Intracoronary Images Research Articles

Characterization of coronary artery pathological formations from OCT imaging using deep learning.

Coronary artery disease is the number one health hazard leading to the pathological formations in coronary artery tissues. In severe cases, they can lead to myocardial infarction and sudden death. Optical Coherence Tomography (OCT) is an interferometric imaging modality, which has been recently used in cardiology to characterize coronary artery tissues providing high resolution ranging from 10 to 20 µm. In this study, we investigate different deep learning models for robust tissue characterization to learn the various intracoronary pathological formations caused by Kawasaki disease (KD) from OCT imaging. The experiments are performed on 33 retrospective cases comprising of pullbacks of intracoronary cross-sectional images obtained from different pediatric patients with KD. Our approach evaluates deep features computed from three different pre-trained convolutional networks. Then, a majority voting approach is applied to provide the final classification result. The results demonstrate high values of accuracy, sensitivity, and specificity for each tissue (up to 0.99 ± 0.01). Hence, deep learning models and especially, majority voting method are robust for automatic interpretation of the OCT images.

Clinical study of optical coherence tomography in the diagnosis of peripheral pulmonary artery thrombus

BackgroundPeripheral pulmonary artery thrombus (PPT) is common in the clinic. However, due to the lack of an ideal diagnostic tool, PPT cannot be quickly diagnosed and effectively treated at present. Optical coherence tomography (OCT) is a new intravascular imaging technique that is characterized by high image resolution. This technique is suitable for small vessel imaging and has the ability to distinguish red and white thrombi. ObjectiveThis study aimed to evaluate the value of OCT in the diagnosis of PPT and in identifying the nature of thrombi by comparing the difference in sensitivity between OCT and selective pulmonary angiography (SPA). MethodsHighly suspected PPT patients were enrolled in this study. Pulmonary ventilation/perfusion (V/Q) mismatch pulmonary segments or peripheral pulmonary arteries were chosen. SPA was performed first, followed by OCT imaging. The diagnostic standard of thrombus with SPA was an intraluminal filling defect. The procedure and criteria for OCT diagnosis of thrombus were previously introduced in intracoronary OCT thrombus images. The diameter of the imaging vessels was measured, and they were grouped according to diameter. The diameter was <2mm in the distal segment group, 2–3mm in the middle segment group, and >3mm in the proximal segment group. The recognition abilities of intravascular thrombus with the different diameters of these two techniques were compared. Patients with obvious clinical symptoms and more red thromboses revealed by OCT were given standardized anticoagulant therapy for half a year. The clinical symptoms, 6-minute walking test and changes in the thrombus in the OCT images of these patients before and after treatment were observed. ResultsA total of 22 patients with highly suspected PPT were suggested to undergo V/Q inspection. Finally, 12 patients were eligible for the study. SPA and OCT were performed in 61 peripheral pulmonary arteries in all 12 patients. The ideal SPA and OCT images obtained from a total of 76 blood vessel segments were suitable for comparative analysis. A total of 62 thrombi were found by SPA. Among these, eight thrombi were in the distal segment, 29 thrombi were in the middle segment, and 25 thrombi were in the proximal segment. A total of 81 thrombi were found by OCT, among which 22 thrombi were in the distal segment, 31 were in the middle segment, and 28 were in the proximal segment. There was a significant difference between two groups in the distal segment group (P=0.013), while there was no significant difference between two groups in the middle segment group or the proximal segment group (P>0.05). In addition to all the thrombi found by SPA, OCT found other thrombi that were missed by SPA. According to previous OCT images for determining the nature of thrombi, OCT revealed 81 thrombi, of which 48 (59%) were red thrombi and 33 (41%) were white thrombi. Then, seven patients who had obvious clinical symptoms and more red thrombi in the peripheral pulmonary artery were given anticoagulant therapy for six months. After treatment, these symptoms were improved, oxygenation indexes increased, and the six-minute walking test was extended in all these patients. After anticoagulation therapy, five patients underwent OCT review. These OCT images were matched and compared before and after anticoagulation therapy. The results revealed that most of the thrombi had disappeared, and a small amount of red thrombi turned white as the volume reduced. The mean lumen area before and after treatment was 2.05±1.03mm2 and 2.86±1.24mm2, respectively, and the difference was statistically significant (P=0.035). ConclusionOCT can clearly show the structure of the lumen and the wall of the peripheral pulmonary artery tube. The sensitivity of the diagnosis of PPT with a diameter of <2mm was higher than that of SPA. Moreover, OCT has the ability to distinguish between red and white thrombi, which is of guiding significance in anticoagulant therapy.

