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Computer-aided detection systems for retinal fluid could be beneficial for disease monitoring and management by chronic age-related macular degeneration (AMD) and diabetic retinopathy (DR) patients, to assist in disease prevention via early detection before the disease progresses to a "wet AMD" pathology or diabetic macular edema (DME), requiring treatment. We propose a proof-of-concept AI-based app to help predict fluid via a "fluid score", prevent fluid progression, and provide personalized, serial monitoring, in the context of predictive, preventive, and personalized medicine (PPPM) for patients at risk of retinal fluid complications.The app comprises a convolutional neural network-Vision Transformer (CNN-ViT)-based segmentation deep learning (DL) network, trained on a small dataset of 100 training images (augmented to 992 images) from the Singapore Epidemiology of Eye Diseases (SEED) study, together with a CNN-based classification network trained on 8497 images, that can detect fluid vs. non-fluid optical coherence tomography (OCT) scans. Both networks are validated on external datasets.Internal testing for our segmentation network produced an IoU score of 83.0% (95% CI = 76.7-89.3%) and a DICE score of 90.4% (86.3-94.4%); for external testing, we obtained an IoU score of 66.7% (63.5-70.0%) and a DICE score of 78.7% (76.0-81.4%). Internal testing of our classification network produced an area under the receiver operating characteristics curve (AUC) of 99.18%, and a Youden index threshold of 0.3806; for external testing, we obtained an AUC of 94.55%, and an accuracy of 94.98% and an F1 score of 85.73% with Youden index.We have developed an AI-based app with an alternative transformer-based segmentation algorithm that could potentially be applied in the clinic with a PPPM approach for serial monitoring, and could allow for the generation of retrospective data to research into the varied use of treatments for AMD and DR. The modular system of our app can be scaled to add more iterative features based on user feedback for more efficient monitoring. Further study and scaling up of the algorithm dataset could potentially boost its usability in a real-world clinical setting.The online version contains supplementary material available at 10.1007/s13167-022-00301-5.

Purpose:To develop a deep learning (DL)-based algorithm to predict the presence of stromal invasion of breast cancer on digital breast tomosynthesis (DBT).Materials and Methods:The institutional review board approved this retrospective study and waived the requisite to obtain the informed consent from the patients. Initially, 499 patients (mean age of 50.5 years, ranging from 29 to 90 years) who were referred to our hospital suggestive of breast cancer and performed DBT between March 1, 2019 and August 31, 2019, were enrolled in this study. Out of the 499 patients, 140 patients who were performed surgery with diagnosed breast cancer were finally selected. Based on the pathological reports, 140 patients were divided to be categorized as 20 patients with non-invasive cancer and 120 patients with invasive cancer. Xception architecture was used for the DL model to differentiate non-invasive cancer and invasive cancer. Diagnostic performance of the DL model was assessed by accuracy, sensitivity, specificity, and areas under the receiver operating characteristic curve (AUC).Results:The average accuracy, sensitivity, specificity, and AUC were 0.897, 0.909, 0.758, and 0.749, respectively.Conclusion:The proposed DL model trained on DBT images is useful to predict the presence of stromal invasion of breast cancer.Secondary abstractThe proposed deep learning (DL) model trained on digital breast tomosynthesis (DBT) images is useful to predict the presence of stromal invasion of breast cancer.

Purpose To describe the distribution and determinants of choroidal thickness (CT) in participants in a population study based on spectral-domain (SD)-OCT measurements. Design Population-based, cross-sectional study. Participants Ethnic Chinese, Indian, and Malay adults aged more than 50 years without any retinal diseases (e.g., diabetic retinopathy, macular edema, age-related macular degeneration, central serous chorioretinopathy) that might affect the CT were recruited from the Singapore Epidemiology of Eye Diseases Study. Methods Choroidal imaging was performed by SD-OCT (Spectralis, Heidelberg Engineering, Heidelberg, Germany) in enhanced depth imaging (EDI) mode. Subfoveal choroidal thickness (SFCT) was measured on the foveal line scan by 2 retinal experts independently (YS and KT), and the average was used in the analyses. In Chinese and Indian cohorts in whom macular raster scans were captured, the manufacturer-supplied research software (Heyex SP-X version 6.4.8.116; Heidelberg Engineering) was used to obtain automated segmentation yielding mean choroidal thickness in each of the 9 ETDRS grid sectors. Main Outcome Measures Subfoveal choroidal thickness and regional CT in the 9 ETDRS grid sectors. Results For the SFCT analysis, 2794 eyes of 1619 participants (Chinese, Indian, and Malay ) were included. The mean age was 60.9 years (standard deviation, 7.7), and 797 (49.2%) were male. Mean SFCT was 255.2 μm (standard deviation, 102.6). The normal range of SFCT was 106 to 447 μm (corresponding to 5th and 95th percentile limits of SFCT, respectively). In multivariable models, thinner SFCT was associated with older age, female gender, longer axial length, and Malay (vs. Chinese) ethnicity. In the subset of Chinese and Indian eyes (n = 1842) in whom regional variation was evaluated, the choroid was thickest at the superior and temporal sectors and thinner at the inferior and nasal sectors. Conclusions Subfoveal choroidal thickness is influenced by age, gender, and ethnicity along with regional differences even within individual eyes. Subfoveal choroidal thickness also shows a wide range in physiologic limits. These data may be used as a reference in future studies.

