.e., those with pacemakers, aneurysm clip, cochlear implants, claustrophobia) were also excluded from the study. All the patients were assessed on CGI Severity scale, BPRS, Positive and Negative Symptom Scale (PANSS),[11] and GAF scale. In addition, using a semi-structured interview, all the patients were evaluated for the presence or absence of auditory hallucinations in their lifetime. Premorbid personality prior to onset of illness was assessed by a semi-structured interview conducted with the patient and family members and a review of treatment records. Presence of personality disorder was defined as per the ICD-10 criteria. DTI data were acquired using 3T MRI machine (60 slices; TE = 100 ms; TR = 15000 ms; 30 directions; voxel size: 2.4 × 2.4 × 2.4; time of accuracy: 8.32 min; and slice thickness = 2.4 mm). The DTI images were processed and analyzed on the Siemens work station (software Numaris, version syngo MR B17). Motion and Eddy current-induced geometric distortions were corrected automatically. DTI data were processed by a qualified neuroradiologist, and the following steps were followed: (i) correction for motion and Eddy current-induced geometric distortions with rotation of the b-matrix to preserve the orientation information was ensured, (ii) diffusion tensor using a robust nonlinear regression method was estimated, and (iii) FA and apparent diffusion coefficient (ADC) were calculated. Subsequently, using the region of interest (ROI) approach, data were analyzed. The tensor data were loaded on the Neuro 3D platform to derive the FA and ADC maps. The FA/ADC maps were subsequently fused with the 3D T1 MPRAGE high-resolution images for better depiction and confirmation of the white-matter tracts. The tracts were identified as per the different cut sections, that is, sagittal, axial, or coronal depending on the best visibility of the tract. Thereafter, ROI-based analysis was performed on the desired tracts. Up to five ROIs were chosen to enclose tracts' cross-sections, and a mean of the ROIs was calculated to improve the specificity of the data. The radius of each ROI varied between 2 mm and 10 mm, depending on the thickness of the white-matter bundle. Following this, a set of 22 values each depicting the FA values and ADC values were obtained for further analysis. Data were analyzed by using SPSS Inc. Released 2007. SPSS for Windows, Version 16.0. (Chicago, SPSS Inc.). The mean and standard deviation with range were calculated for continuous variables and frequency and percentages were calculated for categorical variables. Comparisons were done by using Student's t-test, Mann–Whitney test, and Chi-square test. Bonferroni correction was applied to address multiple comparisons, and P = 0.002 (0.05/22) was considered statistically significant.

RESULTS

The demographic profile of the study sample is shown in Table 1. Compared to non-TRS group, patients with TRS had significantly longer duration of untreated psychosis, had significantly higher BPRS and PANSS total scores, had higher scores in all the domains of BPRS and PANSS, had significantly higher CGI severity score, had significantly higher impairment in the level of functioning as assessed by GAF, and had received significantly higher number of adequate antipsychotic trials [Table 1]. Most of the patients in the TRS group had continuous symptoms in the last 5 years.
Table 1

Comparison of demographic and clinical variables of treatment-resistant schizophrenia and nontreatment-resistant schizophrenia group

