Good Visual Outcomes After Pituitary Tumor Surgery Are Associated With Increased Visual Cortex Functional Connectivity

Patients presenting with visual impairment secondary to pituitary macroadenomas often experience variable recovery after surgery. Several factors may impact visual outcomes including the extent of neuroaxonal dam- age in the afferent visual pathway and cortical plasticity. Optical coherence tomography (OCT) measures of retinal structure and resting-state functional MRI (rsfMRI) can be used to evaluate the impact of neuroaxonal injury and cor- tical adaptive processes, respectively. The purpose of this study was to determine whether rsfMRI patterns of func- tional connectivity (FC) distinguish patients with good vs poor visual outcomes after surgical decompression of pituitary adenomas.

Original Contribution Section Editors: Clare Fraser, MD Susan Mollan, MD Good Visual Outcomes After Pituitary Tumor Surgery Are Associated With Increased Visual Cortex Functional Connectivity Stefan T. Lang, MD, Won Hyung A. Ryu, MD, MSc, MTM, Yves P. Starreveld, MD, PhD, Fiona E. Costello, MD, the PITNET Study Group Background: Patients presenting with visual impairment secondary to pituitary macroadenomas often experience variable recovery after surgery. Several factors may impact visual outcomes including the extent of neuroaxonal damage in the afferent visual pathway and cortical plasticity. Optical coherence tomography (OCT) measures of retinal structure and resting-state functional MRI (rsfMRI) can be used to evaluate the impact of neuroaxonal injury and cortical adaptive processes, respectively. The purpose of this study was to determine whether rsfMRI patterns of functional connectivity (FC) distinguish patients with good vs poor visual outcomes after surgical decompression of pituitary adenomas. Methods: In this retrospective cohort study, we compared FC patterns between patients who manifested good (GO) vs poor (PO) visual outcomes after pituitary tumor surgery. Patients (n = 21) underwent postoperative rsfMRI a minimum of 1 year after tumor surgery. Seed-based connectivity of the visual cortex (primary [V1], prestriate [V2], and extrastriate [V5]) was compared between GO and PO patients and between patients and healthy controls (HCs) (n = 19). Demographics, visual function, and OCT data were compared preoperatively and postoperatively between Division of Neurosurgery (STL, WHAR, YPS), Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, Canada; Division of Ophthalmology (FEC), Department of Surgery, Cumming School of Medicine, University of Calgary, Calgary, Canada; Division of Neurology (FEC), Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, Canada; Department of Neurological Surgery (WHAR), Rush University, Chicago, IL; and Hotchkiss Brain Institute (STL, FEC), University of Calgary, Calgary, Canada. Supported by the Hotchkiss Brain Institute Pilot Research Fund Program. The authors report no conflicts of interest. Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s Web site (www. jneuro-ophthalmology.com). S. Lang and W. H. A. Ryu contributed equally. Address correspondence to Fiona Costello, MD, Foothills Medical Centre, 12th Floor, 1403—29th Street NW, Calgary, Alberta T2N 2T9, Canada; E-mail: fi[e-mail] 504 patient groups. The threshold for GO was visual field mean deviation equal or less than 25.00 dB and/or visual acuity equal to or better than 20/40. Results: Increased postoperative FC of the visual system was noted for GO relative to PO patients. Specifically, good visual outcomes were associated with increased connectivity of right V5 to the bilateral frontal cortices. Compared with HCs, GO patients showed increased connectivity of V1 and left V2 to sensorimotor cortex, increased connectivity of right and left V2 to medial prefrontal cortex, and increased connectivity of right V5 the right temporal and frontal cortices. Conclusions: Increased visual cortex connectivity is associated with good visual outcomes in patients with pituitary tumor, at late phase of recovery. Our findings suggest that rsfMRI does distinguish GO and PO patients after pituitary tumor surgery. This imaging modality may have a future role in characterizing the impact of cortical adaptation on visual recovery. Journal of Neuro-Ophthalmology 2021;41:504–511 doi: 10.1097/WNO.0000000000001155 © 2020 by North American Neuro-Ophthalmology Society V ision loss is a known complication of pituitary macroadenomas. Surgical decompression is performed with the goals of maintaining and restoring