Metabolomics, machine learning and immunohistochemistry to predict succinate dehydrogenase mutational status in phaeochromocytomas and paragangliomas.

Phaeochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine tumours with a hereditary background in over one-third of patients. Mutations in succinate dehydrogenase (SDH) genes increase the risk for PPGLs and several other tumours. Mutations in subunit B (SDHB) in particular are a risk factor for metastatic disease, further highlighting the importance of identifying SDHx mutations for patient management. Genetic variants of unknown significance, where implications for the patient and family members are unclear, are a problem for interpretation. For such cases, reliable methods for evaluating protein functionality are required. Immunohistochemistry for SDHB (SDHB-IHC) is the method of choice but does not assess functionality at the enzymatic level. Liquid chromatography-mass spectrometry-based measurements of metabolite precursors and products of enzymatic reactions provide an alternative method. Here, we compare SDHB-IHC with metabolite profiling in 189 tumours from 187 PPGL patients. Besides evaluating succinate:fumarate ratios (SFRs), machine learning algorithms were developed to establish predictive models for interpreting metabolite data. Metabolite profiling showed higher diagnostic specificity compared to SDHB-IHC (99.2% versus 92.5%, p = 0.021), whereas sensitivity was comparable. Application of machine learning algorithms to metabolite profiles improved predictive ability over that of the SFR, in particular for hard-to-interpret cases of head and neck paragangliomas (AUC 0.9821 versus 0.9613, p = 0.044). Importantly, the combination of metabolite profiling with SDHB-IHC has complementary utility, as SDHB-IHC correctly classified all but one of the false negatives from metabolite profiling strategies, while metabolite profiling correctly classified all but one of the false negatives/positives from SDHB-IHC. From 186 tumours with confirmed status of SDHx variant pathogenicity, the combination of the two methods resulted in 185 correct predictions, highlighting the benefits of both strategies for patient management. © 2020 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Novel methods in adrenal research: a metabolomics approach.

Metabolic alterations have implications in a spectrum of tissue functions and disease. Aided by novel molecular biological and computational tools, our understanding of physiological and pathological processes underpinning endocrine and endocrine-related disease has significantly expanded over the last decade. Herein, we focus on novel metabolomics-related methodologies in adrenal research: in situ metabolomics by mass spectrometry imaging, steroid metabolomics by gas and liquid chromatography-mass spectrometry, energy pathway metabologenomics by liquid chromatography-mass spectrometry-based metabolomics of Krebs cycle intermediates, and cellular reprogramming to generate functional steroidogenic cells and hence to modulate the steroid metabolome. All four techniques to assess and/or modulate the metabolome in biological systems provide tremendous opportunities to manage neoplastic and non-neoplastic disease of the adrenal glands in the era of precision medicine. In this context, we discuss emerging clinical applications and/or promising metabolic-driven research towards diagnostic, prognostic, predictive and therapeutic biomarkers in tumours arising from the adrenal gland and extra-adrenal paraganglia as well as modern approaches to delineate and reprogram adrenal metabolism.

New and Emerging Biomarkers in Endocrine Pathology.

Significant advances in genomics and molecular genetics in recent years have reshaped the practice of endocrine pathology. Pan-genomic studies, including the pioneering ones on papillary thyroid carcinoma, phaeochromocytoma/paraganglioma, and adrenal cortical carcinoma from the Cancer Genome Atlas (TCGA) project, provided a comprehensive integrated genomic analysis of endocrine tumors into distinct molecularly defined subtypes. Better understanding of the molecular landscape and more accurate definition of biological behavior has been accordingly achieved. Nevertheless, how any of these advances are translated into routine practice still remains a challenge in the era of precision medicine. The challenge for modern pathology is to keep up the pace with scientific discoveries by integrating novel concepts in tumor classification, molecular genetics, prognostication, and theranostics. As an example, pathology plays a role in the identification of hereditary disease, while it offers the tools for complementing molecular genetics, for example, validation of variants of unknown significance deriving from targeted sequencing or whole exome/genome sequencing approach. Immunohistochemistry has arisen as a cost-effective strategy in the evaluation either of somatic mutations in tumors and/or germline mutations in patients with familial cancer syndromes. Herein, a comprehensive review focusing on novel and emerging biomarkers is presented in order pathologists and other endocrine-related specialists to remain updated and become aware of potential pitfalls and limitations in the field of endocrine pathology.