ParametersTRS group I (n=23)Non-TRS group II (n=15)T-test/χ2 (P)
Age in years35.26 (10.85)33.47 (8.74)t=0.54 (0.59)
Sex, male (%)11 (47.8)6 (40)χ2=0.22 (0.63)
Education in years, mean (SD); range11.65 (4.02)11.87 (2.90)t=−0.18 (0.86)
Marital status - currently single (%)13 (56.5)5 (33.3)χ2=1.96 (0.17)
Occupation - on paid employment (%)3 (13)3 (20)F.E=0.44
Type of schizophrenia - paranoid (%)19 (82.6)11 (73.3)FE=0.38
Age of onset (in years)24.65 (8.81)22.67 (6.31)t=0.75 (0.46)
Duration of untreated psychosis (in days)1262.35 (1682.43)234.60 (396.8)U=97.5 (0.02)*
Total duration of illness (in years)11.17 (8.12)11.93 (5.92)t=−0.31 (0.76)
Comorbid physical illness - presenta5 (21.74%)4 (26.67%)χ2b=0.0 (1)
Comorbid psychiatric illnessb9 (39.13%)2 (13.3%)χ2b=1.82 (0.18)
PANSS
 Positive subscale score27.13 (7.21)7.27 (0.59)t=10.59 (<0.001)***
 Negative subscale score28.22 (11.83)10.8 (2.57)t=5.59 (<0.001)***
 General Psychopathology subscale score49.70 (10.88)21.07 (2.60)t=9.96 (<0.001)***
 Total PANSS Score105.04 (23.07)39.13 (4.60)t=10.87 (<0.001)***
 Insight score as assessed from PANSS (G12)5.56 (1.37)2.27 (1.10)t=6.69 (<0.001)***
 Depression as per PANSS-D12.43 (5.95)6 (1.51)t=4.08 (<0.001) ***
 Depression as per PANSS-D - present (%)19 (82.60)5 (33.33)χ2=9.47 (0.002)**
BPRSc
 Depression/anxiety/affect9.70 (5.90)4.2 (0.56)t=3.58 (0.001)***
 Psychosis/thinking disorder18.04 (3.76)5.67 (0.90)t=12.46 (<0.001)***
 Negative symptoms/withdrawal/retardation9.17 (6.03)3.6 (1.40)t=3.50 (0.001)***
 Activation6.65 (3.01)3.87 (0.83)t=3.48 (<0.001)***
 Resistance10 (3.27)3.27 (0.46)t=5.84 (<0.001)***
Total BPRS score53.56 (10.68)20.6 (2.03)t=11.76 (<0.001)***
GAF
 GAF score21 (11.27)79.73 (7.36)t=−17.81 (<0.001)***
CGI
 CGI severity5.48 (0.59)1.13 (0.35)t=25.52 (<0.001)***
 Number of adequate trials received3.78 (1.594)1.73 (0.59)t=4.75 (<0.001)***
Course of illness in the last 5 years
 Continuous illness with no improvement in symptoms (%)14 (60.87)0χ2=14.46 (<0.001***)
 Continuous illness with no or minimal symptoms01 (6.7%)FE=0.39
 Episodic illness in lifetime with no improvement in symptoms in last 5 years (%)9 (39.13)0χ2b=0.02*

*P≤0.05; **P≤0.01; ***P≤0.001. AComorbid physical illnesses in TRS: diabetes mellitus (n=2), asthma (n=1), anemia (n=1), Acomorbid physical illnesses in non-TRS: diabetes mellitus (n=2), hypothyroidism (n=1), hypertension (n=1), Marfan syndrome (n=1); Bcomorbid psychiatric illnesses in TRS: moderate depressive episode (n=4), tobacco dependence, currently using (n=6); Bcomorbid psychiatric Illnesses in non-TRS: Moderate depressive episode (n=1), Tobacco dependence, currently using (n=1); cItems of Brief Psychiatric Rating Scale were categorized into various domains as per.[12] χ2 – Chi-square value; χ2b – Chi-square value with Yate’s correction; U – Mann-Whitney value; t – T test; SD – standard deviation; FE – Fisher’s exact value; PANSS – Positive and Negative Syndrome Scale, BPRS – Brief Psychiatric Rating Scale; GAF – Global Assessment of Functioning; CGI – Clinical Global Impression; TRS – Treatment-resistant schizophrenia

