Hyperbaric oxygen therapy improves symptoms, brain's microstructure and functionality in veterans with treatment resistant post-traumatic stress disorder: A prospective, randomized, controlled trial.

INTRODUCTION: Post-traumatic stress disorder (PTSD) is characterized by changes in both brain activity and microstructural integrity. Cumulative evidence demonstrates that hyperbaric oxygen therapy (HBOT) induces neuroplasticity and case-series studies indicate its potentially positive effects on PTSD. The aim of the study was to evaluate HBOT's effect in veterans with treatment resistant PTSD.
METHODS: Veterans with treatment resistant PTSD were 1:1 randomized to HBOT or control groups. All other brain pathologies served as exclusion criteria. Outcome measures included clinician-administered PTSD scale-V (CAPS-V) questionnaires, brief symptom inventory (BSI), BECK depression inventory (BDI), brain microstructural integrity evaluated by MRI diffuse tensor imaging sequence (DTI), and brain function was evaluated by an n-back task using functional MRI (fMRI). The treatment group underwent sixty daily hyperbaric sessions. No interventions were performed in the control group.
RESULTS: Thirty-five veterans were randomized to HBOT (N = 18) or control (n = 17) and 29 completed the protocol. Following HBOT, there was a significant improvement in CAPS-V scores and no change in the control (F = 30.57, P<0.0001, Net effect size = 1.64). Significant improvements were also demonstrated in BSI and BDI scores (F = 5.72, P = 0.024 Net effect size = 0.89, and F = 7.65, P = 0.01, Net effect size = 1.03). Improved brain activity was seen in fMRI in the left dorsolateral prefrontal, middle temporal gyri, both thalami, left hippocampus and left insula. The DTI showed significant increases in fractional anisotropy in the fronto-limbic white-matter, genu of the corpus callosum and fornix.
CONCLUSIONS: HBOT improved symptoms, brain microstructure and functionality in veterans with treatment resistant PTSD.

Introduction

Post-traumatic stress disorder (PTSD) is a complex, chronic, and debilitating psychiatric disorder that develops in response to severe psychological traumatic exposure. PTSD is characterized by intrusive thoughts, nightmares and flashbacks of past traumatic events, avoidance of trauma reminders, hypervigilance, sleep disturbances and persisting dysregulation of the stress response [1]. These protracted symptoms lead to considerable social, occupational, and interpersonal dysfunctions. The global cross-national lifetime prevalence of PTSD reported by the World Health Organization (WHO) is 3.9% [2], while among combatants the prevalence can be as high as 30% [3]. Unfortunately, the current available treatments, including medications and trauma focused psychotherapy, have limited effect and nearly half of the patients suffer from treatment resistant PTSD [4].

New brain imaging techniques enable better understanding of the pathophysiology responsible for developing PTSD. It is now clear that traumatic events cause long-term changes of brain activity and microstructural integrity. The dominant trauma-related pathologies are demonstrated in the frontal-limbic circuit, amygdala, hippocampus and prefrontal cortex [5-8].

Hyperbaric oxygen therapy (HBOT) includes the inhalation of 100% oxygen at pressures exceeding 1 atmosphere absolute (ATA), thus enhancing the amount of oxygen dissolved in the body tissues. Many of the beneficial effects of HBOT can be explained by improvements in tissue/cerebral oxygenation. However, it is currently understood that the combined action of intermittent hyperoxia and hyperbaric pressure, triggers both oxygen and pressure sensitive genes [9]. Additionally, increases in cerebral metabolic rates, restoration of mitochondrial functions, stimulation of cell proliferation and maturation of endogenous neural stem cells, and induction of anti-inflammatory, angiogenic and neurogenic factors have all been demonstrated after HBOT(9). Cumulative evidence from post-stroke and traumatic brain injury (TBI) studies demonstrate that HBOT induces neuroplasticity in the chronic metabolic dysfunctional brain regions even years after the brain insult [10,11]. Recent studies have also demonstrated HBOT induced neuroplasticity and significant clinical improvements in patients with fibromyalgia, including those in whom fibromyalgia was induced by child abuse [12,13].

The potential beneficial effects of HBOT on PTSD were investigated in combat veterans with TBI which is commonly combined with PTSD. In most of the studies, a significant clinical improvement in PTSD symptoms was demonstrated [14-20]. However, to the best of our knowledge, none of these studies focused on PTSD as a stand-alone pathology.

The aim of this study was to evaluate the effect of HBOT on clinical outcomes, brain functionality and brain microstructural integrity in veterans suffering from treatment resistant combat associated PTSD.

Materials and methods

Study design and patients

The study was a randomized, prospective controlled trial conducted at the Sagol Center for Hyperbaric Medicine and Research at the Shamir Medical Center, Israel, between March 2018 and October 2019. The protocol was approved by the Shamir Institutional Review Board (199/17) and registered in the National Institute of Health Clinical Trials Registry (NCT03466554).

Patients were referred to the study by their psychiatrist or psychotherapist, or applied for the study after reading an advertisement in their veterans’ social media groups. The study included male veterans, age 25 to 60 years old, with combat associated, treatment resistant PTSD lasting at least four years prior to their inclusion. Patients were recruited if they had persistent residual debilitating PTSD symptoms, were exposed to at least one trauma focused therapy and pharmacotherapy, and fulfilled the CAPS questionnaire diagnostic criteria for PTSD. Exclusion criteria included history of TBI or any other brain pathology, active malignancy, substance use at baseline (except for prescribed cannabis, and only if nebulized or taken as a tincture), current manic or psychotic episodes, serious current suicidal ideation, severe or unstable physical disorders or major cognitive deficits at baseline, HBOT for any reason prior to study enrollment, chest pathology incompatible with pressure changes (including active asthma), ear or sinus pathologies incompatible with pressure changes, inability to perform an awake brain MRI and active smoking.