Automated Segmentation of Bioresorbable Vascular Scaffold Struts in Intracoronary Optical Coherence Tomography Images.

Bioresorbable vascular scaffolds (BVS), the next step in the continuum of minimally invasive vascular interventions present new opportunities for patients and clinicians but challenges as well. As they are comprised of polymeric materials standard imaging is challenging. This is especially problematic as modalities like optical coherence tomography (OCT) become more prevalent in cardiology. OCT, a light-based intracoronary imaging technique, provides cross-sectional images of plaque and luminal morphology. Until recently segmentation of OCT images for BVS struts was performed manually by experts. However, this process is time consuming and not tractable for large amounts of patient data. Several automated methods exist to segment metallic stents, which do not apply to the newer BVS. Given this current limitation coupled with the emerging popularity of the BVS technology, it is crucial to develop an automated methodology to segment BVS struts in OCT images. The objective of this paper is to develop a novel BVS strut detection method in intracoronary OCT images. First, we preprocess the image to remove imaging artifacts. Then, we use a K-means clustering algorithm to automatically segment the image. Finally, we isolate the stent struts from the rest of the image. The accuracy of the proposed method was evaluated using expert estimations on 658 annotated images acquired from 7 patients at the time of coronary arterial interventions. Our proposed methodology has a positive predictive value of 0.93, a Pearson Correlation coefficient of 0.94, and a F1 score of 0.92. The proposed methodology allows for rapid, accurate, and fully automated segmentation of BVS struts in OCT images.

Compensation of Respiratory Motion Artifacts in Catheter-Based Intracoronary Images

Compensation of Respiratory Motion Artifacts in Catheter-Based Intracoronary Images

Contour segmentation of the intima, media, and adventitia layers in intracoronary OCT images: application to fully automatic detection of healthy wall regions

PurposeQuantitative and automatic analysis of intracoronary optical coherence tomography images is useful and time-saving to assess cardiovascular risk in the clinical arena.MethodsFirst, the interfaces of the intima, media, and adventitia layers are segmented, by means of an original front propagation scheme, running in a 4D multi-parametric space, to simultaneously extract three non-crossing contours in the initial cross-sectional image. Second, information resulting from the tentative contours is exploited by a machine learning approach to identify healthy and diseased regions of the arterial wall. The framework is fully automatic.ResultsThe method was applied to 40 patients from two different medical centers. The framework was trained on 140 images and validated on 260 other images. For the contour segmentation method, the average segmentation errors were 29 pm 46~upmu text {m} for the intima–media interface, 30 pm 50~upmu text {m} for the media–adventitia interface, and 50 pm 64~upmu text {m} for the adventitia–periadventitia interface. The classification method demonstrated a good accuracy, with a median Dice coefficient equal to 0.93 and an interquartile range of (0.78–0.98).ConclusionThe proposed framework demonstrated promising offline performances and could potentially be translated into a reliable tool for various clinical applications, such as quantification of tissue layer thickness and global summarization of healthy regions in entire pullbacks.

Plaque segmentation of intracoronary optical coherence tomography images based on K-means and improved random walk algorithm

In recent years, optical coherence tomography (OCT) has developed into a popular coronary imaging technology at home and abroad. The segmentation of plaque regions in coronary OCT images has great significance for vulnerable plaque recognition and research. In this paper, a new algorithm based on K-means clustering and improved random walk is proposed and Semi-automated segmentation of calcified plaque, fibrotic plaque and lipid pool was achieved. And the weight function of random walk is improved. The distance between the edges of pixels in the image and the seed points is added to the definition of the weight function. It increases the weak edge weights and prevent over-segmentation. Based on the above methods, the OCT images of 9 coronary atherosclerotic patients were selected for plaque segmentation. By contrasting the doctor's manual segmentation results with this method, it was proved that this method had good robustness and accuracy. It is hoped that this method can be helpful for the clinical diagnosis of coronary heart disease.