Comparison of demographic and clinical variables of treatment-resistant schizophrenia and nontreatment-resistant schizophrenia group *P≤0.05; **P≤0.01; ***P≤0.001. AComorbid physical illnesses in TRS: diabetes mellitus (n=2), asthma (n=1), anemia (n=1), Acomorbid physical illnesses in non-TRS: diabetes mellitus (n=2), hypothyroidism (n=1), hypertension (n=1), Marfan syndrome (n=1); Bcomorbid psychiatric illnesses in TRS: moderate depressive episode (n=4), tobacco dependence, currently using (n=6); Bcomorbid psychiatric Illnesses in non-TRS: Moderate depressive episode (n=1), Tobacco dependence, currently using (n=1); cItems of Brief Psychiatric Rating Scale were categorized into various domains as per.[12] χ2 – Chi-square value; χ2b – Chi-square value with Yate’s correction; U – Mann-Whitney value; t – T test; SD – standard deviation; FE – Fisher’s exact value; PANSS – Positive and Negative Syndrome Scale, BPRS – Brief Psychiatric Rating Scale; GAF – Global Assessment of Functioning; CGI – Clinical Global Impression; TRS – Treatment-resistant schizophrenia Only two patients (one borderline and one anxious avoidant personality disorder) in the TRS group had evidence to suggest the presence of personality disorder prior to the onset of the schizophrenia, whereas only one patient had personality disorder (schizoid personality disorder) in the non-TRS group. Overall, majority of the patients in both the groups had no diagnosable personality disorder prior to onset of schizophrenia. In the TRS group, 30.4% (n = 7) of the patients had lifetime diagnosis of tobacco dependence, of which 21.7% were still using tobacco in the dependence pattern at the time of assessment for the study. About one-fifth (21.7%; n = 5) of the patients in the TRS group had lifetime diagnosis of alcohol dependence, of which 8.7% fulfilled the diagnosis of alcohol dependence in the last 2 years too. However, no patient was using alcohol in the dependent pattern at the time of assessment for the study. When patients with and without TRS were compared, no significant difference was seen in terms of substance use pattern in the lifetime, last 5 years, and last 2 years.

Diffusion tensor imaging findings

As is evident from Table 2, in terms of FA values, significant difference between the two groups was noted only in the right superior longitudinal fasciculus (SLF) and right uncinate fasciculus (UF), with higher FA values for the right SLF and right UF for the non-TRS group [Figures 1 and 2]. However, when duration of untreated psychosis was used as a covariate, only significant difference persisted for right UF. Lack of significant difference persisted even after using duration of untreated psychosis as a covariate. However, when we used the Bonferroni correction, no significant difference was seen. In terms of ADC values, no significant difference emerged between both the groups on any of the tracts [Table 2].
Table 2

Comparison of fractional anisotropy and apparent diffusion coefficient (×10-6mm2/s) findings of white matter tracts of treatment-resistant schizophrenia group and nontreatment-resistant schizophrenia group

VariablesTRS group I (n=23)Non-TRS group II (n=15)T-test/χ2 (P)Covariate analysisa F (P)TRS group I (n=23)Non-TRS group II (n=15)T-test/χ2 (P)Covariate analysisa F (P)