Cognitive evaluation at baseline was performed using the computerized cognitive testing battery "Neurotrax". Cognitive scores are presented as normalized scores according to age and education groups, on an IQ-style scale, where 100 is the mean normalized score and one standard deviation equals to 15 points [21].

Randomization and masking

Included participants were 1:1 randomly assigned to the treatment or control group according to a computer-generated randomization list. Assessors were blinded to the participants’ allocation.

Procedures

After receiving detailed information regarding study procedure and signing an informed consent form, participants underwent a baseline evaluation which included a review of their medical history, a physical examination, a psychological interview by two senior clinicians, questionnaires and brain imaging. HBOT was given in addition to the patients’ pre-inclusion psychotherapy. Participants in the control group continued with their pre-inclusion psychotherapy program and did not receive any hyperbaric treatment. No additional psychotherapy or trauma focused therapy was given as part of the study protocol.

Participants were evaluated at baseline and after three months of HBOT or control.

HBOT: Participants were treated in a multiplace chamber (HAUX-Life-Support GmbH) for a total of 60 daily sessions, five days a week. Each session consisted of 90 minutes exposure to 100% oxygen at 2 ATA with five-minute air breaks every 20 minutes.

Participants in both treatment and control groups continued their psychological and pharmacological treatments as they did before their inclusion. Any changes in the frequency of psychological treatments or pharmacotherapy doses were reported and documented. Monthly meetings with study investigators were scheduled during both treatment and control periods. Unscheduled visits were provided as needed.

Outcomes

The primary objective was defined as the change in the clinician-administered DSM-V (CAPS-V) PTSD scale score from baseline. The brief symptom inventory−18 (BSI-18), and Beck depression inventory-II (BDI-II) questionnaires served as secondary clinical endpoints. Changes in brain MRI diffuse tensor imagine (DTI) sequence and n-back task in functional MRI (fMRI) were also analyzed as secondary endpoints.

is a structured interview-based test that consists of 30 items. Items are rated on a 0 to 4 severity scale. Twenty of the items reflect the severity of DSM-V PTSD symptoms and served as the primary endpoint. The score ranges between 0 and 80, with higher scores indicating more severe PTSD symptoms. The interview was administered by a study investigator, under the supervision of the study psychiatrist at baseline and 1 to 4 weeks after the end of the HBOT or control period.

In addition, participants completed the following questionnaires at baseline and 1 to 4 weeks after the end of the study period:

—BDI-II is a widely used psychometric tests for measuring the severity of depression. It consists of 21 multiple-choice questions and a self-report inventory about how the subject has been feeling in the last week. Each answer is scored on a scale value of 0 to 3. The scored ranges between 0 and 63, with higher scores indicating more severe depression symptoms.

—The BSI-18 contains 18 items in three symptom scales: somatization (6 items), depression (6 items), and anxiety (6 items). Each item is rated on the same 0 to 4 scale that reflects symptom severity in the last seven days, and the sum of all responses yields a global severity index (GSI). Scores range between 0 and 72, with the higher scores indicating worse symptoms.

Imaging data acquisition

MRI scans were performed on a MAGNETOM Skyra 3T Scanner, configured with a 20-channel receiver head coil (Siemens Healthcare, Erlangen, Germany). Functional imaging data consisted of 128 volume measurements of gradient-echo (EPI) blood oxygen level dependent (BOLD) contrast sequences. Scan parameters: TR = 3000 ms, TE = 30 ms, flip angle = 90°, voxel size = 3.0 x 3.0 x 3.0 mm, distant factor = 25%, FOV = 192 mm2, within slice resolutions of 64×64, and 36 contiguous slices parallel to the AP-PC plane. Diffusion whole brain images were acquired with the following parameters: 63 axial slices, slice thickness = 2.2 mm, voxel size = 1.8 x 1.8 mm, TR = 10,300 ms, TE = 89 ms, and matrix = 128 x 128 mm. Diffusion gradients were applied along 30 noncollinear directions (b = 1000 s/mm2) and one volume without diffusion weighting. T1-weighted images were acquired with 3D MPRAGE sequences in sagittal orientation with 0.9 mm isotropic resolution. Sequence parameters: TR = 2,000 ms, TE = 2.41 ms, flip angle = 8°, TI = 928 ms, FOV = 245 x 245, and 192 contiguous slices.

Functional task design

The N-back working memory task is one of the most popular paradigms for functional neuroimaging studies, which refers to temporary storage and manipulation of information. In this study, we used a block design paradigm, consisting of two-condition alternating blocks (0-Back and 2-Back) over a course of eight cycles. Each block consisted of a series of 12 letters. Each letter was presented for 1500 ms, followed by a 1500 ms fixation interval. During the 0-Back condition, participants were asked to respond by pressing a button (ResponseGrip, NordicNeuroLab Inc., Norway) when a target Hebrew letter "ג" was presented. In the 2-Back condition, participants were asked to respond when the current letter was identical to the one presented two trials back. The ratio of target to non-target letters presented in each block is 3/4:12. Participants rehearsed a practice version of the test with a technician outside the scanner to ensure comprehension of the task demands. NordicAktiva, (NordicNeuroLab Inc., Norway, www.nordicneurolab.no) was used for stimuli presentation, performance accuracy, and response time acquisition.