visual function. Yet, the timing and extent of postoperative visual recovery varies between patients (1–4). Kerrison identified an “early fast phase” of visual recovery that occurs within 1 week of surgery, an “early slow phase” that manifests within 1–4 months, and a “late phase” of visual recovery that occurs from 6 months to 3 years (2). Factors that contribute to visual recovery phases may include remyelination, neuroaxonal remodeling, and cortical plasticity (1–3,5–9). Resting-state functional MRI (rsfMRI) is an advanced functional imaging technique that permits quantification of statistical relationships between the spontaneous time courses of the blood oxygen level dependent (BOLD) signal from discrete regions of the brain, known as functional Lang et al: J Neuro-Ophthalmol 2021; 41: 504-511 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. Original Contribution connectivity (FC) (10). Several rsfMRI reports have shown that FC changes coincide with visual impairment in patients with chiasmal compression from pituitary tumors (See Supplemental Digital Content 1, Table E1, http://links.lww. com/WNO/A450) (6–9). Yet, interpreting findings from these observational reports has been challenging because of differences in patient populations, study design, characterization of visual outcomes, and imaging protocols (5–9). The primary goal of this study was to determine whether rsfMRI could detect differences in FC between good (GO) and poor (PO) postoperative visual outcomes in patients with pituitary tumor, at a late phase of recovery to patients with pituitary tumors. METHODS Study Design and Patient Selection This retrospective cohort study was approved by the University of Calgary Conjoint Research Ethics Board. All participating patients provided informed written consent. Charts of nonsecreting pituitary macroadenoma patients presenting with functional decline in their vision between January 2010 and December 2017 were reviewed. Inclusion criteria were (1) new radiological diagnosis of pituitary tumor, (2) preoperative visual field loss consistent with chiasmal syndrome, (3) preoperative and postoperative ophthalmic assessments, and (4) ability to provide informed written consent. Exclusion criteria included previous cranial radiation therapy, underlying reasons for cognitive impairment that could influence rsfMRI measures (11), amblyopia, and unrelated optic nerve/retinal pathology. Study Subjects Twenty-two patients (44 eyes) with pituitary adenomas were recruited. All patients underwent preoperative and postoperative visual testing (4 weeks after surgery and at the time of rsfMRI scanning). Data from 20 age-matched and sex-matched healthy controls (HCs) were used for rsfMRI comparisons. These subjects were evaluated on the same scanner, with the same parameters, as the patient group. One patient and one HC were excluded because of significant MRI artifact, resulting in 21 patients and 19 HCs. Optical Coherence Tomography Testing Retinal imaging was performed with Cirrus HD-OCT (model 4000, software V.6.0; Carl Zeiss Meditec, Jena, Germany). The peripapillary mean retinal nerve fiber layer (pRNFL) thicknesses were obtained using the Optic Disc 200 · 200 protocol. Macular assessments were performed with the Macular Cube 200 · 200 scan. The Ganglion Layer Analysis software was used to evaluate the ganglion cell–inner plexiform layer (mGCIPL) thickness. Only studies with good fixation, a circular scan centered on the Lang et al: J Neuro-Ophthalmol 2021; 41: 504-511 nerve head, and a signal strength $7 of 10 were included. Preoperative OCT was not performed in 6 patients (27%), but all 22 patients had postoperative OCT data. Neuro-Ophthalmic Assessment Neuro-ophthalmic assessments included best-corrected logMAR Snellen visual acuity (VA) and visual field mean deviation (VFMD) in decibels (dB) determined with automated perimetry using the Central 30-2 Threshold strategy. Standard automated visual field test results were used if the false-positive and false-negative errors measured less than 33% and fixation losses measured less than 20%. Postoperative patients were categorized as demonstrating either GO (VFMD # 25.00 dB and/or VA # 20/40) (12) or PO (patients with worse visual outcomes). Magnetic Resonance Imaging Protocol Patients underwent MRI testing a minimum of 1 year after surgery, using a 3.0 T GE Discovery MR750 whole-body scanner with a receive-only, 12-channel, phased-array head coil (GE Healthcare, Waukesha, WI). Participants were asked to remain awake and still with their