The purpose of this study was to develop a deep learning model to diagnose breast cancer by embedding a diagnostic algorithm that examines the asymmetry of bilateral breast tissue. This retrospective study was approved by the institutional review board. A total of 115 patients who underwent breast surgery and had pathologically confirmed breast cancer were enrolled in this study. Two image pairs [230 pairs of bilateral breast digital breast tomosynthesis (DBT) images with 115 malignant tumors and contralateral tissue (M/N), and 115 bilateral normal areas (N/N)] were generated from each patient enrolled in this study. The proposed deep learning model is called bilateral asymmetrical detection (BilAD), which is a modified convolutional neural network (CNN) model of Xception with two-dimensional tensors for bilateral breast images. BilAD was trained to classify the differences between pairs of M/N and N/N datasets. The results of the BilAD model were compared to those of the unilateral control CNN model (uCNN). The results of BilAD and the uCNN were as follows: accuracy, 0.84 and 0.75; sensitivity, 0.73 and 0.58; and specificity, 0.93 and 0.92, respectively. The mean area under the receiver operating characteristic curve of BilAD was significantly higher than that of the uCNN (p = 0.02): 0.90 and 0.84, respectively. The proposed deep learning model trained by embedding a diagnostic algorithm to examine the asymmetry of bilateral breast tissue improves the diagnostic accuracy for breast cancer.

Task-free functional connectivity in animal models provides an experimental framework to examine connectivity phenomena under controlled conditions and allows comparison with invasive or terminal procedures. To date, animal acquisitions are performed with varying protocols and analyses that hamper result comparison and integration. We introduce StandardRat, a consensus rat functional MRI acquisition protocol tested across 20 centers. To develop this protocol with optimized acquisition and processing parameters, we initially aggregated 65 functional imaging datasets acquired in rats from 46 centers. We developed a reproducible pipeline for the analysis of rat data acquired with diverse protocols and determined experimental and processing parameters associated with a more robust functional connectivity detection. We show that the standardized protocol enhances biologically plausible functional connectivity patterns, relative to pre-existing acquisitions. The protocol and processing pipeline described here are openly shared with the neuroimaging community to promote interoperability and cooperation towards tackling the most important challenges in neuroscience.

Purpose: To investigate the vasorelaxation effect of ripasudil (K-115), a novel Rho-associated coiled-coil-containing protein kinase (ROCK) inhibitor, on isolated retinal arterioles. We determined ...

Despite extensive efforts to increase the signal-to-noise ratio (SNR) of fMRI images for brain-wide mapping, technical advances of focal brain signal enhancement are lacking, in particular, for animal brain imaging. Emerging studies have combined fMRI with fiber optic-based optogenetics to decipher circuit-specific neuromodulation from meso to macroscales. Acquiring fMRI signal with high spatiotemporal resolution is needed to bridge cross-scale functional dynamics, but SNR of targeted cortical regions is a limiting factor. We have developed a multi-modal fMRI imaging platform with an implanted inductive coil detector. This detector boosts the tSNR of MRI images, showing a 2-3 fold sensitivity gain over conventional coil configuration. In contrast to the cryoprobe or array coils with limited spaces for implanted brain interface, this setup offers a unique advantage to study brain circuit connectivity with optogenetic stimulation and can be further extended to other multi-modal fMRI mapping schemes.