MRI data analysis

Preprocessing of the raw diffusion data, and calculation of DTI-FA (fractional anisotropy) maps were performed using ExploreDTI, and included corrections for eddy current distortion and participant motion. Spatial normalization was performed for each patient based on the mean diffusion image using the ICBM template, based on T1 contrast. The normalization parameters were applied to the DTI maps. Finally, spatial smoothing with a kernel size of 6 mm full width half maximum (FWHM) was applied. To avoid partial volume bias in the statistical map, and to limit statistical testing to white matter, FA maps were thresholded at 0.2.

Analysis of the time series BOLD data was performed using statistical parametric mapping software SPM12 (Welcome Department of Cognitive Neurology, Institute of Neurology, University College London, UK), through a standard preprocessing procedure. All images were initially slice-time corrected, realigned and resliced using a 6-parameter rigid body spatial transformation to correct head motion, and normalized to the MNI space (Montreal Neurological Institute) by using the unified segmentation normalization algorithm. Finally, spatial smoothing was performed using a 6 mm FWHM Gaussian kernel. The general linear model were applied on a subject level. The design matrix incorporated the task and the six spatial axes movement repressors. The task repressors were modeled as a boxcar function, and were convolved with a canonical hemodynamic response function. A high-pass filter (cutoff of 128 s) was applied to account for slow signal drift. All parametric maps thresholds were set at P < 0.05 false discovery rate (FDR) corrected for multiple comparisons. The mean percent BOLD signal change was calculated within spherical regions of interest (6 mm radius of gray matter volume), obtained from this analysis, and centered at the peak t value coordinates.

Statistical analysis

Sample size

Since there was no previous data from prospective studies on the potential beneficial effects of HBOT on PTSD, we followed the recommendations of Hertzog [22] for a sample size determination. A small to medium effect size of 0.3 in a repeated measures ANOVA design, with a power of 85% and an alpha of 5%, a total of 28 participants would be required. Adding a 15% dropout rate would require 32 patients in total.

Data analysis

Unless otherwise stated, continuous data were expressed as means ± standard-deviations. Independent and dependent t-tests with a two-tail distribution were performed to compare variables between and within the two groups, when a normality assumption held according to the Kolmogorov-Smirnov test. Net effect sizes were evaluated using Cohen’s d method, defined as the improvement from baseline after HBOT minus control three months improvement divided by the pooled standard deviation (SD) of the composite score. Positive effect sizes indicate improvement. Categorical data were expressed in numbers and percentages and compared by chi-square/Fisher’s exact test to identify significant variables. A value of P < 0.05 was considered significant. Continuous parameters correlations were performed using the Pearson correlation analysis.

To evaluate HBOT’s effect, a mixed-model repeated-measure ANOVA model was used to compare post-treatment and pre-treatment data. The model included time, group and the group-by-time interaction. Non-imaging data analysis was followed by the Bonferroni post-hoc correction.

Brain imaging maps were analyzed using a voxel-based method to generate statistical parametric maps. Group parametric maps were corrected using the Benjamini–Hochberg False Discovery Rate (FDR) method [23]. A mixed design repeated measure ANOVA model was used to test the main interaction effect between time and group implemented in SPM software (version 12, UCL, London, UK). A sequential Hochberg correction [24] was used to correct for multiple comparisons (P < 0.05).

Data was analyzed using SPSS software (version 22.0), and the Matlab R2019b (Mathworks, Natick, MA) Statistics Toolbox.

Results

Between March 2018 and April 2019, 50 subjects were recruited, and 15 who did not fit the study criteria were excluded. Accordingly, 35 subjects were randomized to the HBOT (N = 18) or control (N = 17) groups. As detailed in Fig 1, one patient allocated to HBOT was not able to cooperate with the treatment protocol and preferred to stop the treatment after 20 sessions, and three patients had frequent treatment stoppages because of upper respiratory tract infections (could not equilibrate the ear pressure). Two patients from the control group refused to attend the scheduled meetings and the final analysis. Therefore, of the 35 test subjects, 14 completed the HBOT protocol and 15 completed the control protocol.

Fig 1

Study flowchart.

Baseline patient characteristics are summarized in Table 1. The mean age at baseline was 39.3 ± 8.1 and 32.4 ± 9.2 and the mean time from last combat exposure was 11.5 ± 5.8 and 10.3 ± 6.7 years for the HBOT and control groups, respectively. The baseline global cognitive score was on the normal range expected for the patients’ age and gender, 99.4±6.2 and 98.5±8.7 in the HBOT and control group respectively, p = 0.75.

Table 1

Patient characteristics.

	Treatment Group	Control Group	P-value
N	14	15
Age (y)	39.3±8.1	32.4±9.2	0.084
Military exposure (y)	6.8±3.6	5.2±4.8	0.33
Time from last combat exposure (y)	11.5±6.1	11.1±6.4	0.85
Total CAPS score	46.6±11.5	49.5±10.7	0.50
Mild PTSD (20–39)	3(21%)	2(13%)	0.65
Moderate PTSD (40–59)	10(71%)	11(73%)	1.00
Severe PTSD (60–79)	1(7%)	2(13%)	0.97
Education (y)	14.2±2.2	13.7±2.5	0.58
Life partner	9(64%)	6(40%)	0.27
Working	6(43%)	8(53%)	0.71
Global cognitive score *	99.4±6.2	98.5±8.7	0.75
Current major depression *	10(71%)	13(86%)	0.39
History pharmacotherapy	13(93%)	12(80%)	0.59
History of psychotherapy
PE	5(36%)	4(27%)	0.69
EMDR	10(71%)	9(60%)	0.69
CBT	14(100%)	13(87%)	0.48
Current medications
SSRI/SNRI	8(57%)	8(53%)	1.00
BDZ	6(43%)	6(40%)	1.00
Anti-psychotic	4(29%)	4(27%)	1.00
Cannabis	12(86%)	10(67%)	0.39
Cannabis (g/ month)	31.4±19.1	25.0±20.8	0.39

* normalized scores presented on an IQ-style scale, where 100 is the mean normalized score and one standard deviation of 15 points.