The mTORC1 Complex Is Significantly Overactivated in SDHX-Mutated Paragangliomas.

AIM: We aimed at exploring the activation pattern of the mTOR pathway in sporadic and hereditary pheochromocytomas (PCCs) and paragangliomas (PGLs). METHODS: A total of 178 PCCs and 44 PGLs, already characterized for the presence of germline mutations in VHL, RET, NF1, MAX, SDHA, SDHB, SDHC, and SDHD as well as somatic mutations in VHL, RET, H-RAS, and MAX, were included in 5 tissue microarrays and tested using immunohistochemistry for mTOR and Rictor as well as the phosphorylated forms of mTOR, p70S6K, AMPK, AKT, 4EBP1, S6, and Raptor. RESULTS: The positive correlation among most of the molecules investigated proved the functional activation of the mTOR pathway in PCCs/PGLs. Total mTOR, p-S6K and p-S6, and mTORC1-associated molecules p-Raptor and p-AMPK were all significantly overexpressed in PGLs rather than in PCCs, and in the head and neck rather than in abdominal locations. None of the markers, except for the low expression of p-mTOR, was associated with malignancy. Cluster 1 PCCs/PGLs had higher total mTOR, p-Raptor, and p-S6 expression than cluster 2 PCCs/PGLs. In contrast, p-mTOR and mTORC2-associated molecule Rictor were significantly overexpressed in cluster 2 tumors. Within cluster 1, molecules active in the mTORC1 complex were significantly overexpressed in SDHX- as compared to VHL-mutated tumors. CONCLUSION: In summary, the mTOR pathway is activated in a high proportion of PCCs/PGLs, with a preferential overactivation of the mTORC1 complex in PGLs of the head and neck and/or harboring SDHX mutations.

SDHB/SDHA immunohistochemistry in pheochromocytomas and paragangliomas: a multicenter interobserver variation analysis using virtual microscopy: a Multinational Study of the European Network for the Study of Adrenal Tumors (ENS@T).

Despite the established role of SDHB/SDHA immunohistochemistry as a valuable tool to identify patients at risk for familial succinate dehydrogenase-related pheochromocytoma/paraganglioma syndromes, the reproducibility of the assessment methods has not as yet been determined. The aim of this study was to investigate interobserver variability among seven expert endocrine pathologists using a web-based virtual microscopy approach in a large multicenter pheochromocytoma/paraganglioma cohort (n=351): (1) 73 SDH mutated, (2) 105 non-SDH mutated, (3) 128 samples without identified SDH-x mutations, and (4) 45 with incomplete SDH molecular genetic analysis. Substantial agreement among all the reviewers was observed either with a two-tiered classification (SDHB κ=0.7338; SDHA κ=0.6707) or a three-tiered classification approach (SDHB κ=0.6543; SDHA κ=0.7516). Consensus was achieved in 315 cases (89.74%) for SDHB immunohistochemistry and in 348 cases (99.15%) for SDHA immunohistochemistry. Among the concordant cases, 62 of 69 (~90%) SDHB-/C-/D-/AF2-mutated cases displayed SDHB immunonegativity and SDHA immunopositivity, 3 of 4 (75%) with SDHA mutations showed loss of SDHA/SDHB protein expression, whereas 98 of 105 (93%) non-SDH-x-mutated counterparts demonstrated retention of SDHA/SDHB protein expression. Two SDHD-mutated extra-adrenal paragangliomas were scored as SDHB immunopositive, whereas 9 of 128 (7%) tumors without identified SDH-x mutations, 6 of 37 (~16%) VHL-mutated, as well as 1 of 21 (~5%) NF1-mutated tumors were evaluated as SDHB immunonegative. Although 14 out of those 16 SDHB-immunonegative cases were nonmetastatic, an overall significant correlation between SDHB immunonegativity and malignancy was observed (P=0.00019). We conclude that SDHB/SDHA immunohistochemistry is a reliable tool to identify patients with SDH-x mutations with an additional value in the assessment of genetic variants of unknown significance. If SDH molecular genetic analysis fails to detect a mutation in SDHB-immunonegative tumor, SDHC promoter methylation and/or VHL/NF1 testing with the use of targeted next-generation sequencing is advisable.

Toward an improved definition of the genetic and tumor spectrum associated with SDH germ-line mutations.