Purpose We aimed to explore the velocity waveform characteristics of the retinal artery associated with age and the cardio-ankle vascular index (CAVI) as a conventional arterial stiffness marker by applying the Doppler optical coherence tomography (DOCT) flowmeter. Methods In this cross-sectional study, DOCT flowmeter imaging was performed in 66 participants aged 21 to 83 years (17 men, 49 women) with no history of eye diseases and no systemic diseases, except for hypertension. Retinal blood velocity waveform was analyzed where several parameters in time (upstroke time, T1, T2, T3, and T4) and area under the waveform (area elevation, area declination, A1, A2, A3, and A4) were extracted. Systolic blood pressure-adjusted Pearson's coefficients were calculated to determine the correlations of each parameter with age or CAVI. Results Corrected upstroke time (UTc) was the waveform parameter most positively correlated with age (r = 0.497, P < 0.001). Area declination was the waveform parameter most negatively correlated with age (r = -0.682, P < 0.001) and CAVI (r = -0.601, P < 0.001). Conclusions We extracted the waveform parameters associated with the risks of arterial stiffening. The velocity waveform analysis of the retinal artery with DOCT flowmeter potentially could become a new method for arterial stiffness identification. Translational Relevance DOCT flowmeter could evaluate arterial stiffening in a different way from the conventional method of measuring arterial stiffening using pressure waveform. Because the DOCT flowmeter can easily, quickly, and noninvasively provide a retinal blood velocity waveform, this system could be useful as a routine medical examination for arterial stiffening.

The purpose of this study was to evaluate the diagnostic performance of retinal blood flow (RBF) measured with the Doppler optical coherence tomography (OCT) segmental scanning method to distinguish between healthy and glaucoma eyes.Fifty-eight patients with normal tension glaucoma (NTG) who had a single-hemifield visual field defect and 44 age-matched healthy subjects were enrolled. Retinal nerve fiber layer thickness (RNFLT) was measured with swept-source OCT. Superior and inferior temporal arteries (TAs) and temporal veins (TVs) RBF were measured with Doppler OCT. The area under the curve (AUC) of the receiver operating characteristic (ROC) was used to compare the diagnostic performances in the damaged and normal hemispheres.Multivariate regression analysis showed TA RBF and TV RBF were significantly reduced in the damaged and normal hemispheres. The ROC analysis showed that the AUC for quadrant RNFLT, TA RBF, and TV RBF were 0.973, 0.909, and 0.872 in the damaged hemisphere, respectively. The AUC values in the normal hemisphere were 0.783, 0.744, and 0.697, respectively. The combination of quadrant RNFLT and TA/TV RBF had a greater AUC than quadrant RNFLT alone in both damaged (AUC = 0.987) and normal (AUC = 0.825) hemispheres.In NTG eyes with single-hemifield damage, the RBF was found to be significantly reduced in the damaged and normal hemispheres independent from structural changes. The combination of RNFLT and RBF could improve diagnostic performances for glaucoma.Combining morphological and blood flow measurements with Doppler OCT may be useful in glaucoma diagnosis.

Pupil dynamics serve as a physiological indicator of cognitive processes and arousal states of the brain across a diverse range of behavioral experiments. Pupil diameter changes reflect brain state fluctuations driven by neuromodulatory systems. Resting-state fMRI (rs-fMRI) has been used to identify global patterns of neuronal correlation with pupil diameter changes; however, the linkage between distinct brain state-dependent activation patterns of neuromodulatory nuclei with pupil dynamics remains to be explored. Here, we identified four clusters of trials with unique activity patterns related to pupil diameter changes in anesthetized rat brains. Going beyond the typical rs-fMRI correlation analysis with pupil dynamics, we decomposed spatiotemporal patterns of rs-fMRI with principal component analysis (PCA) and characterized the cluster-specific pupil–fMRI relationships by optimizing the PCA component weighting via decoding methods. This work shows that pupil dynamics are tightly coupled with different neuromodulatory centers in different trials, presenting a novel PCA-based decoding method to study the brain state-dependent pupil–fMRI relationship.