Optical Coherence Tomography Guidance for Percutaneous Intervention

Article, see p 906 Adoption of invasive imaging for guidance during percutaneous coronary interventions (PCI) varies largely between clinical sites and between geographies, being greatest in Japan, intermediate to low in the United States and Asia, and very low to nonexistent in Europe. Yet nearly every interventional cardiologist will agree that intracoronary images obtained by intravascular ultrasound (IVUS) and optical coherence tomography (OCT) add significant information content to what is provided by angiography alone, thereby improving the understanding of and our capacity to interpret angiographic images. Although Japanese colleagues have the opportunity to use either IVUS or OCT in the majority of cases as part of their regular procedural strategy, use of invasive imaging in the rest of the world is hampered by inadequate or restricted reimbursement. Payers and some physicians are indeed claiming that adding IVUS or OCT imaging to simple angiographic guidance has not been shown unequivocally to affect patient outcomes. Observational or retrospective data obtained with use of the more recently developed OCT are even less conclusive than those obtained over the years with IVUS guidance.1 The study reported here by Meneveau et al2 is an important milestone in the journey to accumulating sufficient global evidence to support the role of OCT-guidance eventually during complex PCI and to extend the Practice Guidelines recommendations supporting its use. As mentioned in the original article,3 the DOCTORS (Does Optical Coherence Tomography Optimize Results of Stenting?) randomized trial is an investigator-driven initiative, supported by central analyses performed at the leading participating center, and funded by the French government. DOCTORS is the first, randomized, multicenter study specifically evaluating the impact of combined angiographic and OCT imaging on PCI optimization. The study confirms prior observational or retrospective studies4–7 in identifying OCT findings that jeopardize the immediate PCI …

Identifying stable coronary plaques with OCT technology

AbstractThis article discusses the current value of optical coherence tomography (OCT) for the assessment of stable coronary lesions. OCT generates intracoronary images with unprecedented image resolution, namely a 10‐fold higher image resolution compared to conventional intravascular ultrasound. OCT is able to visualize a variety of atherosclerotic plaques features that have been associated with rapid lesion progression and clinical events. There is broad agreement that the detailed, easy accessible, and interpretable information of OCT on the presence of atherosclerosis, its extent, lumen narrowing, as well as on the result of any interventional measure can be of clinical value, at least in individual patients and in specific clinical scenarios. Preliminary data indicate that OCT can change the operator's intention‐to‐treat and modify the overall revascularization strategy, potentially avoiding unnecessary interventional procedures. OCT might be efficient in complex interventions including treatment of long lesions, diffuse disease, bifurcations, as well as in all cases of angiographically ambiguous lesions. As such, OCT might emerge, next to its undisputed position in research, as tool of choice in all clinical scenarios where angiography is limited by its nature as two‐dimensional luminogram.Answer questions and earn CME: https://wileyhealthlearning.com/Activity2/4279893/Activity.aspx

Iatrogenic Occlusion of the Circumflex Artery: Intracoronary Image

Iatrogenic Occlusion of the Circumflex Artery: Intracoronary Image

Clinical Characterization of Coronary Atherosclerosis With Dual-Modality OCT and Near-Infrared Autofluorescence Imaging

ObjectivesThe authors present the clinical imaging of human coronary arteries in vivo using a multimodality optical coherence tomography (OCT) and near-infrared autofluorescence (NIRAF) intravascular imaging system and catheter. BackgroundAlthough intravascular OCT is capable of providing microstructural images of coronary atherosclerotic lesions, it is limited in its capability to ascertain the compositional/molecular features of plaque. A recent study in cadaver coronary plaque showed that endogenous NIRAF is elevated in necrotic core lesions. The combination of these 2 technologies in 1 device may therefore provide synergistic data to aid in the diagnosis of coronary pathology in vivo. MethodsWe developed a dual-modality intravascular imaging system and 2.6-F catheter that can simultaneously acquire OCT and NIRAF data from the same location on the artery wall. This technology was used to obtain volumetric OCT-NIRAF images from 12 patients with coronary artery disease undergoing percutaneous coronary intervention. Images were acquired during a brief, nonocclusive 3- to 4-ml/s contrast purge at a speed of 100 frames/s and a pullback rate of 20 or 40 mm/s. OCT-NIRAF data were analyzed to determine the distribution of the NIRAF signal with respect to OCT-delineated plaque morphological features. ResultsHigh-quality intracoronary OCT and NIRAF image data (>50-mm pullback length) were successfully acquired without complication in all patients (17 coronary arteries). The maximum NIRAF signal intensity of each plaque was compared with OCT-defined type, showing a statistically significant difference between plaque types (1-way analysis of variance, p < 0.0001). Interestingly, coronary arterial NIRAF intensity was elevated only focally in plaques with a high-risk morphological phenotype (p < 0.05), including OCT fibroatheroma, plaque rupture, and fibroatheroma associated with in-stent restenosis. ConclusionsThis OCT-NIRAF study demonstrates that dual-modality microstructural and fluorescence intracoronary imaging can be safely and effectively conducted in human patients. Our findings show that NIRAF is associated with a high-risk morphological plaque phenotype. The focal distribution of NIRAF in these lesions furthermore suggests that this endogenous imaging biomarker may provide complementary information to that obtained by structural imaging alone.