Primary endpoint

Analysis of the CAPS score are summarized in Table 2. At baseline, there were no differences between the groups in any of the CAPS score parameters. A significant improvement in total CAPS score by 17.7 points (CI 11.3–24.1), with group by time interaction (F = 30.57, p<0.0001, Net effect size = 1.643, Supporting information), was demonstrated in the HBOT group. Additionally, the HBOT group had significant improvements in all of the subcategories of the CAPS score (Table 2) (Fig 2). No differences in total CAPS scores or in any of the subcategories were seen in the control group.

Table 2

CAPS measures results.

	HBOT ARM (N = 14)				CONTROL ARM (N = 15)
	Baseline	Post HBOT	Change [95% CI]	3 Months P value	Baseline	Control	Change [95% CI]	3 Months P value	Baseline	Change	Cohen’s d*	ANOVA (Group-by-Time) Interaction
												F	P
B. Intrusion symptoms	12.2±3.8	6.6±4.7	-5.6 [-7.7, -3.6]	0.000	12.9±2.6	13.1±2.1	0.3 [-1, 1.5]	0.658	0.610	0.000	1.741	28.9	0.000
C. Avoidance symptoms	4.5±1.7	2.3±1.8	-2.2 [2.9, -1.5]	0.000	4.5±1.8	5.0±1.4	0.5 [-0.5, 1.4]	0.313	0.960	0.000	1.797	23.4	0.000
D. Cognitions and mood symptoms	17.5±3.7	11.1±7.4	-6.4 [-10.2, -2.6]	0.003	16.8±5.6	17.5±3.8	0.7 [-1.2, 2.6]	0.465	0.700	0.001	1.109	13.3	0.001
E. Arousal and reactivity symptoms	12.3±4.5	9.0±5.6	-3.4 [-6.1, -0.6]	0.022	15.3±3.2	15.9±3.6	0.7 [-0.6, 1.9]	0.265	0.060	0.008	0.865	8.5	0.007
T. Total	46.6±11.5	28.5±17.4	-18.1 [-25.4, -10.8]	0.000	49.5±10.7	51.5±8.4	2.0 [-1.3, 5.3]	0.211	0.500	0.000	1.643	30.6	0.000

Data are presented as mean ± SD; CI, confidence interval; Bold, significant after Bonferroni correction; * Cohen’s d net effect size.

Fig 2

CAPS scores paired box plot.

The central mark indicates the median, and the bottom and top edges of the box indicate the 25th and 75th percentiles, respectively. + Symbols indicate outliers.

Secondary endpoints

Questionnaire results are summarized in Table 3. At baseline, there were no significant differences in all questionnaire domains. Significant group-by-time interactions (F = 5.72, P = 0.024, Net effect size = 0.89) were demonstrated in total BSI-II scores and in the depression subcategory (F = 10.72, P = 0.003, Net effect size = 1.22, S2 Table). A trend towards improvement was demonstrated in the somatization and anxiety subcategories, but the improvements did not reach statistical significance (F = 1.26, P = 0.27 and F = 3.34 and P = 0.079 for somatization and anxiety respectively). In addition, a significant group-time interaction (F = 7.65, P = 0.01, Net effect size = 1.03, Supporting Information) was demonstrated in the total BDI-II score after HBOT. In addition, statistically significant correlations were found between the percent change in total CAPS Score and the percent change in BDI-II and BSI-18 questionnaires (r = 0.62–0.67, p<0.0004, Supporting Information).

Table 3

Questionnaire results.

	HBOT ARM (N = 14)				CONTROL ARM (N = 15)
	Baseline	Post HBOT	Change [95% CI]	3 Months P value	Baseline	Control	Change [95% CI]	3 Months P value	Baseline	Change	Cohen’s d*	ANOVA (Group-by-Time) Interaction
												F	P
BSI
Total	38.0 ± 13.0	27.0 ± 16.0	-11.0 [-19.2, -2.8]	0.012	44.3 ± 7.9	43.8 ± 10.9	-0.5 [-5.5, 4.6]	0.846	0.134	0.024	0.890	5.7	0.020
Somatization	10.0 ± 5.5	7.6 ± 5.4	-2.3 [-5.2, 0.4]	0.092	12.8 ± 3.4	12.4 ± 5.0	-0.4 [-2.9, 2.1]	0.739	0.120	0.272	0.420	1.3	0.270
Anxiety	14.3 ± 5.1	10.2 ± 6.4	-4.1 [-7.6, -0.5]	0.027	17.5 ± 3.4	16.9 ± 3.6	-0.6 [-2.8, 1.6]	0.565	0.062	0.079	0.680	3.3	0.080
Depression	13.7 ± 4.8	9.1 ± 5.5	-4.6 [-7.3, -1.8]	0.003	14.0 ± 3.0	14.5 ± 3.8	0.5 [-1.4, 2.5]	0.571	0.854	0.003	1.220	10.7	0.003
BECK	24.4 ± 6.8	18.1 ± 9.5	-6.3 [-9.7, -2.9]	0.002	26.8 ± 6.7	27.5 ± 7.7	0.6 [-3.5, 4.7]	0.757	0.357	0.010	1.030	7.7	0.010

Data are presented as mean ± SD; CI, confidence interval; Bold, significant after Bonferroni correction; * Cohen’s d net effect size.