The tricarboxylic acid, or Krebs, cycle is central to the cellular metabolism of sugars, lipids, and amino acids; it fuels the mitochondrial respiratory chain for energy generation. In the past decade, mutations in the Krebs-cycle enzymes succinate dehydrogenase, fumarate hydratase, and isocitrate dehydrogenase have been documented to be causally involved in carcinogenesis. This review is focused on the relationship between SDH mutations and the carcinogenic phenotype. The succinate dehydrogenase complex catalyzes the oxidation of succinate to fumarate; mutations in its subunits SDHA, SDHB, SDHC, and SDHD, and in the assembly factor SDHAF2, result in syndromes with distinct tumor types, including pheochromocytoma/paraganglioma, gastrointestinal stromal tumor, and, less often, renal-cell carcinoma and pituitary adenoma. In this study we collected all previously reported SDH mutations with the aim of defining their nature and tumor spectrum. In addition, genotype-phenotype correlations as well as mechanisms of biallelic inactivation were analyzed in the SDH-deficient setting. Finally, we performed bioinformatics analysis using SIFT, Polyphen2, and Mutation Assessor to predict the functional impact of nonsynonymous mutations. The prediction of the latter was further compared with available SDHA and/or SDHB immunohistochemistry data.

EBV-positive diffuse large B-cell lymphoma of the elderly.

Epstein-Barr virus (EBV) positive diffuse large B-cell lymphoma (DLBCL) of the elderly, initially described in 2003, is a provisional entity in the 2008 World Health Organization classification system and is defined as an EBV-positive monoclonal large B-cell proliferation that occurs in patients >50 years of age and in whom there is no known immunodeficiency or history of lymphoma. These tumors are more common in Asia but also occur in North America and Europe at a low frequency. These neoplasms exhibit a morphologic continuum, from polymorphous to monomorphous, but morphologic features do not correlate with prognosis as all patients have a clinically aggressive course. Most EBV-positive DLBCL of the elderly patients have an activated B-cell immunophenotype and are characterized by prominent nuclear factor-κB activation. Cytogenetic complexity is usually low. In this review, we comprehensively delineate the data emerging from analyses of EBV latency program, microRNA-mediated EBV viral oncogenesis, functional genomics of EBV and its biology, and differential diagnosis challenge for EBV-positive DLBCL of the elderly. It is hoped that the improved understanding of these tumors will lead to the development of novel therapeutic approaches, enhance the effectiveness of clinical trials, and improve prognosis.

Convolutional neural networks for the differentiation between benign and malignant renal tumors with a multicenter international computed tomography dataset.

OBJECTIVES: To use convolutional neural networks (CNNs) for the differentiation between benign and malignant renal tumors using contrast-enhanced CT images of a multi-institutional, multi-vendor, and multicenter CT dataset. METHODS: A total of 264 histologically confirmed renal tumors were included, from US and Swedish centers. Images were augmented and divided randomly 70%:30% for algorithm training and testing. Three CNNs (InceptionV3, Inception-ResNetV2, VGG-16) were pretrained with transfer learning and fine-tuned with our dataset to distinguish between malignant and benign tumors. The ensemble consensus decision of the three networks was also recorded. Performance of each network was assessed with receiver operating characteristics (ROC) curves and their area under the curve (AUC-ROC). Saliency maps were created to demonstrate the attention of the highest performing CNN. RESULTS: Inception-ResNetV2 achieved the highest AUC of 0.918 (95% CI 0.873-0.963), whereas VGG-16 achieved an AUC of 0.813 (95% CI 0.752-0.874). InceptionV3 and ensemble achieved the same performance with an AUC of 0.894 (95% CI 0.844-0.943). Saliency maps indicated that Inception-ResNetV2 decisions are based on the characteristics of the tumor while in most tumors considering the characteristics of the interface between the tumor and the surrounding renal parenchyma. CONCLUSION: Deep learning based on a diverse multicenter international dataset can enable accurate differentiation between benign and malignant renal tumors. CRITICAL RELEVANCE STATEMENT: Convolutional neural networks trained on a diverse CT dataset can accurately differentiate between benign and malignant renal tumors. KEY POINTS: • Differentiation between benign and malignant tumors based on CT is extremely challenging. • Inception-ResNetV2 trained on a diverse dataset achieved excellent differentiation between tumor types. • Deep learning can be used to distinguish between benign and malignant renal tumors.

Paragangliomas: update on differential diagnostic considerations, composite tumors, and recent genetic developments.