BackgroundTo develop computer-aided detection (CADe) of ORL abnormalities in the retinal pigmented epithelium, interdigitation zone and ellipsoid zone via optical coherence tomography (OCT).MethodsIn this retrospective study, healthy participants with normal ORL, and patients with abnormality of ORL including choroidal neovascularisation (CNV) or retinitis pigmentosa (RP) were included. First, an automatic segmentation deep learning (DL) algorithm, CADe, was developed for the three outer retinal layers using 120 handcraft masks of ORL. This automatic segmentation algorithm generated 4000 segmentations, which included 2000 images with normal ORL and 2000 (1000 CNV and 1000 RP) images with focal or wide defects in ORL. Second, based on the automatically generated segmentation images, a binary classifier (normal vs abnormal) was developed. Results were evaluated by area under the receiver operating characteristic curve (AUC).ResultsThe DL algorithm achieved an AUC of 0.984 (95% CI 0.976 to 0.993) for individual image evaluation in the internal test set of 797 images. In addition, performance analysis of a publicly available external test set (n=968) had an AUC of 0.957 (95% CI 0.944 to 0.970) and a second clinical external test set (n=1124) had an AUC of 0.978 (95% CI 0.970 to 0.986). Moreover, the CADe highlighted well normal parts of ORL and omitted highlights in abnormal ORLs of CNV and RP.ConclusionThe CADe can use OCT images to segment ORL and differentiate between normal ORL and abnormal ORL. The CADe classifier also performs visualisation and may aid future physician diagnosis and clinical applications.

In addition to the development of chrononutrition, food ingredients have been demonstrated to contribute to expression changes in the peripheral clock genes responsible for circadian rhythms. Passion fruit seeds extract (PFSE) contains a high concentration of piceatannol that exhibits many physiological activities; however, whether PFSE and piceatannol affect clock genes is not known with certainty. In this study, we evaluated the effects of PFSE and piceatannol on the rhythm of PER2 using bioluminescence in mPer2Luc knock-in mice and their embryonic fibroblasts. Piceatannol was demonstrated to advance and delay the phase of PER2::LUC oscillation owing to differences in timing of treatment in vitro. In the in vivo imaging system, oral administration of piceatannol significantly advanced the luminescence rhythm of PER2::LUC in peripheral organs. Furthermore, piceatannol recovered the phase change of PER2::LUC disturbed by high-fat diet intake. These findings indicate that piceatannol affects peripheral clock gene expression and may prevent circadian disturbance.

Dynamic fMRI responses vary largely according to the physiological conditions of animals either under anesthesia or in awake states. We developed a real-time fMRI platform to guide experimenters to monitor fMRI responses instantaneously during acquisition, which can be used to modify the physiology of animals to achieve desired hemodynamic responses in animal brains. The real-time fMRI set-up is based on a 14.1T preclinical MRI system, enabling the real-time mapping of dynamic fMRI responses in the primary forepaw somatosensory cortex (FP-S1) of anesthetized rats. Instead of a retrospective analysis to investigate confounding sources leading to the variability of fMRI signals, the real-time fMRI platform provides a more effective scheme to identify dynamic fMRI responses using customized macro-functions and a common neuroimage analysis software in the MRI system. Also, it provides immediate troubleshooting feasibility and a real-time biofeedback stimulation paradigm for brain functional studies in animals.

Background: Doppler optical coherence tomography (DOCT) flowmeter can be used to measure retinal blood flow (RBF) parameters, including vessel diameter, blood velocity, and the absolute value of RBF within 2.0 s. We investigated the RBF parameters in eyes with branch retinal vein occlusion (BRVO) using a DOCT flowmeter. Methods: Seventeen patients with unilateral BRVO were enrolled. All subjects underwent comprehensive ophthalmologic examinations. The RBF parameters were assessed from three veins, i.e., (1) an occluded vein, (2) a non-occluded vein in the BRVO eyes, and (3) an equivalent (superior or inferior) vein in the fellow eye (non-affected vein), using prototype DOCT flowmeter (Topcon, Tokyo, Japan). Moreover, the correlation between RBF parameters and the best corrected visual acuity (BCVA) was examined. We investigated the correlation between (1) the RBF parameters and the time from the initial visit, (2) the RBF parameters and the time from the last injection, and (3) the RBF parameters and the number of anti-vascular endothelial growth factor injections (VEGF). Results: The diameter of the occluded vein (95.9 &plusmn, 24.7 &micro, m) was smaller than that of the non-occluded vein (127.9 &plusmn, 23.7 &micro, m) and that of the healthy veins (116.4 &plusmn, 13.9 &micro, m). The RBF was lower in the occluded veins (4.7 &plusmn, 3.7 &micro, L/min) than that in the non-occluded veins (10.3 &plusmn, 5.1 &micro, L/min, p &lt, 0.01) and in the fellow eyes (8.6 &plusmn, 4.0 &micro, p = 0.013). In contrast, the blood velocity was not significantly different among the three types of veins. BCVA was correlated with the diameter of the occluded vein (&rho, = 0.711, p = 0.001) but not with the RBF and blood velocity. The time from the initial visit, the time from the last injection, and the total number of anti-VEGF injections were not associated with any RBF parameters on the occluded vein. Conclusions: The RBF was significantly lower in the occluded veins than that in the other veins, and the diameter of the occluded vein was significantly smaller than that of the other veins in patients with BRVO. However, neither the time from the initial visit, nor the time from the last injection, nor the number of anti-VEGF injections were correlated with the RBF parameters on the occluded vein.