Regional brain microstructure integrity

One patient did not perform MRI due to retained metal shrapnel in the lungs that was detected in a chest X-ray after inclusion. DTI-MRI was analyzed from 13 patients from the HBOT group and from 15 patients from the control group. Voxel-based DTI analysis of brain white-matter FA maps is shown in Fig 3 and in Table 4. Significant group-time interactions were demonstrated in the HBOT group compared to the control group in frontal white-matter fiber bundles connecting the thalamus and frontal lobe (anterior limb of internal capsule L and corona radiata R) and in the genu of corpus callosum, connecting between the frontal lobes. In the parietal lobe, significant clusters were found in parietal white-matter (adjacent to the superior longitudinal fasciculus) and in the anterior limb of the internal capsule and cerebral peduncle (ascending and descending motor and sensory fibers). Significant clusters were also found in the fornix, in an area adjacent to the hippocampus.

Fig 3

Statistical parametric maps of the group-by-time interaction for the white matter FA.

(F: Fornix; GCC: Genu of corpus callosum; ACR: Anterior corona radiata; ALIC: Anterior limb of internal capsule; PLIC: Posterior limb of internal capsule; PWM: Parietal white matter).

Table 4

Statistical parametric maps of the group-by-time interaction for the white matter FA (L left, R right, X, sagittal, Y, coronal, Z, axial, coordinates refers to Montreal Neurological Institute.

Peak Region	Cluster Size	x	y	z	t Value	p Value
L Posterior limb of internal capsule	79	-29	-8	6	3.67*	0.0001
R Parietal white matter	93	21	-34	53	3.33*	0.001
L Anterior limb of internal capsule	46	-11	5	-5	3.22*	0.001
Genu of corpus callosum	91	33	32	-8	3.07	0.002
R Anterior corona radiate	228	-13	30	-5	3.04	0.002
L Fornix	111	-28	-6	-15	2.8	0.004

* Satisfied Hochberg correction p<0.05).

Only the posterior and anterior limbs of the internal capsule and parietal white-matter passed the correction to multiple comparisons (p<0.05, corrected). However, since this was a small sample size and we evaluate the treatment effect including a control group, we included clusters larger than 40 voxels passing p <0.01 uncorrected.

Task-related functional imaging results

Brain activity of the PTSD patients was obtained from 13 patients from the HBOT group, and 15 patients from the control group patients. The whole‐brain task related activation (2‐back > 0‐back) at baseline and after HBOT/control sessions is shown in Fig 4 (P < 0.05, FDR corrected). The two-sample t-test analysis, performed between groups at baseline, yielded no significant functional differences. Brain clusters with a significant group-by-time interaction effect (p<0.05, Hochberg corrected) are listed in Table 5. Improved activity after HBOT was demonstrated in the left dorsolateral prefrontal, middle temporal and temporal gyri as well as in both thalami, left hippocampus and left insula. No significant functional differences between the two control group fMRI sessions were found (Fig 4). Statistically significant correlations were demonstrated between mean percent BOLD signal changes in peak significantly activated regions and percent change in total CAPS score (r = 0.42–0.67, p<0.05, Supporting Information).

Fig 4

Main regional loci of brain activation in a verbal working memory task (2-Back– 0-Back) Group analysis, p< 0.05, FDR corrected.

Table 5

Local maxima of brain activation (2-Back– 0-Back): Group-by-time interaction.

Peak Region	BA	Cluster Size	x	y	z	t value	p value
R Fusiform Gyrus	20	68	44	-26	-24	4.85	0.0000
L Thalamus	50	78	-12	-10	8	4.79	0.0000
R Thalamus	50	64	12	-28	2	4.67	0.0000
L Hippocampus	54	95	-34	-30	-12	4.64	0.0000
L Temporal Gyrus	21	48	-54	-44	10	4.24	0.0001
L Insula	13	21	-44	-2	-8	3.90	0.0001
L Dorsolateral Prefrontal	9	20	-28	40	44	3.89	0.0002
L Medial Posterior Parietal	7	59	-16	-70	40	3.89	0.0002
R PCC	23	30	0	-14	34	3.87	0.0002
L Superior Temporal Gyrus	38	20	-44	4	-18	3.82	0.0002
L Middle Temporal Gyrus	39	21	-30	-76	34	3.70	0.0003

Safety and side effects

HBOT for PTSD was well tolerated with seven documented events of mild and spontaneously resolved middle ear barotrauma. Seven subjects from the HBOT group had an unexpected surfacing of new memories during the HBOT course. In all accept one participant memories surfaced gradually, during the second half of the treatment course (after 25–35 sessions of HBOT) in peaces that gathered to whole clear picture of the event. In one of the participants, the new memory appeared abruptly as flashback, following the fifth HBO session.

The recovery of the memories was usually accompanied by severe distress followed by integration of the memory and resolution of the distress. Patients who reported surfacing of new memories were interviewed and their symptoms and memories were documented.

No intentional questioning regarding memory surfacing was done, and thus memory surfacing could not be ruled out in other patients who might not reported as it.

Discussion

The current study evaluates for the first time in a prospective controlled study, the effect of HBOT on veterans suffering from treatment resistant PTSD. HBOT induced significant reductions in the PTSD symptoms and the associated depression as assayed by CAPS-V, BDI and BSI questionnaires. The marked clinical improvement was associated with improved brain functionality and microstructural integrity as evident by fMRI and DTI-MRI.