Optical coherence tomography: a new diagnostic technique in interventional cardiology.

Optical coherence tomography (OCT) is a novel invasive imaging technique that produces high resolution intracoronary images. Its general principle of operation is similar to intravascular ultrasound, however OCT uses infrared light, not ultrasound. Using infrared light, optical coherence tomography enables detailed evaluation of coronary atherosclerotic plaques and of the vascular response to coronary interventional devices, such as new generation coronary stents. 1 Optical coherence tomography can also be used as guide for coronary intervention. In the last years, the need for more precise information regarding coronary artery disease to achieve optimal treatment has seen intravascular imaging becoming an area of primary importance in interventional cardiology. OCT in this area has grown and is spreading. It benefits both therapeutic and research purposes and is also proving able to fill gaps in conventional invasive coronary imaging.

Automated detection of cardiac phase from intracoronary ultrasound image sequences.

Intracoronary ultrasound (ICUS) is a widely used interventional imaging modality in clinical diagnosis and treatment of cardiac vessel diseases. Due to cyclic cardiac motion and pulsatile blood flow within the lumen, there exist changes of coronary arterial dimensions and relative motion between the imaging catheter and the lumen during continuous pullback of the catheter. The action subsequently causes cyclic changes to the image intensity of the acquired image sequence. Information on cardiac phases is implied in a non-gated ICUS image sequence. A 1-D phase signal reflecting cardiac cycles was extracted according to cyclical changes in local gray-levels in ICUS images. The local extrema of the signal were then detected to retrieve cardiac phases and to retrospectively gate the image sequence. Results of clinically acquired in vivo image data showed that the average inter-frame dissimilarity of lower than 0.1 was achievable with our technique. In terms of computational efficiency and complexity, the proposed method was shown to be competitive when compared with the current methods. The average frame processing time was lower than 30 ms. We effectively reduced the effect of image noises, useless textures, and non-vessel region on the phase signal detection by discarding signal components caused by non-cardiac factors.

Optical Coherence Tomography in Coronary Atherosclerosis

Despite developments in therapeutic and diagnostic technologies, the global burden of atherosclerotic coronary artery disease is increasing. Intravascular imaging has become an invaluable adjunct to percutaneous coronary intervention. Optical coherence tomography (OCT) is a catheter based invasive imaging system that uses light instead of ultrasound to produce high resolution in vivo images of coronary arteries and deployed stents. The technical aspects of intracoronary image acquisition, advantages, disadvantages of use and current applications of OCT in coronary atherosclerosis are discussed.

GPU-accelerated framework for intracoronary optical coherence tomography imaging at the push of a button.

Frequency domain optical coherence tomography (FD-OCT) has become one of the important clinical tools for intracoronary imaging to diagnose and monitor coronary artery disease, which has been one of the leading causes of death. To help more accurate diagnosis and monitoring of the disease, many researchers have recently worked on visualization of various coronary microscopic features including stent struts by constructing three-dimensional (3D) volumetric rendering from series of cross-sectional intracoronary FD-OCT images. In this paper, we present the first, to our knowledge, "push-of-a-button" graphics processing unit (GPU)-accelerated framework for intracoronary OCT imaging. Our framework visualizes 3D microstructures of the vessel wall with stent struts from raw binary OCT data acquired by the system digitizer as one seamless process. The framework reports the state-of-the-art performance; from raw OCT data, it takes 4.7 seconds to provide 3D visualization of a 5-cm-long coronary artery (of size 1600 samples x 1024 A-lines x 260 frames) with stent struts and detection of malapposition automatically at the single push of a button.

Intravascular imaging in Kounis syndrome: role of IVUS and OCT in achieving an etiopathogenic diagnosis.