Pupillometry, a noninvasive measure of arousal, complements human functional MRI (fMRI) to detect periods of variable cognitive processing and identify networks that relate to particular attentional states. Even under anesthesia, pupil dynamics correlate with brain-state fluctuations, and extended dilations mark the transition to more arousable states. However, cross-scale neuronal activation patterns are seldom linked to brain state-dependent pupil dynamics. Here, we complemented resting-state fMRI in rats with cortical calcium recording (GCaMP-mediated) and pupillometry to tackle the linkage between brain-state changes and neural dynamics across different scales. This multimodal platform allowed us to identify a global brain network that covaried with pupil size, which served to generate an index indicative of the brain-state fluctuation during anesthesia. Besides, a specific correlation pattern was detected in the brainstem, at a location consistent with noradrenergic cell group 5 (A5), which appeared to be dependent on the coupling between different frequencies of cortical activity, possibly further indicating particular brain-state dynamics. The multimodal fMRI combining concurrent calcium recordings and pupillometry enables tracking brain state-dependent pupil dynamics and identifying unique cross-scale neuronal dynamic patterns under anesthesia.

Purpose We aimed to observe longitudinal changes in retinal blood flow (RBF) and structural transformations in capillaries using Doppler optical coherence tomography (DOCT) and optical coherence tomography angiography (OCTA) in a feline retinal blood occlusion (RVO) model. Methods RVO was induced by argon green laser photocoagulation (PC) in six eyes of six cats. RBF was measured at a first-order retinal artery and vein by a DOCT flowmeter, and structural changes in the capillaries around the occluded vessels (12 × 12 and 3 × 3 mm) were assessed by OCTA before (at baseline); immediately after PC; and on days 1, 4, 7, and 14 thereafter. Systemic and ocular parameters were monitored during the observation period. Results There were no significant differences in any systemic or ocular parameters before and after PC. Arterial RBF increased significantly on day 1 (160.6 ± 8.6% vs. baseline, P < 0.001) and decreased below baseline after day 1 through 14. Venous RBF decreased immediately after PC (17.4 ± 9.6% vs. baseline, P = 0.001) and then gradually increased afterwards, but did not return to baseline. OCTA showed dilatation of retinal venules immediately after PC to day 1. Collateral vessels began to form on day 4, had matured by day 7, and were pruned on day 14, which formed as mature as normal retinal venule diameters. Conclusions With increasing arterial RBF within 1 day after inducing RVO, venules gradually expanded to form collateral vessels, suggesting that collateral vessels originate from existing capillary networks, not neovascularization.

AimsTo evaluate the associations between retinal blood flow (RBF) and optical coherence tomography (OCT) structural measurements in normal-tension glaucoma (NTG) eyes with single-hemifield visual field (VF) damage by the Doppler OCT.MethodsThe Doppler OCT was used to measure temporal artery (TA) RBF and temporal vein (TV) RBF. Retinal nerve fibre layer thickness (RNFLT) was measured by spectral-domain OCT.ResultsForty-three consecutive eyes of 43 patients with NTG with VF defect confined to a single hemifield and 24 eyes of 24 age-matched healthy subjects were studied. TA and TV RBF and RNFLT were reduced in the damaged hemisphere compared with the normal hemisphere (mean (SD), 3.61 (1.68) vs 5.86 (2.59) µL/min, pConclusionIn NTG eyes with single-hemifield damage, the RBF was significantly reduced in the damaged hemisphere compared with the normal one. The RBF decreased in the normal and damaged hemispheres of NTG eyes compared with the healthy hemisphere independent from RNFLT.