HBOT’s potential beneficial effects on combat associated PTSD was demonstrated in previous studies that evaluated its effect on TBI and included PTSD related symptoms as one of the study endpoints [14-20]. The last study from BIMA study team [20] clearly demonstrated pronounced effects of HBOT on the subgroup of veterans who had concomitant PTSD symptoms, with PTSD effected veterans benefiting more from HBOT than veterans without PTSD. Since TBI and PTSD share common symptoms such as nervousness, sleep disorders, and impaired cognitive function, it is difficult to assign the improvement to either one of the pathologies. In the current study, only patients with PTSD who did not have TBI were included, and any history of TBI served as an exclusion criterion. Thus, both clinical and radiological effects demonstrated in the current study can only be associated to HBOT’s effects on PTSD.

PTSD’s current treatment success rate is poor. Trauma-focused psychotherapy is currently the treatment of choice while pharmacotherapy is added when psychotherapy is insufficient. However, up to 50% fail to respond to any of the available treatments. The lack of effective treatments might have contributed to the successful recruitment in the current trial, despite the demanding treatment protocol.

Brain imaging changes can serve as markers for poor treatment responses [25]. A review of the published studies using high resolution and functional MRI techniques, indicate failure of the frontal-limbic circuit as PTSD’s hallmark [5-8]. Diminished prefrontal inhibition and a hyperactive amygdala in response to both trauma-related [5,6] and non-trauma-related [6] stimuli in PTSD patients are consistent with diminished prefrontal inhibition of fear circuitry. Functional MRI studies using N-back tasks, demonstrate under-recruitment of prefrontal neurons, mostly dorsolateral PFC, and parietal cortex. Changes in brain microstructure, demonstrated by DTI-MRI, including reduced white-matter integrity, typically seen in the left frontal and temporal tracts and thalamo-cortical tracts, are also part of the fronto-limbic circuit failure [26,27]. In addition, impaired inter-hemispheric connectivity, as evident by decreased FA values in the genu of the corpus callosum, was also described among PTSD patients [28].

In the current study, using fMRI and the N-back paradigm, restoration of fronto-limbic integrity was demonstrated, with improved recruitment of the left dorsolateral PFC, of both thalami and of the left hippocampus. Improved microstructural integrity between frontal and parietal or temporal regions was also demonstrated using MRI-DTI as increased FA in the anterior limb of the left internal capsule, right corona radiata and fornix. Restoration of the fronto-limbic circuit may explain the significant clinical improvement related to emotional regulations as reflected by a decrease in total, and in particular, criterion E of the CAPS score. Since the intrusive symptoms can also be a result of the cortex’s failure to inhibit the limbic system [7], restoration of fronto-limbic circuit may also explain the significant clinical improvements in criterion B of the CAPS score.

In addition to the fronto-limbic circuit, HBOT induced significant improvements of hippocampal activity as demonstrated by fMRI and the integrity of its connections, assessed as improved FA in the fornix in DTI imaging. The hippocampus has a central role in PTSD pathogenesis, and it may serve as an important treatment target. The hippocampus is involved in memory performance and in information processing deficits observed in PTSD patients [29]. Hippocampal integrity is also crucial for fear extinction [30].

Studies on hippocampal cell culture show that HBOT can directly induce orthodromic activity and neural plasticity [31]). In addition, the dentate gyrus of the hippocampus serves as one of the major niches for endogenous neuronal stem cells (NSC), and recent reports demonstrated HBOT’s effect on mitochondrial signaling and regulation of NSC proliferation and differentiation [32].

One of the interesting findings in the current study, was the surfacing of inaccessible memories in half of the patients from the HBOT group. A similar HBOT effect on childhood sexual abuse related repressed memories was previously reported in a fibromyalgia patient study [13]. It is known that direct triggering of the hippocampus by deep brain stimulation can induce surfacing of inaccessible memories [33]. Therefore, the surfacing of memories in our veteran population can be related to the direct neuroplasticity effect detailed above at the hippocampal level.

Study limitations

First, a cohort of 35 randomized patients is rather small. Even though the results are significant, larger scale clinical trials are required to confirm the finding presented. Second, even with randomization and blinded imaging analysis, participants were not blinded to the treatment arm, due to the inherent difficulty of conducting a sham control in HBOT trials [9,2] This could possibly affect the questionnaires. However, the chronic unremitting nature of PTSD among our participants together with the correspondence between the clinical improvement and brain functional and structural improvements as evident by the brain imaging, substantiates the clinical findings. In addition, the unexpected recovery of memories and accompanied distress during the second half of the treatment course, strongly point to HBOT’s direct biological effects on this cohort of PTSD patients.

To conclude

This prospective randomized controlled trial demonstrates that HBOT can induce neuroplasticity and improve PTSD related symptoms of veterans suffering for treatment resistant PTSD. HBOT improved both the brain function and brain microstructure in regions typically involved in PTSD pathogenesis. The correlation between the clinical improvement and the changes in the brain functionality and microstructure can shed additional important light on the biology responsible for treatment resistant PTSD.

CONSORT 2010 checklist of information to include when reporting a randomised trial*.

(DOC)

Click here for additional data file.

Scatter plot of the correlations between percent change in total CAPS Score and the percent change in BDI and BSI questionnaires scores.

r is Pearson’s correlation coefficient, p < 0.0004 for all comparisons.

(TIF)

Click here for additional data file.

Scatter plot of the relative percent BOLD signal change in peak significantly activated regions, and the percent change in total CAPS score.

r is Pearson’s correlation coefficient, p < 0.05 for all comparisons.

(TIF)

Click here for additional data file.

Questionnaire scores paired box plot.

(TIF)

Click here for additional data file.

Total CAPS score repeated measures ANOVA.

(DOCX)

Click here for additional data file.