Recent developments in molecular genetics have expanded the spectrum of disorders associated with pheochromocytomas (PCCs) and extra-adrenal paragangliomas (PGLs) and have increased the roles of pathologists in helping to guide patient care. At least 30% of these tumors are now known to be hereditary, and germline mutations of at least 10 genes are known to cause the tumors to develop. Genotype-phenotype correlations have been identified, including differences in tumor distribution, catecholamine production, and risk of metastasis, and types of tumors not previously associated with PCC/PGL are now considered in the spectrum of hereditary disease. Important new findings are that mutations of succinate dehydrogenase genes SDHA, SDHB, SDHC, SDHD, and SDHAF2 (collectively "SDHx") are responsible for a large percentage of hereditary PCC/PGL and that SDHB mutations are strongly correlated with extra-adrenal tumor location, metastasis, and poor prognosis. Further, gastrointestinal stromal tumors and renal tumors are now associated with SDHx mutations. A PCC or PGL caused by any of the hereditary susceptibility genes can present as a solitary, apparently sporadic, tumor, and substantial numbers of patients presenting with apparently sporadic tumors harbor occult germline mutations of susceptibility genes. Current roles of pathologists are differential diagnosis of primary tumors and metastases, identification of clues to occult hereditary disease, and triaging of patients for optimal genetic testing by immunohistochemical staining of tumor tissue for the loss of SDHB and SDHA protein. Diagnostic pitfalls are posed by morphological variants of PCC/PGL, unusual anatomic sites of occurrence, and coexisting neuroendocrine tumors of other types in some hereditary syndromes. These pitfalls can be avoided by judicious use of appropriate immunohistochemical stains. Aside from loss of staining for SDHB, criteria for predicting risk of metastasis are still controversial, and "malignancy" is diagnosed only after metastases have occurred. All PCCs/PGLs are considered to pose some risk of metastasis, and long-term follow-up is advised.

Machine Learning Integrating 99mTc Sestamibi SPECT/CT and Radiomics Data Achieves Optimal Characterization of Renal Oncocytic Tumors.

The increasing evidence of oncocytic renal tumors positive in 99mTc Sestamibi Single Photon Emission Tomography/Computed Tomography (SPECT/CT) examination calls for the development of diagnostic tools to differentiate these tumors from more aggressive forms. This study combined radiomics analysis with the uptake of 99mTc Sestamibi on SPECT/CT to differentiate benign renal oncocytic neoplasms from renal cell carcinoma. A total of 57 renal tumors were prospectively collected. Histopathological analysis and radiomics data extraction were performed. XGBoost classifiers were trained using the radiomics features alone and combined with the results from the visual evaluation of 99mTc Sestamibi SPECT/CT examination. The combined SPECT/radiomics model achieved higher accuracy (95%) with an area under the curve (AUC) of 98.3% (95% CI 93.7-100%) than the radiomics-only model (71.67%) with an AUC of 75% (95% CI 49.7-100%) and visual evaluation of 99mTc Sestamibi SPECT/CT alone (90.8%) with an AUC of 90.8% (95%CI 82.5-99.1%). The positive predictive values of SPECT/radiomics, radiomics-only, and 99mTc Sestamibi SPECT/CT-only models were 100%, 85.71%, and 85%, respectively, whereas the negative predictive values were 85.71%, 55.56%, and 94.6%, respectively. Feature importance analysis revealed that 99mTc Sestamibi uptake was the most influential attribute in the combined model. This study highlights the potential of combining radiomics analysis with 99mTc Sestamibi SPECT/CT to improve the preoperative characterization of benign renal oncocytic neoplasms. The proposed SPECT/radiomics classifier outperformed the visual evaluation of 99mTc Sestamibii SPECT/CT and the radiomics-only model, demonstrating that the integration of 99mTc Sestamibi SPECT/CT and radiomics data provides improved diagnostic performance, with minimal false positive and false negative results.

A pilot radiometabolomics integration study for the characterization of renal oncocytic neoplasia.