eyes closed. Resting-state fMRI was collected for 2 runs of 5 minutes using a gradient-recalled echo, echo planar imaging sequence (voxel dimensions 3.75 · 3.75 · 4 mm, 30 slices, 64 · 64 matrix, TE = 30 milliseconds, TR = 2,000 milliseconds, and flip angle = 70). HC subjects underwent one run of the same scanning protocol. Resting-State Preprocessing All subjects underwent standard preprocessing (performed by an interpreting physician blinded to status of the study participant) in SPM12, including realignment, slice-time correction, and segmentation into gray matter, white matter, and cerebrospinal fluid (CSF) components using SPMs Unified Segmentation (13). Images were directly (nonlinearly) normalized to Montreal Neurological Institute (MNI) space using an echo planar imaging template (14). Denoising was performed in the software Conn (15). This included regression of 6 movement parameters and their first temporal derivatives and implementation of CompCor (16) by performing principal component analysis on eroded white matter and CSF masks with regression of the first 5 components. Volumes with large (.0.9 mm) frame-wise displacement or global signal change (.5 SD) were also included as covariates of no interest. Linear detrending was performed to remove signal drift, and high frequency noise was excluded by subjecting the residual signal to a band pass filter (.0.008–0.09 Hz). Seed-Based Connectivity Analysis Ten millimeter spherical regions of interest (ROIs) were placed in the visual cortex, corresponding to primary visual (V1), right and left prestriate (V2), as well as right and left extrastriate (V5) cortex (Fig. 1). The denoised spontaneous 505 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. Original Contribution FIG. 1. Visual cortex regions of interest (MNI coordinates [x, y, z]: V1 = 0, 290.5, 22; right V2 = +13.5, 280, 217.5; right V5 = +41.5, 273, 24; left V2 = 213.5, 280, 217.5; left V5 = 241.5, 273, 24). BOLD time course was averaged among the voxels within each ROI. Functional connectivity of each ROI across the whole brain was assessed by correlating the average BOLD time course on a voxel-wide scale with Pearson’s correlation. To improve normality, a Fisher Z transformation was performed. Statistical Analyses Descriptive statistics were performed comparing demographic, visual, and structural imaging data between GO and PO patients. Comparative analyses were performed using the unpaired t test for continuous variables, the Mann–Whitney U test for nonparametric variables, and the Fisher exact test for categorical variables. Post hoc analysis using the paired t test was used to compare the postoperative (Week 4 to rsfMRI scan time) visual data for GO and PO groups. For the comparative analyses, a P value less than 0.05 was set as statistically significant. The connectivity of each ROI was assessed on a voxel-wide basis with a two-sample t test, assessing for differences in connectivity between groups. The patient comparison was adjusted for age and length of time between surgery and rsfMRI scanning. Correction for multiple comparisons was performed using a cluster-based method as implemented in Conn (17). This was implemented with a voxel threshold of P , 0.005 (uncorrected), followed by a cluster threshold of P , 0.05 with a false discovery rate correction. The 3 separate contrasts included GO vs PO patients, GO vs HC, and PO vs HC. RESULTS Patient Demographics, Clinical Features, and Visual Outcomes The clinical features, visual findings, and demographic details are presented in Table 1. Preoperatively, there were no significant differences in visual function between the GO and PO groups, whereas pRNFL values were significantly higher in the GO group. Four weeks after surgery, VA and VFMD were significantly better in GO relative to PO patients. The OCT measured pRNFL and mGCIPL measures were higher in the GO group at all postoperative time points. In the GO group, 506 right eye VFMD values improved (P = 0.0364), whereas pRNFL values declined between postoperative follow-up points (P = 0.0120 and P = 0.0442 for the left and right eyes, respectively). No significant postoperative changes, from 4 weeks to the time of rsfMRI scanning, were observed with respect to visual function or OCT measurements in the PO group. Seed-Based Functional Connectivity: Good Outcome vs Poor Outcome There was no difference in FC of V1 or right V2 between the GO and PO patient groups (Fig. 2A, D). PO patients demonstrated decreased connectivity of right V5 with clusters spanning the bilateral