Questionnaire repeated measures ANOVA.

(DOCX)

Click here for additional data file.

(XLSX)

Click here for additional data file.

(PDF)

Click here for additional data file.

5 Nov 2021

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

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Senior Editor

PLOS ONE

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We are grateful to Prof. Rachel Lev-Wiesel, (The Emili Sagol University of Haifa, Israel CAT Research Center). Yair Bechor PhD, Yonathan Zemel, Katia Adler, Dr.  Erez, Lang, Dr. Shachar Fynci, Dr. Nir Poliak, Dr. Gregory Fishlev, Dr. Mony Fridman, Moran Adler, Or Nagauker, Rahav  Boussi-Gross, Ido May-Raz and Gil Suzin (Sagol Center for hyperbaric medicine), Merav Ben Yosef, Galina Sakliarvski (Department of radiology) and Revital Ozeri (Beit Halochem) for their participation in treatment monitoring, data acquisition and  medical support. We thank Hadas Okon-Zinger (Department of Psychology, University of Haifa, Haifa, Israel) for her consultation regarding fMRI tasks. We would also like to thank all the patients for their motivation, cooperation, and confidence."

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Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: No

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

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Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: This is an excellent paper on a important topic. It is well written and the conclusions are sound. The groups are clearly define, as well as the diagnosis and treatment methods. It is also easy to understand. It provides a new way to address PTSD by optimizing brain function.

Reviewer #2: I thank the authors for the opportunity to review the reporting of their important research study. While I found the manuscript generally well written and concise, clarification of a couple of things could improve the quality and scientific impact of the paper in the field.

1) On page 11, it’s not clear why prescribed cannabis (mean grams/month) is reported differently than the other prescribed medication (number of patients (% of group)). The reader is left wondering what number and percentage in each group were using prescribed cannabis during the study.

2) On page 16, line 28, the authors write: "One of the interesting findings in the current study, was the surfacing of unaccusable memories in half of the patients from the HBOT group." If the adjective "unaccusable" (not charged with wrongdoing) used here was intended to convey psychological meaning regarding the nature of previously "inaccessible" memories, then "unaccusable memories" should be operationally defined here. Moreover, since this phenomenon occurred in half those receiving treatment (n=7?) and this has only been reported once previously in the literature, this could be an important psychological predicter of therapeutic response that deserves further quantitative and qualitative analysis and discussion, especially in regards to maximizing psychological interventions for PTSD. For example, quantitatively, did those who experienced these repressed memories differ on clinical outcome measures from those who didn’t experience them within the HBOT treatment group? Were any time course patterns observed in regards to when these repressed memories began to emerge following the start of treatment? For example, in the previous fibromyalgia HBOT study cited by the authors, time course information was only provided for two of the nine patients, with reemergence of repressed memories occurring between HBOT days 17 and 34 in one and HBOT days 37 and 44 in the second patient. It would also be of interest to provide more information regarding the qualitative nature of these repressed memories and how they resolved psychotherapeutically. For example, the authors should consider providing a brief and concise clinical vignette on one or more of these 7 PTSD patients as illustrative examples as was provided in the previous fibromyalgia HBOT study.

Reviewer #3: 1. Sample size determination is not acceptable. Need to add more details, e.g. effect size.

2. Data analysis section needs more work. Be consistent with the statistical terms. Just use “Repeated ANOVA” instead of “within-subject RM ANOVA ” or “mixed design RM ANOVA”. Two names were used for p value correction also: “sequence Hochberg” and “FDR (Figure 4)”, use one.

What method was used if the data does not follow normal distribution?

What is the “net effect size”?

Page 9 line 6 the sentence “univariate analyses were performed … significant variables” can be omitted. It does not seem that you performed univariable or multivariable analyses.

3. Results:

For RM ANOVA, it is not meaningful to show a significant interaction. For each outcome, better show at least three p values and mean differences (with 95% confidence intervals) for the following tests: 1) pre-post test within the treatment group, 2) pre-post test within the control group, 3) a comparison of pre-post change between the treatment and control group. The p value and mean difference (95%) for pre-post change between the two groups should be shown in Table 2 and 3.

Need to test normality for RM ANOVA.

Bonferroni not mentioned in method but not in the results.

Page 17 line 6 “affect” instead of “effect”

**********

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

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17 Nov 2021

Reply to Review Comments to the Author

Reviewer #1:

This is an excellent paper on a important topic. It is well written and the conclusions are sound. The groups are clearly define, as well as the diagnosis and treatment methods. It is also easy to understand. It provides a new way to address PTSD by optimizing brain function.

Reply: we thank the reviewer for his support.

Reviewer #2:

I thank the authors for the opportunity to review the reporting of their important research study. While I found the manuscript generally well written and concise, clarification of a couple of things could improve the quality and scientific impact of the paper in the field.

Comment 1: “On page 11, it’s not clear why prescribed cannabis (mean grams/month) is reported differently than the other prescribed medication (number of patients (% of group)). The reader is left wondering what number and percentage in each group were using prescribed cannabis during the study”.

Reply: The number and percentage of patients using cannabis in each group were added to table 1.

Comment 2: “On page 16, line 28, the authors write: "One of the interesting findings in the current study, was the surfacing of unaccusable memories in half of the patients from the HBOT group." If the adjective "unaccusable" (not charged with wrongdoing) used here was intended to convey psychological meaning regarding the nature of previously "inaccessible" memories, then "unaccusable memories" should be operationally defined here.”

Reply: Thank you for the comment. The term “unaccusable memories” was replaced by the more appropriate term “inaccessible memories”.