We report a case of a 60-year-old male patient presenting with anaphylactic response to anchovies associated with an acute coronary syndrome. His history was remarkable for coronary artery disease treated with a drug eluting stent to the right coronary artery six years before and stent fracture documented by coronary angiography four years prior to the event. Coronary angiography on admission revealed a very late stent thrombosis (VLST) in the right coronary artery. Intracoronary imaging techniques (IVUS and OCT) were used and were key to discard main causes of VLST. We described the characteristics of intracoronary images, along with the advantages and disadvantages of these techniques. The findings described in this case could explain a new physiopathological mechanism of stent thrombosis occurring in stent fractures.

Automatic atherosclerotic heart disease detection in intracoronary optical coherence tomography images.

Intracoronary optical coherence tomography (OCT) is a new invasive imaging system which produces high-resolution images of coronary arteries. Preliminary data suggests that the atherosclerotic disease can be detected from the intracoronary OCT images. However, manual assessment of the intracoronary OCT images is time-consuming and subjective. In this work, we present an automatic atherosclerotic disease detection system on intracoronary OCT images. In the system, a preprocessing scheme is first applied to remove speckle noise and artifacts caused by catheter. Intensity, Histograms of Oriented Gradients (HOG), and Local Binary Patterns (LBP) are then extracted to represent the OCT image. Finally a linear SVM classifier is employed to detect the unhealthy subject. Four-fold cross-validation process is conducted to evaluate the proposed system; and a dataset with 200 images from healthy subjects and 200 images from unhealthy subjects is built to evaluate the system. The mean accuracy is 0.90 and standard deviation is 0.0427, which indicates that the proposed system is accurate and stable.

Optical Coherence Tomographic Imaging in a Patient with Granulomatosis with Polyangiitis Presenting with Acute Myocardial Infarction

Optical Coherence Tomography (OCT) is an imaging modality that produces high-resolution intracoronary images. We used it to see intraluminal thrombi, coronary intima, atherosclerotic plaque morphology, and stent strut coverage. A 59-year-old woman with a recent diagnosis of granulomatosis with polyangiitis (GPA; previously Wegener’s granulomatosis) presented with fever and chest pain. An electrocardiogram showed ST segment elevation in the anterior leads. Emergent coronary angiography demonstrated total occlusion (Figure 1A) of the mid-left anterior descending artery …

Methodology for fully automated segmentation and plaque characterization in intracoronary optical coherence tomography images

Optical coherence tomography (OCT) is a light-based intracoronary imaging modality that provides high-resolution cross-sectional images of the luminal and plaque morphology. Currently, the segmentation of OCT images and identification of the composition of plaque are mainly performed manually by expert observers. However, this process is laborious and time consuming and its accuracy relies on the expertise of the observer. To address these limitations, we present a methodology that is able to process the OCT data in a fully automated fashion. The proposed methodology is able to detect the lumen borders in the OCT frames, identify the plaque region, and detect four tissue types: calcium (CA), lipid tissue (LT), fibrous tissue (FT), and mixed tissue (MT). The efficiency of the developed methodology was evaluated using annotations from 27 OCT pullbacks acquired from 22 patients. High Pearson's correlation coefficients were obtained between the output of the developed methodology and the manual annotations (from 0.96 to 0.99), while no significant bias with good limits of agreement was shown in the Bland-Altman analysis. The overlapping areas ratio between experts' annotations and methodology in detecting CA, LT, FT, and MT was 0.81, 0.71, 0.87, and 0.81, respectively.

Clinical validation of an algorithm for rapid and accurate automated segmentation of intracoronary optical coherence tomography images

ObjectivesThe analysis of intracoronary optical coherence tomography (OCT) images is based on manual identification of the lumen contours and relevant structures. However, manual image segmentation is a cumbersome and time-consuming process, subject to significant intra- and inter-observer variability. This study aims to present and validate a fully-automated method for segmentation of intracoronary OCT images. MethodsWe studied 20 coronary arteries (mean length=39.7±10.0mm) from 20 patients who underwent a clinically-indicated cardiac catheterization. The OCT images (n=1812) were segmented manually, as well as with a fully-automated approach. A semi-automated variation of the fully-automated algorithm was also applied. Using certain lumen size and lumen shape characteristics, the fully- and semi-automated segmentation algorithms were validated over manual segmentation, which was considered as the gold standard. ResultsLinear regression and Bland–Altman analysis demonstrated that both the fully-automated and semi-automated segmentation had a very high agreement with the manual segmentation, with the semi-automated approach being slightly more accurate than the fully-automated method. The fully-automated and semi-automated OCT segmentation reduced the analysis time by more than 97% and 86%, respectively, compared to manual segmentation. ConclusionsIn the current work we validated a fully-automated OCT segmentation algorithm, as well as a semi-automated variation of it in an extensive “real-life” dataset of OCT images. The study showed that our algorithm can perform rapid and reliable segmentation of OCT images.