frontal operculum and posterior insula (Fig. 2G). Connectivity values from significant clusters were extracted and displayed for visualization purposes in Figure 3. Details for each significant cluster, including MNI coordinates, size, and peak P values, are displayed in Table 2. There were no significant effects from the leftsided ROIs. Seed-Based Functional Connectivity: Patients vs Healthy Controls To determine whether the decreased connectivity observed in the PO vs GO patient contrast was driven by an actual decrease in the PO group or by an increase in FC in the GO group, we compared both patient groups to HCs. This analysis revealed decreased FC of left V2 to several clusters in the bilateral cerebellum and bilateral occipital cortex, along with a cluster of increased FC to the subcallosal cortex (Fig. 2K, Table 3). No differences in FC were observed between the PO group and HCs for any of the other visual cortex ROIs at the specified statistical threshold. By contrast, increased FC of V1 and left V2 to bilateral precentral and postcentral gyrus (Fig. 2C, L), increased FC of right and left V2 to the medial prefrontal cortex (Fig. 2F, L), and increased FC of right V5 to right temporal regions (including a cluster spanning into the frontal operculum [Fig. 2I]), distinguished GO patients from HCs. This latter cluster partially overlapped with the cluster in the right frontal operculum seen in the “PO . GO group,” suggesting that the PO vs GO finding resulted from an increase in connectivity in the GO group. Cluster location and significance for Lang et al: J Neuro-Ophthalmol 2021; 41: 504-511 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. Original Contribution TABLE 1. Patient demographics, clinical characteristics, and visual outcomes Age (years ±SD) Gender (F:M) Time from surgery to resting-state functional MRI scan (days ± SD) Extent of tumor resection Surgical complications Preoperative assessment LogMar VA OS ± SD (OD ± SD) Poor Outcome (n =7) Good Outcome (n = 15) P Value 59.9 ± 7.73 1:6 1,870 ± 863 (range 651–3,109) Subtotal:3; total: 4 None: 7 53.8 ± 12.17 6:9 1,452 ± 949 (range 394–2,290) Subtotal: 12; total: 3 None: 13; CSF leak: 2 0.24 0.35 0.33 VFMD OS ± SD (OD ± SD), dB RNFL OS ± SD (OD ± SD), mm GCIP layer* Postoperative assessment at 4-week follow-up LogMAR VA OS ± SD (OD ± SD) VFMD OS ± SD (OD ± SD), dB RNFL OS ± SD (OD ± SD), mm GCIP OS ± SD (OD ± SD) Postoperative assessment at resting state functional MRI scan LogMAR VA OS ± SD (OD ± SD) VFMD OS ± SD (OD ± SD), dB RNFL OS ± SD (OD ± SD), mm GCIP OS ± SD (OD ± SD) 0.43 ± 0.52 (0.24 ± 0.48) 211.01 ± 7.32 (210.90 ± 12.95) 68.20 ± 5.40 (71.80 ± 14.31) NA 0.23 ± 0.35 (0.21 ± 0.34) 212.21 ± 9.88 (28.98 ± 7.01) 82.55 ± 13.31 (86.64 ± 13.27) NA 0.21 ± 0.27 (0.41 ± 0.61) 210.62 ± 9.25 (213.74 ± 11.50) 67.9 ± 8.05 (63.1 ± 10.38) 58.7 ± 8.24 (54.4 ± 6.16) 0.05 ± 0.07 (0.05 ± 0.08) 21.67 ± 2.10 (21.25 ± 1.15) 81.7 ± 13.69 (84.2 ± 13.36) 68.3 ± 7.82 (72.1 ± 9.38) 0.09 ± 0.18 (0.53 ± 0.56) 28.04 ± 5.37 (213.53 ± 13.23) 67.71 ± 6.52 (59.86 ± 6.94) 58.8 ± 8.17 (53.43 ± 4.79) 0.06 ± 0.07 (0.03 ± 0.04) 21.53 ± 1.56 (20.96 ± 1.28) 78.27 ± 11.60 (82.33 ± 12.46) 68.87 ± 7.95 (70.80 ± 8.81) 0.14 0.16 (0.42) 0.83 (0.73) 0.031 (0.019) NA 0.036 (0.031) 0.002 (0.001) 0.023 (0.001) 0.016 (0.0002) 0.26 (0.001) 0.0003 (0.001) 0.019 (0.0003) 0.013 (0.0001) dB, decibels; F, female; FDR, false discovery rate; GCIP, ganglion cell–inner plexiform layer; logMAR, logarithm of the minimum angle of resolution; M, male; OD, right eye; OS, left eye; RNFL, retinal nerve fiber layer; SD, standard deviation; VA, visual acuity; VFDM, visual field mean deviation. Bold entry = Statistically significant at P , 0.05. *Defines analyses were not performed due to missing data this analysis can be found in Table 4. Repeating the above analysis with only one run of patient data resulted in qualitatively similar results. DISCUSSION Resting-state fMRI has been used to explore the impact of cortical plasticity on recovery from visual pathway lesions (18– 26). Multiple sclerosis patients with optic neuritis (ON) have shown increased FC in the extrastriate cortex and decreased FC at the level of the right inferior peristriate cortex, relative to those without ON (20). Huang (21) demonstrated lowerfrequency fluctuation rsfMRI measures in the default mode network (DMN) of ON patients and higher measures in the right inferior temporal gyrus and left inferior parietal lobule. Lang et al: J Neuro-Ophthalmol 2021; 41: 504-511 Thus, visual recovery after ON may be