Purpose The glucose-regulated protein 78 (GRP78), also referred to as immunoglobulin heavy chain binding protein (BiP) (BiP/GRP78), is a major molecular chaperone in the endoplasmic reticulum (ER) and is extensively expressed in human neoplasms. Although the enhanced expression of BiP/GRP78 has been described to be associated with poor prognosis in gastric cancer (GC), details regarding its prognostic significance remain unclear. The aim of this study was to elucidate the prognostic role of BiP/GRP78 in patients with GC. Methods Study subjects included 328 patients who underwent surgical resection. Tumor specimens of primary tumors underwent immunohistochemical staining for BiP/GRP78. Results BiP/GRP78 was highly expressed in 57% (188/328) of patients. High expression of BiP/GRP78 was significantly associated with older age, male, disease staging, T factor, lymph node metastases, differentiation, lymphatic permeation, and vascular invasion. According to univariate analysis, age, disease staging, T factor, N factor, lymphatic permeation, vascular invasion, and BiP/GRP78 expression were significant prognostic factors for OS. In particular, high BiP/GRP78 expression was proven to be a significant predictor of prognosis in patients with older age, female sex, early disease stage, T1-2 factor, well or moderately differentiated tumors, and negative vascular invasion. Conclusion BiP/GRP78 is significantly associated with tumor aggressiveness and progression. The increased expression of BiP/GRP78 was identified as an independent factor for predicting poor OS in patients with early stage of disease, especially T1-2 factor.

BACKGROUND CD98 expression is high in various human neoplasms. However, the relationship of CD98 expression with the clinicopathological factors of gastric cancer (GC) remains unclear. This study examined CD98 expression and its clinicopathological impact on GC. PATIENTS AND METHODS Three hundred and thirty-one patients with surgically resected GC were evaluated. Tumor sections were stained and analyzed using immunohistochemistry to assess CD98 expression. RESULTS CD98 was positively expressed in 19% (66/331) of our patient cohort. Increased CD98 expression was significantly associated with advanced GC stage, lymph node metastasis, non-signet histology, lymphatic permeation, and vascular invasion. Positive CD98 expression was also a significant prediction marker for unfavorable prognosis postoperatively. However, CD98 was not identified as GC's independent prognostic predictor. CONCLUSION CD98 could be a novel prediction marker for worse prognosis in GC-affected patients. Our data suggests that increased CD98 expression plays an essential role in tumor aggressiveness and metastasis.

L-type amino acid transporter 1 (LAT1) and CD98 are frequently expressed in various human cancers, and closely correlated with tumor aggressiveness and survival. However, little is known about the expression of LAT1 and CD98 in cutaneous angiosarcoma. The aim of this study is to investigate the clinicopathological significance of these markers in the dismal disease. A total of 52 patients with cutaneous angiosarcoma were retrospectively reviewed. Immunohistochemical staining of tumor specimens were evaluated using anti-LAT1, CD98 and Ki-67 antibodies. The rates of high expression for LAT1 and CD98 were 56% (29/52) and 79% (41/52), respectively. The frequency of high expression for CD98 was significantly higher than that for LAT1 (p=0.021). The low expression of CD98 was significantly associated with distant metastasis (p=0.044) and was identified as a significant prognostic predictor by multivariate analysis. The expression level of LAT1 was not significantly correlated with prognosis. The low expression of CD98 is a novel biomarker for predicting poor prognosis in patients with cutaneous angiosarcoma.

Cutaneous angiosarcoma (CA) is extremely rare, and little is known about the biological significance of possible biomarkers for chemotherapeutic agents. Thymidylate synthase (TS) is an attractive target for cancer treatment in various human neoplasms. It remains unclear whether the expression of TS is associated with the clinicopathological features of CA patients. The aim of this study was to elucidate the relationship between TS expression and the clinicopathological significance in CA patients. Fifty-one patients with CA were included in this study. TS expression and Ki-67 labeling index were examined using immunohistochemical analysis. TS was positively expressed in 39% (20/51) of CA patients. No statistically significant prognostic factor was identified as a predictor of overall survival (OS) for all patients by univariate analysis, whereas a significant prognostic variable for progression free survival (PFS) was found to be the clinical stage. In addition, both univariate and multivariate analyses confirmed that positive expression of TS was a significant predictor of worse PFS in CA patients of clinical stage 1. CONCLUSION Positive TS expression in CA was identified as a significant predictor of worse outcome in patients of clinical stage 1.