Differentiating benign renal oncocytic tumors and malignant renal cell carcinoma (RCC) on imaging and histopathology is a critical problem that presents an everyday clinical challenge. This manuscript aims to demonstrate a novel methodology integrating metabolomics with radiomics features (RF) to differentiate between benign oncocytic neoplasia and malignant renal tumors. For this purpose, thirty-three renal tumors (14 renal oncocytic tumors and 19 RCC) were prospectively collected and histopathologically characterised. Matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI) was used to extract metabolomics data, while RF were extracted from CT scans of the same tumors. Statistical integration was used to generate multilevel network communities of -omics features. Metabolites and RF critical for the differentiation between the two groups (delta centrality > 0.1) were used for pathway enrichment analysis and machine learning classifier (XGboost) development. Receiver operating characteristics (ROC) curves and areas under the curve (AUC) were used to assess classifier performance. Radiometabolomics analysis demonstrated differential network node configuration between benign and malignant renal tumors. Fourteen nodes (6 RF and 8 metabolites) were crucial in distinguishing between the two groups. The combined radiometabolomics model achieved an AUC of 86.4%, whereas metabolomics-only and radiomics-only classifiers achieved AUC of 72.7% and 68.2%, respectively. Analysis of significant metabolite nodes identified three distinct tumour clusters (malignant, benign, and mixed) and differentially enriched metabolic pathways. In conclusion, radiometabolomics integration has been presented as an approach to evaluate disease entities. In our case study, the method identified RF and metabolites important in differentiating between benign oncocytic neoplasia and malignant renal tumors, highlighting pathways differentially expressed between the two groups. Key metabolites and RF identified by radiometabolomics can be used to improve the identification and differentiation between renal neoplasms.

99mTc-Sestamibi SPECT/CT and histopathological features of oncocytic renal neoplasia.

BACKGROUND: 99mTc-Sestamibi Single Photon Emission Computed Tomography/Computed Tomography (SPECT/CT) contributes to the non-invasive differentiation of renal oncocytoma (RO) from renal cell carcinoma (RCC) by characterising renal tumours as Sestamibi positive or Sestamibi negative regarding their 99mTc-Sestamibi uptake compared to the non-tumoral renal parenchyma. PURPOSE: To determine whether 99mTc- Sestamibi uptake in renal tumour and the non-tumoral renal parenchyma measured using Standard Uptake Value (SUV) SPECT, has a beneficial role in differentiating RO from RCC. MATERIAL AND METHODS: Fifty-seven renal tumours from 52 patients were evaluated. In addition to visual evaluation of 99mTc-Sestamibi uptake, SUVmax measurements were performed in the renal tumour and the ipsilateral non-tumoral renal parenchyma. Analysis of the area under the receiver operating characteristic curve identified an optimal cut-off value for detecting RO, based on the relative ratio of 99mTc- Sestamibi uptake. RESULTS: Semiquantitative evaluation of 99mTc-Sestamibi uptake did not improve the performance of 99mTc- Sestamibi SPECT/CT in detecting RO. 99mTc- Sestamibi SPECT/CT identifies a group of mostly indolent Sestamibi-positive tumours with low malignant potential containing RO, Low-Grade Oncocytic Tumours, Hybrid Oncocytic Tumours, and a subset of chromophobe RCCs. CONCLUSION: The imaging limitations for accurate differentiation of Sestamibi-positive renal tumours mirror the recognised diagnostic complexities of the histopathologic evaluation of oncocytic neoplasia. Patients with Sestamibi-positive renal tumours could be better suited for biopsy and follow-up, according to the current active surveillance protocols.

Cue relevance effects in conjunctive visual search: cueing for location, color, and orientation.

Performance in visual search tasks where the target differs from distractors by a conjunction of features can improve when a precue signals observers to limit their search by attending to a subset of elements. The current experiments were designed to study the temporal characteristics of precueing the location or feature (color or orientation) of targets in color-orientation conjunctive searches. Color (sensory or symbolic), location, or orientation precues preceded the search stimulus with cue-to-stimulus onset asynchrony (SOA) in the range of 50-750 ms. The stimuli consisted of elements formed by combining horizontal/vertical and red/green features. Observers responded to the presence/absence of an odd element in an "odd-man-out" paradigm. Reaction time and accuracy were used as measures of performance. Color and location precues improved search performance. The magnitude of improvement did not vary as the SOA changed. The color and location cues exhibited their effects in guiding visual search even at 50 ms after cue onset. However, orientation precue did not facilitate nor inhibit the search processing. These results indicate that in conjunctive search it takes at most 50 ms after cue onset for the visual system to exert the guidance effects using color and location precueing. We speculate that color may be a stronger feature than orientation for segmenting the search elements, thus facilitating visual search.

State anxiety influences P300 and P600 event-related potentials over parietal regions in the hollow-mask illusion experiment.