TCT-657 Calibration of Intravascular Optical Coherence Tomography As Presented In Peer Reviewed Publications

Intravascular optical coherence tomography (OCT) is a new imaging modality in interventional cardiology providing highresolution intracoronary images. The modality is already established as an efficient and precise research tool and is increasingly used for guiding coronary intervention. The quantitative capabilities of marketed OCT systems have been validated and measurements are found accurate and precise in bench testing [1]. When using OCT it is important to carefully calibrate the system for accuratemeasurements [2,3]. Present standard in marketed systems is automated calibration. Still the calibration can be incorrect due to failed automated calibration, wrong manual adjustment, or changes to the length of the optic fiber due to altered bending of the imaging wire. Correct calibration and the identification of incorrect calibration can be challenging due to mirror artifacts, blood in the imaging wire and proximity to the vessel wall. Looking for guidance on calibration of intravascular OCT in published peer reviewed papers led to the identification of some inconsistencies similar to our own experience. Still we do not have a database of wrong calibrations owing to immediate corrections. Therefore we aimed at identifying patterns of failed calibration as presented in images in peerreviewed papers. Using the PubMed internet database, we built a search containing following MESH-terms: “Tomography, Optical Coherence” AND (“Percutaneous Coronary Intervention”OR “Coronary Occlusion”OR “Coronary Stenosis” OR “Coronary Restenosis” OR “Coronary Vessels” OR “Coronary Disease”OR “Coronary Circulation”OR “Coronary Thrombosis” OR “Coronary Artery Disease” OR “Myocardial Reperfusion”). With this search more than 300 articles published since 1 January 2011 were identified. Of these, 222 were included in the analysis giving a total of 1164 OCT images with the information needed for evaluating the calibration. Articles which were excluded from the analysis are due to lack of images (N = 57), lack of fiduciaries (N = 38) or no full-text subscription by the local university library (N = 27). Calibration errors were divided into 8 groups, ranging from slightly incorrect through errors with potentially clinical relevant impact on quantitative measurements. Errors in classes that may likely affect stent sizing if applied in clinical practice were termed serious calibration errors (Classes 3, 4 and 6). Frames which we were unable to classify were not counted and if a frame appearedmore than once or in more articles (e.g. editorials), it was only counted once. Our findings (shown in Table 1) were 1) 640 images produced by time domain OCT systems. Of these 15% were in-assessable. Worse than slightly incorrect calibration, was found in 35% of assessable cases. Serious calibration incorrectness was seen in 16% of images. 2) A total of 524 images had been obtained bymarketed frequency domain systems (482 by C7 system and 42 images by Illumien—both St. Jude Medical, USA). In images acquired by the C7 system serious calibration incorrectness was detected in 16% of cases. In images acquired by the Illumien system (42) only a single acquisition with 3 images was severely incorrect calibrated due to inverted calibration. Inverted calibration may cause the depicted catheter to resemble a correct calibrated OCT catheter. This is an occasional finding termed “inverted calibration” (Class 4 error). A related finding due to inverted calibration is the distortion of the image and appearance of vessel wall or wires inside the apparent imaging wire (Fig. 1 error Class 4). We propose the term “inverted calibration artifacts” for such findings. The “slightly incorrect”-group was expanded to contain also the Class 1 categorized images, as the error in these groups only result in minimal error of the measurements. For the C7 system 43% of images in articles presenting quantitative measurements showed any degree of incorrect calibration. For the M2 system, this was 40%. We are aware, that images shown in articles are chosen for illustrative purpose. This is a process different from the systematic core lab evaluation, andwe assume that all results derivedweremade from correctly calibrated images. Still, systematic errors inmany or all images in a paper might induce a slight uncertainty about derived quantitative results. Incorrect calibration in images presented for tissue characterization or similar could be seen as unimportant. Still, when presented in high impact journals, in expert reviews or consensus reports some users might potentially adopt this as the gold standard of calibration. In conclusion, a high incidence of incorrect calibrated images was found in systematic review of peer reviewed publications. Improved calibration facilities by newer generation OCT systems seems to reduce errors though not alleviating the risk associated with not identifying inverted calibration.