associated with cortical reorganization in extrastriate areas and compensatory responses within the DMN (20,21). Likewise, in glaucoma subjects, studies have revealed disrupted FC between the primary and higher visual cortex and between visual cortex and associative visual areas (26). Although rsfMRI studies in patients with pituitary tumors have been relatively few in number, decreased FC of the visual cortex has been a consistent finding (6–9). Song (8) compared connectivity patterns between 25 patients with pituitary tumor and 25 HCs and noted decreased FC between vision-related and higher-order cognitive brain areas. In a similar study, Qian (6) described “neural dysfunction” in the visual cortex of patients with pituitary tumor compared with HCs; yet, increased FC was noted between the pulvinar region and the middle temporal and secondary visual cortices. 507 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. Original Contribution FIG. 2. Connectivity of visual regions of interest compared across groups (visualized at T . 2.5 and T , 22.5; Arrows points at significant clusters found at P , 0.005, cluster P , 0.05 FDR). GO, good outcome; HC, healthy control; L, left; PO, poor outcome; R, right. FDR, false discovery rate. Different from the current report, however, these studies evaluated patients with pituitary tumor before surgical intervention. Recently, Qian (7) studied 10 patients with rsfMRI before and after surgical resection and observed increased postoperative neural activity within the visual cortex. Postoperative neural activity was, however, decreased in subareas of the multisensory and multimodal systems beyond the visual cortex. Ying (9) assessed 13 patients before and after resection and noted increased FC of the visual cortex in patients with postoperative visual recovery. These 2 reports had limited followup (1–3 months) and included only patients with visual improvement. We therefore extend the findings of the pub- lished literature, by comparing rsfMRI findings between patients with pituitary tumors with good and poor postoperative visual outcomes. We chose 5 ROIs representing different cortical hierarchies present in the visual cortex (19). The connectivity of each of these ROIs was evaluated across the entire brain and subsequently compared between patients and HCs. Poor outcome patients had reduced connectivity of V5 to regions of the frontal cortex compared with GO patients and decreased connectivity of left V2 to clusters in the cerebellum and occipital cortex relative to HCs. Patients with good postoperative outcomes showed increased connectivity of FIG. 3. Connectivity values extracted from significant clusters in the right and left frontal operculum for the poor outcome (PO) vs good outcome (GO) contrast. 508 Lang et al: J Neuro-Ophthalmol 2021; 41: 504-511 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. Original Contribution TABLE 2. Cluster location and significance Visual Regions of Interest Right V5 Right V5 Cluster Location Right frontal/central operculum, Heschl’s gyrus, and posterior insula Left frontal/central operculum, Heschl’s gyrus, and posterior insula MNI Coordinate (x, y, z) Cluster Size Peak P (Uncorrected) Size P (FDR Correction) +30, 220, +04 223 0.000079 0.029154 250, 218, +08 194 0.000117 0.030451 Good outcome vs poor outcome. FDR, false discovery rate. V1 and left V2 to the sensorimotor cortex (precentral and postcentral gyrus), right and left V2 to the medial prefrontal cortex, and right V5 to right frontal and temporal regions, relative to HCs. The increased FC of right V5 to temporal regions in the GO group was consistent with the observations of Ying (9), who described increased FC between the left V5 and other brain regions at both the ROI level and the whole-brain network level. Interestingly, V5 is often referred to as the “movement area,” responsible for visual motion perception and smooth pursuit movements (9). Activation of subcortical extrastriate pathways through V5 and the middle temporal area may therefore represent a compensatory adaptation that potentiates recovery in patients with pituitary tumors (6,9,27,28). Cortical plasticity may be viewed as the recruitment of activity by nearby healthy cortex to facilitate function (29). Yet, it remains unclear whether differences in visual cortex connectivity that distinguish patients with pituitary tumor with good vs poor surgical outcomes represent cortical adaptive responses or bystander effects of neuroaxonal changes in the afferent visual pathway. Specifically, we