Fractional anisotropyApparent diffusion coefficient
Anterior commissure0.22 (0.10)0.20 (0.15)t=0.51 (0.610)F=0.058 (0.811)2078.39 (857.1)1792.22 (689.65)t=1.08 (0.29)F=0.635 (0.431)
Genu0.70 (0.21)0.76 (0.21)t=−0.92 (0.365)F=0.819 (0.372)1204.53 (1662.14)734.05 (98.27)t=1.1 (0.28)F=1.494 (0.23)
Splenium0.87 (0.07)0.77 (0.26)t=1.6 (0.12)F=2.897 (0.098)662.29 (106.66)822.44 (463.64)t=−1.6 (0.12)F=2.852 (0.100)
Corpus callosum0.70 (0.18)0.66 (0.20)t=0.67 (0.51)F=0.489 (0.489)873.52 (358.95)826.11 (188.22)t=0.47 (0.64)F=0.970 (0.331)
Left anterior limb of internal capsule0.53 (0.20)0.48 (0.16)t=0.80 (0.43)F=0.342 (0.563)653.03 (139.57)724.97 (98.10)t=−1.73 (0.09)F=4.767 (0.036)
Left genu of internal capsule0.67 (0.15)0.68 (0.13)t=−0.88 (0.93)F=0.024 (0.878)613.4 (90.33)621.1 (82.68)t=−0.26 (0.79)F=0.299 (0.588)
Left posterior limb of internal capsule0.72 (0.10)0.73 (0.12)t=−0.21 (0.84)F=0.111 (0.741)662.03 (70.42)664.58 (51.89)t=−0.12 (0.90)F=0.003 (0.960)
Right anterior limb of internal capsule0.61 (0.19)0.56 (0.17)t=0.82 (0.41)F=0.044 (0.834)687.48 (222.14)725.79 (81.77)t=−0.64 (0.53)F=0.037 (0.849)
Right genu of internal capsule0.65 (0.16)0.68 (0.14)t=−0.65 (0.52)F=0.003 (0.958)639.93 (100.23)615.29 (96.48)t=0.75 (0.46)F=0.427 (0.518)
Right posterior limb of internal capsule0.75 (0.12)0.12 (0.11)t=0.81 (0.42)F=0.397 (0.533)626.55 (75.10)663.15 (63.28)t=−1.56 (0.13)F=0.698 (0.409)
Left cingulum0.71 (0.09)0.72 (0.07)t=−0.33 (0.75)F=0.141 (0.709)704.87 (125.37)701.87 (51.52)t=0.09 (0.93)F=0.456 (0.504)
Right cingulum0.65 (0.13)0.66 (0.04)t=−0.12 (0.90)F=1.013 (0.321)698.62 (86.98)717.33 (76.53)t=−0.68 (0.50)F=0.006 (0.636)
Left superior occipitofrontal fasciculus0.44 (0.07)0.48 (0.05)t=−1.73 (0.09)F=1.254 (0.270)673.58 (59.34)644.67 (38.20)t=1.71 (0.10)F=3.114 (0.086)
Right superior occipitofrontal fasciculus0.44 (0.08)0.46 (0.06)t=−0.93 (0.36)F=0.266 (0.609)670.13 (88.63)653.99 (35.20)t=1.05 (0.30)F=0.179 (0.675)
Left superior longitudinal fasciculus0.41 (0.06)0.42 (0.06)t=−0.80 (0.43)F=1.254 (0.270)665.96 (43.14)648.82 (33.38)t=1.30 (0.20)F=1.465 (0.234)
Right superior longitudinal fasciculus0.41 (0.07)0.45 (0.06)t=−2.05 (0.047)*F=0.266 (0.609)662.19 (35.55)653.99 (35.21)t=0.7 (0.49)F=0.718 (0.403)
Left inferior occipitofrontal fasciculus0.54 (0.09)0.57 (0.09)t=−1.10 (0.28)F=0.654 (0.424)789.33 (105.16)769.85 (86.18)t=0.6 (0.55)F=0.646 (0.427)
Right inferior occipitofrontal fasciculus0.57 (0.11)0.51 (0.09)t=1.71 (0.10)F=0.357 (0.067)750.30 (78.76)752.98 (56.20)t=−0.11 (0.91)F=0.253 (0.618)
Left inferior longitudinal fasciculus0.39 (0.08)0.40 (0.09)t=−0.19 (0.85)F=0.033 (0.856)774.82 (94.58)786.93 (116.79)t=−0.35 (0.73)F=2.045 (0.162)
Right inferior longitudinal fasciculus0.38 (0.10)0.38 (0.11)t=0.12 (0.90)F=0.045 (0.833)761.38 (96.90)728.23 (66.70)t=1.16 (0.25)F=0.003 (0.958)
Left uncinate fasciculus0.38 (0.10)0.36 (0.10)t=0.64 (0.53)F=0.175 (0.678)780.97 (102.04)811.15 (89.13)t=−0.93 (0.36)F=0.403 (0.530)
Right uncinate fasciculus0.36 (0.09)0.44 (0.11)t=−2.46 (0.019)*F=6.122 (0.018)*770.24 (95.71)775.9 (69.74)t=−0.2 (0.84)F=0.119 (0.732)

*P≤0.05; **P≤0.01; ***P≤0.001. aCovariate: Duration of untreated psychosis. χ2 – Chi-square value; χ2b – Chi-square value with Yate’s correction; U – Mann-Whitney value; t – T test; SD – standard deviation; FE – Fisher’s exact value; TRS – Treatment-resistant schizophrenia

Figure 1

The tract superior longitudinal fasciculus (yellow arrowhead), an association fiber tract well represented in the color green. Uncinate fibers (blue arrow) are forming a loop and turning around the lateral sulcus; in turn connecting inferior frontal and temporal lobes. The ellipsoids depict anisotropy in both the tracts, with higher fractional anisotropy in the right superior longitudinal fasciculus and right uncinate fasciculus in the control group

Figure 2

(a) Fractional anisotropy at a point for the densest portion of uncinate fasciculus. (b) Fractional anisotropy at a point for the densest portion of superior longitudinal fasciculus