Comment 3: “since this phenomenon occurred in half those receiving treatment (n=7?) and this has only been reported once previously in the literature, this could be an important psychological predicter of therapeutic response that deserves further quantitative and qualitative analysis and discussion, especially in regards to maximizing psychological interventions for PTSD. For example, quantitatively, did those who experienced these repressed memories differ on clinical outcome measures from those who didn’t experience them within the HBOT treatment group? Were any time course patterns observed in regards to when these repressed memories began to emerge following the start of treatment? For example, in the previous fibromyalgia HBOT study cited by the authors, time course information was only provided for two of the nine patients, with reemergence of repressed memories occurring between HBOT days 17 and 34 in one and HBOT days 37 and 44 in the second patient. It would also be of interest to provide more information regarding the qualitative nature of these repressed memories and how they resolved psychotherapeutically. For example, the authors should consider providing a brief and concise clinical vignette on one or more of these 7 PTSD patients as illustrative examples as was provided in the previous fibromyalgia HBOT study.”

Reply: Additional data regarding the time and pattern of the reported memories was added to the results section of the revised manuscript.

The surfacing of the repressed memories was not anticipated prior to the study so no intentional questioning and monitoring of this phenomenon was done as part of the study protocol. Since it might be possible that other participants had recovery of memories and did not report it, we cannot use the current data for additional conclusions on the psychological meaning of this effect.

we agree that the surfacing memories has the potential to serve as a psychological predictor of therapeutic response and it indeed deserves further quantitative and qualitative analysis. Accordingly, our next study will include in depth evaluation and actively monitored of all participants with multiple aspects related to their memory.

Reviewer #3:

Comment 1: “Sample size determination is not acceptable. Need to add more details, e.g. effect size.

Replay: Data related to sample size calculation based on effect size was added to the Statistical analysis - Sample size section.

Comment 2: “Data analysis section needs more work. Be consistent with the statistical terms. Just use “Repeated ANOVA” instead of “within-subject RM ANOVA ” or “mixed design RM ANOVA”. Two names were used for p value correction also: “sequence Hochberg” and “FDR (Figure 4)”, use one.

Replay: Thank you for this comment. The ANOVA and the multiple comparisons methods were not described clearly enough. A mixed-model repeated-measure ANOVA was performed to compare post-treatment and pre-treatment data. The model included time, group and the group-by-time interaction (detailed results are presented in Supporting Tables SI-1, SI-2).

Brain imaging parametric maps were corrected using the Benjamini–Hochberg False Discovery Rate (FDR) method (ref. 22 in the revised manuscript). Group-by-time interaction imaging analysis was corrected using the sequential Hochberg correction (ref. 23 in the revised manuscript).

The data analysis section was revised accordingly.

Comment 3: “What method was used if the data does not follow normal distribution?”

Replay: In this study, all continuous data were tested by the Kolmogorov-Smirnov test and found to be normally distributed.

Comment 4: “What is the “net effect size”?”

Replay: Net effect size is the relative Cohen’s d effect size, defined as the improvement from baseline after HBOT minus control three months improvement divided by the pooled standard deviation (SD) of the composite score. Positive effect sizes indicate improvement. An explanation was added to the statistical analysis section.

Comment 5: “Page 9 line 6 the sentence “univariate analyses were performed … significant variables” can be omitted. It does not seem that you performed univariable or multivariable analyses.”

Replay: This was referred to the categorical data, and corrected in the revised manuscript.

Comment 6: “Results - For RM ANOVA, it is not meaningful to show a significant interaction. For each outcome, better show at least three p values and mean differences (with 95% confidence intervals) for the following tests: 1) pre-post test within the treatment group, 2) pre-post test within the control group, 3) a comparison of pre-post change between the treatment and control group. The p value and mean difference (95%) for pre-post change between the two groups should be shown in Table 2 and 3.”

Replay: The group-by-time interaction ANOVA method is a common method for demonstrating outcomes between groups controlling for time. However, we also added p-values and mean differences with 95% confidence intervals, as suggested (Tables 2 and 3).

Comment 7: “Need to test normality for RM ANOVA. Bonferroni not mentioned in method but not in the results.”

Replay: Indeed, RM ANOVA model is valid for normally distributed data. All continuous data in this study were normally distributed.

Non-imaging data was corrected for multiple comparisons using the Bonferroni correction. Marked and added to Tables 2 and 3.

Comment 8: “Page 17 line 6 “affect” instead of “effect””

Replay: Done.

Submitted filename: PONE-D-20-34405 rebuttal letter.docx

Click here for additional data file.

19 Jan 2022

Hyperbaric oxygen therapy improves symptoms, brain's microstructure and functionality in veterans with treatment resistant post-traumatic stress disorder: a prospective, randomized, controlled trial.

PLOS ONE

Dear Dr. Doenyas,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

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Burak Yulug

Academic Editor

PLOS ONE

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Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments (if provided):

This is an interesting paper indicating the therapeutic role of HBOT on PTSD associated with relevant changes in the brain network and microstructure. Although the authors responded well to the reviewers' recommendation, I think that more detail regarding the cognitive baseline data of the patients should be included in the main text. For instance, were all patients cognitively homogeneously distributed in this respect, which could be critical in affecting both the clinical and imaging data. More relevant data regarding the questions should be provided in the main text since cognitive status could be game-changer in such clinical neuroimaging studies: What is the dementia/cognitive impairment threshold of MindStream. Why the authors did not use MMSE which is widely used for dementia exclusion.

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Reviewer #3: All comments have been addressed

**********

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Reviewer #3: (No Response)

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #3: (No Response)

**********

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Reviewer #3: (No Response)

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Reviewer #3: (No Response)

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