observed higher postoperative pRNFL and mGCIPL measures in GO patients, relative to their PO counterparts, consistent with previous studies (1,30–36). Analogously, anterior visual pathway structure–function relationships in patients with glaucoma have been characterized by a “broken-stick” model such that visual field loss is detectable only when thresholds of neuroaxonal injury have been breached (pRNFL = 76.9 mm; mGCIPL = 59.6 mm) (25). A similar relationship has been dem- onstrated between fMRI measures of visual cortex activity and visual field function, indicating that glaucomatous deterioration is already present in the eye and the brain before detectable vision loss (25). Correlations between posterior visual pathway neuroaxonal structural and visual function have likewise been demonstrated in patients with pituitary tumors, with diffusion tensor imaging (DTI) MRI studies. Specifically, DTI measures of preserved axonal integrity in the optic tracts are associated with better visual outcomes in patients with pituitary tumors (1,37–39). Similarly, the extent of DTI measured rarefaction of the optic radiations has been shown to correlate with measures of optic nerve atrophy, visual field loss, and cerebral glucose hypometabolism in the striate cortex of patients with glaucoma (25). Thus, in the setting of pituitary tumors, and other chronic optic neuropathies, elucidating the extent of neuroaxonal injury throughout the afferent visual pathway is germane to interpreting rsfMRI visual cortex connectivity findings. FC differences detected by rsfMRI distinguished PO and GO patients with pituitary tumor in this study. It would be speculative, however, to ascribe these differences to cortical plasticity, owing to several limitations. Specifically, our small sample size limited data analysis for univariate comparisons. Moreover, our retrospective evaluation was associated with missing data, which prevented statistical analysis of some clinical variables. Finally, our crosssectional design, including only a single postoperative scan per patient, impacted the interpretation of our rsfMRI TABLE 3. Cluster location and significance Visual Regions of Interest Left V2 Left Left Left Left V2 V2 V2 V2 Cluster Location Left occipital pole, left occipital pole, right intracalcarine cortex, and left intracalcarine cortex Left cerebellum Right cerebellum Left cerebellum Subcallosal cortex MNI Coordinate (x, y, z) Cluster Size Peak P (Uncorrected) Size P (FDR Correction) +18, 286, +06 694 0.000004 0.000344 232, 260, 250 +28,254, 232 230, 262, 224 206, +14, 214 560 349 342 221 0.000005 0.000006 0.000011 0.000020 0.000914 0.00868 0.00868 0.0469 Poor outcome vs healthy control. FDR, false discovery rate. Lang et al: J Neuro-Ophthalmol 2021; 41: 504-511 509 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. Original Contribution TABLE 4. Cluster location and significance Visual Regions of Interest V1 Right V2 Right V5 Right V5 Left V2 Left V2 Cluster Location Left precentral gyrus and left postcentral gyrus Medial prefrontal and paracingulate gyrus Right temporal pole and superior temporal gyrus Right middle temporal gyrus, central operculum, Heschl’s gyrus, and posterior insula Left postcentral gyrus, left precentral gyrus, right precentral, and right postcentral Medial prefrontal cortex MNI Coordinate (x, y, z) Cluster Size Peak P (Uncorrected) Size P (FDR Correction) 230, 220, +70 797 0.000008 0.000187 +08, +44, +00 363 0.000016 0.038940 +50, +04, 214 403 0.000016 0.025117 +60, 208, 208 530 0.000023 0.012360 +10, 220, +76 726 0.000048 0.00036 214, +46, 208 379 0.000006 0.0147 Good outcome vs healthy control. findings. Ideally, to better understand the relative contributions of remyelination, neuroaxonal remodeling, and cortical adaptive responses to visual recovery phases in patients with pituitary tumor, future rsfMRI studies should include detailed serial preoperative and postoperative evaluations. Furthermore, patients with both good and poor visual outcomes should be compared. Finally, DTI and OCT should be used to measure the extent of neuroaxonal and potentially transneuronal structural remodeling in the afferent visual pathway over time. In so doing, it may be possible to determine whether cortical changes precede or follow retinal ganglion cell neurodegeneration and discern how neuroplasticity contributes to visual recovery in patients with pituitary tumors. Ultimately, these insights may help facilitate the timing of surgical intervention, optimize visual recovery, and establish a future role for rsfMRI in predicting surgical outcomes for patients with pituitary tumor. 