Comparison of fractional anisotropy and apparent diffusion coefficient (×10-6mm2/s) findings of white matter tracts of treatment-resistant schizophrenia group and nontreatment-resistant schizophrenia group *P≤0.05; **P≤0.01; ***P≤0.001. aCovariate: Duration of untreated psychosis. χ2 – Chi-square value; χ2b – Chi-square value with Yate’s correction; U – Mann-Whitney value; t – T test; SD – standard deviation; FE – Fisher’s exact value; TRS – Treatment-resistant schizophrenia The tract superior longitudinal fasciculus (yellow arrowhead), an association fiber tract well represented in the color green. Uncinate fibers (blue arrow) are forming a loop and turning around the lateral sulcus; in turn connecting inferior frontal and temporal lobes. The ellipsoids depict anisotropy in both the tracts, with higher fractional anisotropy in the right superior longitudinal fasciculus and right uncinate fasciculus in the control group (a) Fractional anisotropy at a point for the densest portion of uncinate fasciculus. (b) Fractional anisotropy at a point for the densest portion of superior longitudinal fasciculus

DISCUSSION

Two main schools of thought exist regarding the neurobiology of TRS. One, which can be characterized as the continuum hypothesis, posits that the same pathophysiological processes underlie symptoms in both treatment-responsive and -resistant patients, but that these processes occur to a greater degree in patients with TRS, which leads to poor response to treatment. The other hypothesis, which can be considered, is the categorical hypothesis, which suggests that patients with TRS have a fundamentally different pathophysiology compared to those showing response to treatment, and thus current treatments are ineffective as they target the wrong processes.[12] The present study attempted to understand the etiopathogenesis of TRS on the basis of these hypotheses. In the present study, in terms of FA values, when the comparison was done without statistical correction, significant difference between the two groups was noted only in the right SLF and right UF, with higher FA values for the non-TRS group. However, this disappeared when the Bonferroni correction was applied. In terms of ADC findings of white-matter tracts, no significant difference emerged between the two groups on any of the tracts. There is only one study in the existing literature, which has evaluated the white-matter integrity in patients with TRS by using DTI and compared the same with patients without treatment refractoriness.[6] This study concluded that there are no differences in FA values/white-matter integrity between treatment refractory and nonrefractory groups following voxel-wise analysis TBSS approach.[6] The findings of the present study support the same. As per evidence, normal controls have asymmetry, with anisotropy on the left more than right in the UF and patients with chronic schizophrenia lack the normal left-greater-than-right anisotropy asymmetry in the UF.[131415] Findings of the present study must be interpreted in light of its limitations in the form of small sample size and cross-sectional assessment. Cross-sectional comparisons of treatment-resistant and -responsive patients can potentially indicate differences that may underlie treatment resistance. They cannot, however, determine causality. In the present study, the study participants in the non-TRS group were in clinical remission, whereas participants of the TRS group were symptomatic at the time of the assessment. Have a non-TRS symptomatic group, could have been better. Furthermore, prospective studies will be required to evaluate whether any neurobiological markers have the potential for clinically relevant prediction of treatment resistance. The present study did not involve the assessment of cognitive functions and did not include a healthy control group. DTI findings were assessed manually rather than using more sophisticated techniques such as tract-based spatial statistics. Future studies must attempt to overcome these limitations.

CONCLUSION

The present study demonstrates that white-matter integrity does not significantly differ between the patients with and without TRS.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.
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Journal:  Psychol Assess       Date:  2005-09

Review 8.  The Mini-International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10.

Authors:  D V Sheehan; Y Lecrubier; K H Sheehan; P Amorim; J Janavs; E Weiller; T Hergueta; R Baker; G C Dunbar
Journal:  J Clin Psychiatry       Date:  1998       Impact factor: 4.384

9.  Guidelines for rating Global Assessment of Functioning (GAF).

Authors:  I H Monrad Aas
Journal:  Ann Gen Psychiatry       Date:  2011-01-20       Impact factor: 3.455

Review 10.  Brain-imaging studies of treatment-resistant schizophrenia: a systematic review.

Authors:  Elias Mouchlianitis; Robert McCutcheon; Oliver D Howes
Journal:  Lancet Psychiatry       Date:  2016-03-04       Impact factor: 27.083

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