The hollow-mask illusion is an optical illusion where a concave face is perceived as convex. It has been demonstrated that individuals with schizophrenia and anxiety are less susceptible to the illusion than controls. Previous research has shown that the P300 and P600 event-related potentials (ERPs) are affected in individuals with schizophrenia. Here, we examined whether individual differences in neuroticism and anxiety scores, traits that have been suggested to be risk factors for schizophrenia and anxiety disorders, affect ERPs of healthy participants while they view concave faces. Our results confirm that the participants were susceptible to the illusion, misperceiving concave faces as convex. We additionally demonstrate significant interactions of the concave condition with state anxiety in central and parietal electrodes for P300 and parietal areas for P600, but not with neuroticism and trait anxiety. The state anxiety interactions were driven by low-state anxiety participants showing lower amplitudes for concave faces compared to convex. The P300 and P600 amplitudes were smaller when a concave face activated a convex face memory representation, since the stimulus did not match the active representation. The opposite pattern was evident in high-state anxiety participants in regard to state anxiety interaction and the hollow-mask illusion, demonstrating larger P300 and P600 amplitudes to concave faces suggesting impaired late information processing in this group. This could be explained by impaired allocation of attentional resources in high-state anxiety leading to hyperarousal to concave faces that are unexpected mismatches to standard memory representations, as opposed to expected convex faces.

What Have We Learned from Molecular Biology of Paragangliomas and Pheochromocytomas?

Recent advances in molecular genetics and genomics have led to increased understanding of the aetiopathogenesis of pheochromocytomas and paragangliomas (PPGLs). Thus, pan-genomic studies now provide a comprehensive integrated genomic analysis of PPGLs into distinct molecularly defined subtypes concordant with tumour genotypes. In addition, new embryological discoveries have refined the concept of how normal paraganglia develop, potentially establishing a developmental basis for genotype-phenotype correlations for PPGLs. The challenge for modern pathology is to translate these scientific discoveries into routine practice, which will be based largely on histopathology for the foreseeable future. Here, we review recent progress concerning the cell of origin and molecular pathogenesis of PPGLs, including pathogenetic mechanisms, genetic susceptibility and molecular classification. The current roles and tools of pathologists are considered from a histopathological perspective, including differential diagnoses, genotype-phenotype correlations and the use of immunohistochemistry in identifying hereditary predisposition and validating genetic variants of unknown significance. Current and potential molecular prognosticators are also presented with the hope that predictive molecular biomarkers will be integrated into risk stratification scoring systems to assess the metastatic potential of these intriguing neoplasms and identify potential drug targets.

Treatment of submacular hemorrhage with tissue plasminogen activator and pneumatic displacement in age-related macular degeneration.

PURPOSE: To evaluate visual and anatomic outcomes following pars plana vitrectomy and intravitreal or subretinal tissue plasminogen activator for submacular hemorrhage in patients with age-related macular degeneration. METHODS: This was a retrospective study on patients with a minimum follow-up of 12 months undertaken at a tertiary referral center. Data collected include demographic details, visual and optical coherence tomography changes, surgical details, and complications. Surgical results were compared with patients who were age and lesion size matched and treated with anti-vascular endothelial growth factor injections alone. RESULTS: There were 36 patients in surgical and 18 patients in control group. Patients in surgical arm had pars plana vitrectomy, intravitreal tissue plasminogen activator with air 24 (67%), 6 (16%) with C3F8 gas, 1 (3%) with SF6 gas, 4 (11%) subretinal tissue plasminogen activator with air, and 1 (3%) with C2F6 as post-operative tamponade. Mean LogMAR in tissue plasminogen activator group at baseline was 1.56, and it was improved at all time points 1.06 at 1 month (p < 0.05), 0.91 at 6 months (p < 0.05), and 1.07 at 1 year (p < 0.05). Mean best corrected visual acuity in control group at baseline was 1.22LogMAR with no significant improvement at any time points: 1 month (1.27), 6 months (1.35), and 12 months (1.36). Complications included retinal detachment 5%, vitreous hemorrhage 7.5%, and cataract 19%. CONCLUSION: Pars plana vitrectomy with intravitreal (or subretinal) tissue plasminogen activator and pneumatic displacement can offer better outcome in comparison to anti-vascular endothelial growth factor alone in patients with submacular hemorrhage secondary to age-related macular degeneration.