3. 4. 5. 6. 7. 8. STATEMENT OF AUTHORSHIP Category 1: a. Conception and design: F. Costello, W. H. A. Ryu, S. Lang, and Y. Starreveld; b. Acquisition of data: F. Costello, W. H. A. Ryu, S. Lang, and Y. Starreveld; c. Analysis and interpretation of data: F. Costello, W. H. A. Ryu, and S. Lang. Category 2: a. Drafting the manuscript: F. Costello, W. H. A. Ryu, S. Lang, and Y. Starreveld; b. Revising it for intellectual content: F. Costello, W. H. A. Ryu, and S. Lang. Category 3: a. Final approval of the completed manuscript: F. Costello, W. H. A. Ryu, S. Lang, and Y. Starreveld. 9. 10. 11. REFERENCES 1. Danesh-Meyer HV, Yoon JJ, Lawlor M, Savino P. Visual loss and recovery in chiasmal compression. Prog Retin Eye Res. 2019;73:100765. 2. Gnanalingham KK, Bhattacharjee S, Pennington R, Ng J, Mendoza N. The time course of visual field recovery following transphenoidal surgery for pituitary adenomas: predictive 510 12. 13. 14. factors for a good outcome. J Neurol Neurosurg Psychiatry. 2005;76:415–419. Kerrison JB, Lynn MJ, Baer CA, Newman SA, Biousse V, Newman NJ. Stages of improvement in visual fields after pituitary tumor resection. Am J Ophthalmol. 2000;130:813– 820. Aghi MK, Chen CC, Fleseriu M, Newman SA, Lucas JW, Kuo JS, Barkhoudarian G, Farrell CJ, Sheehan J, Ziu M, Dunn IF. Congress of neurological surgeons systematic review and evidence-based guidelines on the management of patients with nonfunctioning pituitary adenomas: executive summary. Neurosurgery. 2016;79:521–523. Chouinard PA, Striemer CL, Ryu WH, Sperandio I, Goodale MA, Nicolle DA, Rotenberg B, Duggal N. Retinotopic organization of the visual cortex before and after decompression of the optic chiasm in a patient with pituitary macroadenoma. J Neurosurg. 2012;117:218–224. Qian HY, Wang XC, Wang Z, Wang Z, Liu PN. Altered visionrelated resting-state activity in pituitary adenoma patients with visual damage. PLoS One. 2016;11:e0160119. Qian HY, Wang XC, Wang ZY, Wang ZM, Liu PN, Wang ZC. Changes in the vision-related resting-state network in pituitary adenoma patients after vision improvement. Chin Med J (Engl). 2015;128:1171–1176. Song G, Qiu J, Li C, Li J, Gui S, Zhu H, Zhang Y. Alterations of regional homogeneity and functional connectivity in pituitary adenoma patients with visual impairment. Sci Rep. 2017;7:13074. Ying J, Li C, Yuan T, Jin L, Wang R, Zuo Z, Zhang Y. Increased resting-state functional connectivity in suprasellar tumor patients with postoperative visual improvement. Int J Med Sci. 2019;16:1245–1253. Lang S, Duncan N, Northoff G. Resting-state functional magnetic resonance imaging: review of neurosurgical applications. Neurosurgery. 2014;74:453–455. Li HJ, Hou XH, Liu HH, Yue CL, He Y, Zuo XN. Toward systems neuroscience in mild cognitive impairment and Alzheimer’s disease: a meta-analysis of 75 fMRI studies. Hum Brain Mapp. 2015;36:1217–1232. Costello F, Coupland S, Hodge W, Lorello GR, Koroluk J, Pan YI, Freedman MS, Zackon DH, Kardon RH. Quantifying axonal loss after optic neuritis with optical coherence tomography. Ann Neurol. 2006;59:963–969. Ashburner J, Friston KJ. Unified segmentation. Neuroimage. 2005;26:839–851. Calhoun VD, Wager TD, Krishnan A, Rosch KS, Seymour KE, Nebel MB, Mostofsky SH, Nyalakanai P, Kiehl K. The impact of Lang et al: J Neuro-Ophthalmol 2021; 41: 504-511 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. Original Contribution 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. T1 versus EPI spatial normalization templates for fMRI data analyses. Hum Brain Mapp. 2017;38:5331–5342. Whitfield-Gabrieli S, Nieto-Castanon A. Conn: a functional connectivity toolbox for correlated and anticorrelated brain networks. Brain Connect. 2012;2:125–141. Behzadi Y, Restom K, Liau J, Liu TT. A component based noise correction method (CompCor) for BOLD and perfusion based fMRI. Neuroimage. 2007;37:90–101. Van Essen DC, Maunsell JH. Hierarchical organization and functional streams in the visual cortex. Trends Neurosci. 1983;6:370–375. Filippi M, Agosta F, Spinelli EG, Rocca MA. Imaging resting state brain function in multiple sclerosis. J Neurol. 2013;260:1709–1713. Dai H, Morelli JN, Ai F, Yin D, Hu C, Xu D, Li Y. Resting-state functional MRI: functional connectivity analysis of the visual cortex in primary open-angle glaucoma patients. Hum Brain Mapp. 2013;34:2455–2463. Gallo A, Esposito F, Sacco R, Docimo R, Bisecco A, Della Corte M, D’Ambrosio A, Corbo D, Rosa N, Lanza M, Cirillo S, Bonavita S, Tedeschi G. Visual resting-state network in relapsingremitting MS with and without previous optic neuritis. Neurology. 2012;79:1458–1465. Huang J, Duan Y, Liu S, Liang P, Ren Z, Gao Y, Liu Y, Zhang X, Lu J, Li K. Altered brain structure and functional connectivity of primary visual cortex in optic neuritis. Front Hum Neurosci. 2018;12:473. Backner Y, Ben-Shalom I, Kuchling J, Siebert N, Scheel M, Ruprecht K, Brandt A, Paul F, Levin N. Cortical topological network changes following optic neuritis. Neurol Neuroimmunol Neuroinflamm. 2020;7:e687. Wu GF, Brier MR, Parks CA, Ances BM, Van Stavern GP. An eye on brain integrity: acute optic neuritis affects resting state functional connectivity. Invest Ophthalmol Vis Sci. 2015;56:2541–2546. Shao Y, Cai FQ, Zhong YL, Huang X, Zhang Y, Hu PH, Pei CG, Zhou FQ, Zeng XJ. Altered intrinsic regional spontaneous brain activity in patients with optic neuritis: a resting-state functional magnetic resonance imaging study. Neuropsychiatr Dis Treat. 2015:11:3065–3073. Murphy MC, Conner IP, Teng CY, Lawrence JD, Safiullah Z, Wang B, Bilonick RA, Kim SG, Wollstein G, Schuman JS, Chan KC. Retinal structures and visual cortex activity are impaired prior to clinical vision loss in glaucoma. Sci Rep. 2016;6:31464. Nuzzi R, Dallorto L, Rolle T. Changes of visual pathway and brain connectivity in glaucoma: a systematic review. Front Neurosci. 2018;12:363. Rokszin A, Márkus Z, Braunitzer G, Berényi A, Benedek G, Nagy A. Visual pathways serving motion detection in the mammalian brain. Sensors (Basel). 2010;10:3218–3242. Lang et al: J Neuro-Ophthalmol 2021; 41: 504-511 28. Hadid V, Lepore F. From cortical blindness to conscious visual perception: theories on neuronal networks and visual training strategies. Front Syst Neurosci. 2017;11:64. 29. Urbanski M, Coubard OA, Bourlon C. Visualizing the blind brain: brain imaging of visual field defects from early recovery to rehabilitation techniques. Front Integr Neurosci. 2014;8:74. 30. Danesh-Meyer HV, Carroll SC, Foroozan R, Savino PJ, Fan J, Jiang Y, Hoorn SV. Relationship between retinal nerve fiber layer and visual field sensitivity as measured by optical coherence tomography in chiasmal compression. Invest Ophthalmol Vis Sci. 2006;47:4827–4835. 31. Danesh-Meyer HV, Papchenko T, Savino PJ, Law A, Evans J, Gamble GD. In vivo retinal nerve fiber layer thickness measured by optical coherence tomography predicts visual recovery after surgery for parachiasmal tumors. Inves Ophthalmol Vis Sci. 2008;49:1879–1885. 32. Danesh-Meyer HV, Wong A, Papchenko T, Matheos K, Stylli S, Nicols A, Frampton C, Daniell M, Savino PJ, Kaye AH. Optical coherence tomography predicts visual outcome for pituitary tumors 2015. J Clin Neurosci. 2015;22:1098–1104. 33. Moon CH, Hwang SC, Ohn YH, Park TK. The time course of visual field recovery and changes of retinal ganglion cells after optic chiasmal decompression. Invest Ophthalmol Vis Sci. 2011;52:7966–7973. 34. Yoneoka T, Hatase T, Watanabe N, Jinguji S, Okada M, Takagi M, Fujii Y. Early morphological recovery of the optic chiasm is associated with excellent visual outcome in patients with compressive chiasmal syndrome caused by pituitary tumors. Neurol Res. 2015;37:1–8. 35. Lee GI, Park KA, Son G, Kong DS, Oh SY. Optical coherence tomography analysis of inner and outer retinal layers in eyes with chiasmal compression caused by suprasellar tumours. Acta Ophthalmol. 2019;98:e373–e380. 36. Phal PM, Steward C, Nichols AD, Kokkinos C, Desmond PM, Danesh-Meyer H, Sufaro YZ, Kaye AH, Moffat BA. Assessment of optic pathway structure and function in patients with compression of the optic chiasm: a correlation with optical coherence tomography. Invest Ophthalmol Vis. 2016;57:3884–3890. 37. Anik I, Anik Y, Cabuk B, Caklili M, Pirhan D, Ozturk O, Cirak M, Ceylan S. Visual outcome of an endoscopic endonasal transsphenoidal approach in pituitary macroadenomas: quantitative assessment with diffusion tensor imaging early and long-term results. World Neurosurg. 2018;112:e691–e701. 38. Anik I, Anik Y, Koc K, Ceylan S, Genc H, Altintas O, Ozdamar D, Baykal Ceylan D. Evaluation of early visual recovery in pituitary macroadenomas after endoscopic endonasal transphenoidal surgery: quantitative assessment with diffusion tensor imaging (DTI). Acta Neurochir (Wien). 2011;153:831–842. 39. Paul DA, Gaffin-Cahn E, Hintz EB, Adeclat GJ, Zhu T, Williams ZR, Vates GE, Mahon BZ. White matter changes linked to visual recovery after nerve decompression. Sci Transl Med. 2014;6:266ra173. 511 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited.