Initial Experience of 10 Imaging Vendors with the IHE SHARAZONE: a New Multivendor Peer-to-Peer Test Service for DICOM Objects.

Alignment of DICOM (Digital Imaging and Communications in Medicine) capabilities among vendors is crucial to improve interoperability in the healthcare industry and advance medical imaging 2. However, a sustainable model for sharing DICOM samples is not available. To address this issue, Integrating the Healthcare Enterprise (IHE) has introduced the IHE SHARAZONE, a continuous cross-vendor DICOM data sharing test service. IHE is a highly regarded organization known for profiling standards such as DICOM, HL7 v2 (Health Level Seven, version 2), HL7 CDA (Clinical Document Architecture), and HL7 FHIR (Fast Healthcare Interoperability Resources) into practical solutions for clinical practice. The primary goal of the IHE SHARAZONE is to provide a reliable and consistent cross-vendor DICOM data sharing system. To evaluate its effectiveness, a 5-month pilot was conducted with ten imaging vendors. The pilot concluded with a participant survey, which yielded valuable insights into the initial experience with the IHE SHARAZONE. These findings can inform future improvements and developments to this important service.

[Display Performance of X-ray Image Output from DICOM-embedded Printer to Paper-based Hard Copy Print: Comparison with X-ray Image on LCD].

PURPOSE: We have been using a paper-based hard copy print (paper print) system of X-ray images, in which digital imaging and communications in medicine (DICOM) data can be directly output on papers from medical imaging systems or from a picture archiving and communication system (PACS) server, and they are utilized as patient referral materials or for preoperative planning. The purpose of this study was to compare the display performance of X-ray images on the printed paper and that on the liquid crystal display (LCD). METHODS: We measured contrast response to verify consistency of image appearance on both display systems. The contrast resolution was assessed by a CDRAD phantom. The spatial resolution was assessed by an X-ray test chart. RESULTS: The contrast response of the paper printer was not concordant with the grayscale standard display function (GSDF). The difference between the measured contrast response and the ideal GSDF on the paper was large in the high-density area. The low-contrast resolution on the paper was inferior to that on the LCD. The spatial resolving power on the paper was superior to that on the LCD. CONCLUSION: The display performance of the paper printer for X-ray images was clarified. X-ray images printed on the paper should be used carefully taking account of their characteristics of display performance.

Co-Clinical Imaging Metadata Information (CIMI) for Cancer Research to Promote Open Science, Standardization, and Reproducibility in Preclinical Imaging.

Preclinical imaging is a critical component in translational research with significant complexities in workflow and site differences in deployment. Importantly, the National Cancer Institute's (NCI) precision medicine initiative emphasizes the use of translational co-clinical oncology models to address the biological and molecular bases of cancer prevention and treatment. The use of oncology models, such as patient-derived tumor xenografts (PDX) and genetically engineered mouse models (GEMMs), has ushered in an era of co-clinical trials by which preclinical studies can inform clinical trials and protocols, thus bridging the translational divide in cancer research. Similarly, preclinical imaging fills a translational gap as an enabling technology for translational imaging research. Unlike clinical imaging, where equipment manufacturers strive to meet standards in practice at clinical sites, standards are neither fully developed nor implemented in preclinical imaging. This fundamentally limits the collection and reporting of metadata to qualify preclinical imaging studies, thereby hindering open science and impacting the reproducibility of co-clinical imaging research. To begin to address these issues, the NCI co-clinical imaging research program (CIRP) conducted a survey to identify metadata requirements for reproducible quantitative co-clinical imaging. The enclosed consensus-based report summarizes co-clinical imaging metadata information (CIMI) to support quantitative co-clinical imaging research with broad implications for capturing co-clinical data, enabling interoperability and data sharing, as well as potentially leading to updates to the preclinical Digital Imaging and Communications in Medicine (DICOM) standard.

Semi-automated 18F-FDG PET segmentation methods for tumor volume determination in Non-Hodgkin lymphoma patients: a literature review, implementation and multi-threshold evaluation.

In the treatment of Non-Hodgkin lymphoma (NHL), multiple therapeutic options are available. Improving outcome predictions are essential to optimize treatment. The metabolic active tumor volume (MATV) has shown to be a prognostic factor in NHL. It is usually retrieved using semi-automated thresholding methods based on standardized uptake values (SUV), calculated from 18F-Fluorodeoxyglucose Positron Emission Tomography (18F-FDG PET) images. However, there is currently no consensus method for NHL. The aim of this study was to review literature on different segmentation methods used, and to evaluate selected methods by using an in house created software tool. A software tool, MUltiple SUV Threshold (MUST)-segmenter was developed where tumor locations are identified by placing seed-points on the PET images, followed by subsequent region growing. Based on a literature review, 9 SUV thresholding methods were selected and MATVs were extracted. The MUST-segmenter was utilized in a cohort of 68 patients with NHL. Differences in MATVs were assessed with paired t-tests, and correlations and distributions figures. High variability and significant differences between the MATVs based on different segmentation methods (p < 0.05) were observed in the NHL patients. Median MATVs ranged from 35 to 211 cc. No consensus for determining MATV is available based on the literature. Using the MUST-segmenter with 9 selected SUV thresholding methods, we demonstrated a large and significant variation in MATVs. Identifying the most optimal segmentation method for patients with NHL is essential to further improve predictions of toxicity, response, and treatment outcomes, which can be facilitated by the MUST-segmenter.

Imaging biomarkers to stratify lymph node metastases in abdominal CT - Is radiomics superior to dual-energy material decomposition?

Purpose: To assess the potential of radiomic features in comparison to dual-energy CT (DECT) material decomposition to objectively stratify abdominal lymph node metastases. Materials and methods: In this retrospective study, we included 81 patients (m, 57; median age, 65 (interquartile range, 58.7-73.3) years) with either lymph node metastases (n = 36) or benign lymph nodes (n = 45) who underwent contrast-enhanced abdominal DECT between 06/2015-07/2019. All malignant lymph nodes were classified as unequivocal according to RECIST criteria and confirmed by histopathology, PET-CT or follow-up imaging. Three investigators segmented lymph nodes to extract DECT and radiomics features. Intra-class correlation analysis was applied to stratify a robust feature subset with further feature reduction by Pearson correlation analysis and LASSO. Independent training and testing datasets were applied on four different machine learning models. We calculated the performance metrics and permutation-based feature importance values to increase interpretability of the models. DeLong test was used to compare the top performing models. Results: Distance matrices and t-SNE plots revealed clearer clusters using a combination of DECT and radiomic features compared to DECT features only. Feature reduction by LASSO excluded all DECT features of the combined feature cohort. The top performing radiomic features model (AUC = 1.000; F1 = 1.000; precision = 1.000; Random Forest) was significantly superior to the top performing DECT features model (AUC = 0.942; F1 = 0.762; precision = 0.800; Stochastic Gradient Boosting) (DeLong < 0.001). Conclusion: Imaging biomarkers have the potential to stratify unequivocal lymph node metastases. Radiomics models were superior to DECT material decomposition and may serve as a support tool to facilitate stratification of abdominal lymph node metastases.

Translating Imaging Into 3D Printed Cardiovascular Phantoms: A Systematic Review of Applications, Technologies, and Validation.

Translation of imaging into 3-dimensional (3D) printed patient-specific phantoms (3DPSPs) can help visualize complex cardiovascular anatomy and enable tailoring of therapy. The aim of this paper is to review the entire process of phantom production, including imaging, materials, 3D printing technologies, and the validation of 3DPSPs. A systematic review of published research was conducted using Embase and MEDLINE, including studies that investigated 3DPSPs in cardiovascular medicine. Among 2,534 screened papers, 212 fulfilled inclusion criteria and described 3DPSPs as a valuable adjunct for planning and guiding interventions (n = 108 [51%]), simulation of physiological or pathological conditions (n = 19 [9%]), teaching of health care professionals (n = 23 [11%]), patient education (n = 3 [1.4%]), outcome prediction (n = 6 [2.8%]), or other purposes (n = 53 [25%]). The most common imaging modalities to enable 3D printing were cardiac computed tomography (n = 131 [61.8%]) and cardiac magnetic resonance (n = 26 [12.3%]). The printing process was conducted mostly by material jetting (n = 54 [25.5%]) or stereolithography (n = 43 [20.3%]). The 10 largest studies that evaluated the geometric accuracy of 3DPSPs described a mean bias <±1 mm; however, the validation process was very heterogeneous among the studies. Three-dimensional printed patient-specific phantoms are highly accurate, used for teaching, and applied to guide cardiovascular therapy. Systematic comparison of imaging and printing modalities following a standardized validation process is warranted to allow conclusions on the optimal production process of 3DPSPs in the field of cardiovascular medicine.

An approach for the online determination of Entrance Surface Air Kerma (ESAK) from Kerma Area product (PKA) in digital radiology.

We propose determining the entrance surface air kerma (ESAK) from the kerma area product (PKA) in digital radiology. ESAK values were derived from the X-ray tube outputs and patient exposure factors across five X-ray departments. Using linear regression between ESAK and PKA values, the slope and intercept coefficients were determined for each X-ray equipment and procedure. The method was examined using the data collected from patients who underwent chest PA/LAT, abdomen, pelvic AP, and lumbar spine AP/LAT X-ray examinations. The results showed a highly significant correlation between ESAK and PKA values and correlation coefficients, ranging from 0.77 to 1 with P-value < 0.001 in most studies. This method can be employed by incorporating dose data and related parameters into the X-ray device's software, similar to other dose-displayed information. The online determination of ESAK from PKA could help with quality assurance and patient dose management in digital radiology.

Securing Your Radiology Practice: Evidence-Based Strategies for Radiologists Compiled From 10 Years of Cyberattacks and HIPAA Breaches Involving Medical Imaging.

While there is significant literature discussing physical and cybersecurity risks around health information technology in general, the number of publications that specifically address medical imaging is much smaller, and many of these focus on the technical security requirements for the exchange of medical images over public networks rather than practical guidelines for radiologists and technicians. This study examines the US Department of Health and Human Services database of reported breaches involving medical imaging from 2010-2020, identifies the most common contributing factors to those breaches, and offers recommendations for radiology practices to prevent each, based on the National Institute of Standards and Technology (NIST) guidelines as well as measures proposed in the literature on health information technology.

Quantitative Ultrasound Assessment of Hepatic Steatosis.

Background/Aims: Non-alcoholic fatty liver disease (NAFLD) is widespread chronic disease of the live in humans with the prevalence of 30% of the United States population.1,2 The goal of the study is to validate the performance of quantitative ultrasound algorithms in the assessment of hepatic steatosis in patients with suspected NAFLD. Methods: This prospective study enrolled a total of 31 patients with clinical suspicion of NAFLD to receive liver fat measurements by quantitative ultrasound and reference MRI measurements (proton density fat-fraction, PDFF). The following ultrasound (US) parameters based on both raw ultrasound RF (Radio Frequency) data and 2D B-mode images of the liver were analyzed with subsequent correlation with MRI-PDFF: hepatorenal index, acoustic attenuation coefficient, Nakagami coefficient parameter, shear wave viscosity, shear wave dispersion and shear wave elasticity. Ultrasound parameters were also correlated with the presence of hypertension and diabetes. Results: The mean (± SD) age and body mass index of the patients were 49.03 (± 12.49) and 30.12 (± 6.15), respectively. Of the aforementioned ultrasound parameters, the hepatorenal index and acoustic attenuation coefficient showed a strong correlation with MRI-PDFF derivations of hepatic steatosis, with r-values of 0.829 and 0.765, respectively. None of the remaining US parameters showed strong correlations with PDFF. Significant differences in Nakagami parameters and acoustic attenuation coefficients were found in those patients with and without hypertension. Conclusions: Hepatorenal index and acoustic attenuation coefficient correlate well with MRI-PDFF-derived measurements of hepatic steatosis. Quantitative ultrasound is a promising tool for the diagnosis and assessment of patients with NAFLD.

Portal vein recanalisation alone to treat severe portal hypertension in non-cirrhotic patients with chronic extrahepatic portal vein obstruction.

Background & Aims: We aimed to evaluate long-term outcome of patients with chronic non-cirrhotic extrahepatic portal vein obstruction (CNC-EHPVO) who underwent portal vein recanalisation (PVR) without transjugular intrahepatic portosystemic shunt (TIPS) insertion and to determine factors predicting PVR failure and stent occlusion. Methods: This retrospective monocentric study included all patients who underwent PVR without TIPS insertion in the context of CNC-EHPVO between the years 2000 and 2019. Primary patency was defined by the absence of a complete stent occlusion on follow-up imaging. Results: A total of 31 patients underwent PVR with a median follow-up of 52 months (24-82 months). Indications were gastrointestinal bleeding (n = 13), abdominal pain attributed to CNC-EHPVO (n = 7), prior to abdominal surgery (n = 4), and others (n = 7). Technical success was obtained in 27 patients. PVR failure was associated with extension within the intrahepatic portal veins (p = 0.005) and recanalisation for abdominal pain (p = 0.02). Adverse events occurred in 6 patients with no mortality. Anticoagulation was administered in 21 patients after technical success of PVR. In patients with technical success, 5-year primary patency was 73% and was associated with improved muscle mass (p = 0.007) and decreased spleen volume (p = 0.01) at 1 year. Furthermore, 21 (78%) patients with PVR technical success were free of portal hypertension complication at 5 years. Conclusions: PVR without TIPS insertion was feasible and safe in selected patients with CNC-EHPVO and portal hypertension with past or expected complications. Primary patency at 5 years was obtained in 3 of 4 patients with technical success of PVR and was associated with a control of complications of CNC-EHPVO. PVR was associated with improvement of sarcopenia and decreased spleen volume at 1 year. Lay summary: Patients with chronic obstruction of the portal vein and without cirrhosis or malignancy can develop complications related to the high pressure in the venous system. The present study reports long-term favourable outcome of patients in whom the obstruction was treated with stents.

Methodology of thermal drift measurements for surface guided radiation therapy systems and clinical impact assessment illustrated on the C-Rad Catalyst+ HD system.

Thermal drift of optical systems employed for surface guided radiation therapy (SGRT) adds uncertainty to patient setup and monitoring. This work describes methods to measure the drift of individual camera pods as well as the drift of the combined clinical signal. It presents results for four clinical C-Rad Catalyst+ HD systems. Based on the measured clinical drift, recipes are provided on how to calculate relevant uncertainties in patient setup and patient position monitoring with SGRT. Strategies to reduce the impact of drift are explained. While the results are specific to the systems investigated, the methodology is transferable and the clinical recipes are universally applicable.

Artificial intelligence in liver diseases: Improving diagnostics, prognostics and response prediction.

Clinical routine in hepatology involves the diagnosis and treatment of a wide spectrum of metabolic, infectious, autoimmune and neoplastic diseases. Clinicians integrate qualitative and quantitative information from multiple data sources to make a diagnosis, prognosticate the disease course, and recommend a treatment. In the last 5 years, advances in artificial intelligence (AI), particularly in deep learning, have made it possible to extract clinically relevant information from complex and diverse clinical datasets. In particular, histopathology and radiology image data contain diagnostic, prognostic and predictive information which AI can extract. Ultimately, such AI systems could be implemented in clinical routine as decision support tools. However, in the context of hepatology, this requires further large-scale clinical validation and regulatory approval. Herein, we summarise the state of the art in AI in hepatology with a particular focus on histopathology and radiology data. We present a roadmap for the further development of novel biomarkers in hepatology and outline critical obstacles which need to be overcome.

Effectiveness of digital data acquisition technologies in the fabrication of maxillofacial prostheses - A systematic review.

OBJECTIVE: The systematic review was designed to review and analyze the outcomes of various digital data acquisition technologies used for treatment planning in the prosthetic rehabilitation of maxillofacial defects. METHODS: The review protocol was registered in PROSPERO data with registration number: CRD42020188415. The PICOS inclusion criteria was employed in the systematic review. An electronic search (PubMed, databases) yielded twenty-eight eligible case reports. The qualitative methodological assessment was done according to an article that provided criteria for special considerations in evaluating case reports. It consisted of four questions, each carrying grading of 0, 1, and 2. During the full-text screening, the reviewers shortlisted six outcomes (time, aesthetics, cost, dimensional accuracy, patient satisfaction, and fabrication process) and graded (0, 1, 3) according to the outcomes they met. RESULTS: The majority of the included case reports used LASER scanners. Auricular and orbital defects were the highest reported cases. In nasal and orbital defects, the mean outcome of the shorter time required for the fabrication was the highest. In auricular prostheses, the mean outcome of dimensional accuracy was highest. In facial prostheses, aesthetics, dimensional accuracy, and patient satisfaction had the highest mean outcome whereas, in obturators, the shorter time required, dimensional accuracy, and patient satisfaction had the highest mean outcome. A total of 18 studies were graded as highly significant studies according to the methodological qualitative assessment. CONCLUSION: LASER scanning systems in nasal prostheses, LASER scanners and combination of CT scan and digital photography in auricular prostheses, digital photography and stereophotogrammetry in case of large facial defects and combination of MRI and CT scan for obturators appeared to be a superior method of digital data acquisition.

A New Method of Intracranial Aneurysm Modeling for Stereolithography Apparatus 3D Printer: The "Wall-Carving Technique" Using Digital Imaging and Communications in Medicine Data.

OBJECTIVE: To assess the ability of the "wall-carving (WC) image technique", which uses vascular images from 3-dimensional digital subtraction angiograms (3DDSAs). Also, to verify the accuracy of the resulting 3D-printed hollow models of intracranial aneurysms. METHODS: The 3DDSA data from 9 aneurysms were processed to obtain volumetric models suitable for the stereolithography apparatus. The resulting models were filled with iodinated contrast media. 3D rotational angiography of the models was carried out, and the aneurysm geometry was compared with the original patient data. The accuracy of the 3D-printed hollow models' sizes and shapes was evaluated using the nonparametric Wilcoxon signed-rank test and the Dice coefficient index. RESULTS: The aneurysm volumes ranged from 34.1 to 4609.8 mm3 (maximum diameters 5.1-30.1 mm), and no statistically significant differences were noted between the patient data and the 3D-printed models (P = 0.4). Shape analysis of the aneurysms and related arteries indicated a high level of accuracy (Dice coefficient index value: 88.7%-97.3%; mean ± SD: 93.6% ± 2.5%). The vessel wall thickness of the 3D-printed hollow models was 0.4 mm for the parent and 0.2 mm for small branches and aneurysms, almost the same as the patient data. CONCLUSIONS: The WC technique, which involves volume rendering of 3DDSAs, can provide a detailed description of the contrast enhancement of intracranial vessels and aneurysms at arbitrary depths. These models can provide precise anatomic information and be used for simulations of endovascular treatment.

Quality assurance of dysphagia-optimised intensity modulated radiotherapy treatment planning for head and neck cancer.

This study aimed to assess the impact of the margin applied to the clinical target volume, to create the planning target volume, on plan quality of a novel dysphagia-optimised intensity modulated radiotherapy technique developed within a head and neck cancer multicentre randomised controlled trial. Protocol compliant plans were used for a single benchmark planning case. Larger margins were associated with higher doses to adjacent organs at risk, particularly the inferior pharyngeal constrictor muscle, but coincided with some improved low dose target coverage. A 3 mm margin is recommended for this technique if local practices allow.

[Structured reporting in radiology : IT essentials]. / Strukturierte Befundung in der Radiologie : IT-Essentials.

A clinically meaningful use of structured reporting, which in the opinion of numerous scientific societies and experts is a very important prerequisite for the further development of radiological findings, especially under quality aspects, requires corresponding standards for implementation in IT systems. In addition to DICOM ("digital imaging and communication in medicine"), these are other standards for coding, for example RadLex ("radiological lexicon") or the specification of so-called interoperability profiles, as they are being developed by IHE ("integrating the healthcare enterprise"). The management of radiology report templates (MRRT) profiles is the central building block for this. The building blocks for efficient IT implementation, which also allow harmonization, for example at a national level, are currently available. Users in radiology should familiarize themselves with them and demand appropriate solutions from manufacturers.

Prediction of treatment response to transarterial radioembolization of liver metastases: Radiomics analysis of pre-treatment cone-beam CT: A proof of concept study.

PURPOSE: To investigate the potential of texture analysis and machine learning to predict treatment response to transarterial radioembolization (TARE) on pre-interventional cone-beam computed tomography (CBCT) images in patients with liver metastases. MATERIALS AND METHODS: In this IRB-approved retrospective single-center study 36 patients with a total of 104 liver metastases (56 % male, mean age 61.1 ± 13 years) underwent CBCT prior to TARE and follow-up imaging 6 months after therapy. Treatment response was evaluated according to RECIST version 1.1 and dichotomized into disease control (partial response/stable disease) versus disease progression (progressive disease). After target lesion segmentation, 104 radiomics features corresponding to seven different feature classes were extracted with the pyRadiomics package. After dimension reduction machine learning classifications were performed on a custom artificial neural network (ANN). Ten-fold cross validation on a previously unseen test data set was performed. RESULTS: The average administered cumulative activity from TARE was 1.6 Gbq (± 0.5 Gbq). At a mean follow-up of 5.9 ± 0.8 months disease control was achieved in 82 % of metastases. After dimension reduction, 15 of 104 (15 %) texture analysis features remained for further analysis. On a previously unseen set of liver metastases the Multilayer Perceptron ANN yielded a sensitivity of 94.2 %, specificity of 67.7 % and an area-under-the receiver operating characteristics curve of 0.85. CONCLUSION: Our study indicates that texture analysis-based machine learning may has potential to predict treatment response to TARE using pre-treatment CBCT images of patients with liver metastases with high accuracy.

A DICOM Framework for Machine Learning and Processing Pipelines Against Real-time Radiology Images.

Real-time execution of machine learning (ML) pipelines on radiology images is difficult due to limited computing resources in clinical environments, whereas running them in research clusters requires efficient data transfer capabilities. We developed Niffler, an open-source Digital Imaging and Communications in Medicine (DICOM) framework that enables ML and processing pipelines in research clusters by efficiently retrieving images from the hospitals' PACS and extracting the metadata from the images. We deployed Niffler at our institution (Emory Healthcare, the largest healthcare network in the state of Georgia) and retrieved data from 715 scanners spanning 12 sites, up to 350 GB/day continuously in real-time as a DICOM data stream over the past 2 years. We also used Niffler to retrieve images bulk on-demand based on user-provided filters to facilitate several research projects. This paper presents the architecture and three such use cases of Niffler. First, we executed an IVC filter detection and segmentation pipeline on abdominal radiographs in real-time, which was able to classify 989 test images with an accuracy of 96.0%. Second, we applied the Niffler Metadata Extractor to understand the operational efficiency of individual MRI systems based on calculated metrics. We benchmarked the accuracy of the calculated exam time windows by comparing Niffler against the Clinical Data Warehouse (CDW). Niffler accurately identified the scanners' examination timeframes and idling times, whereas CDW falsely depicted several exam overlaps due to human errors. Third, with metadata extracted from the images by Niffler, we identified scanners with misconfigured time and reconfigured five scanners. Our evaluations highlight how Niffler enables real-time ML and processing pipelines in a research cluster.

The Use of a 3D Printing Model in Planning a Donor Hepatectomy for Living Donor Liver Transplantation: First in India.

INTRODUCTION: Three-dimensional (3D) anatomical relationships between the hepatic veins and portal structures can serve as a guide to plan resections in donor hepatectomy during living donor liver transplantation. We present the first case report from India on the use of a 3D printed liver model, as an assist to living donor liver transplantation. METHODS: A 3D model of the donor liver with hepatic venous structures printed within it was prepared using image acquisition data. The model was used for a simulated cut preoperatively, to mimic the donor hepatectomy based on the venous structures seen through the transparent material used for making the liver model. The volume of the graft measured by volume displacement in the actual surgery was compared with the volume of the model after the simulated cut. RESULTS: The calculated volume of the graft was 359 ml as per the preoperative simulation, and the observed weight/volume was 380 gm/310 ml. CONCLUSION: Three-dimensional printing of liver models using imaging data can help predict the actual size of the graft after donor hepatectomy, in patients undergoing living donor liver transplantation.

Dicom_wsi: A Python Implementation for Converting Whole-Slide Images to Digital Imaging and Communications in Medicine Compliant Files.

BACKGROUND: Adoption of the Digital Imaging and Communications in Medicine (DICOM) standard for whole slide images (WSIs) has been slow, despite significant time and effort by standards curators. One reason for the lack of adoption is that there are few tools which exist that can meet the requirements of WSIs, given an evolving ecosystem of best practices for implementation. Eventually, vendors will conform to the specification to ensure enterprise interoperability, but what about archived slides? Millions of slides have been scanned in various proprietary formats, many with examples of rare histologies. Our hypothesis is that if users and developers had access to easy to use tools for migrating proprietary formats to the open DICOM standard, then more tools would be developed as DICOM first implementations. METHODS: The technology we present here is dicom_wsi, a Python based toolkit for converting any slide capable of being read by the OpenSlide library into DICOM conformant and validated implementations. Moreover, additional postprocessing such as background removal, digital transformations (e.g., ink removal), and annotation storage are also described. dicom_wsi is a free and open source implementation that anyone can use or modify to meet their specific purposes. RESULTS: We compare the output of dicom_wsi to two other existing implementations of WSI to DICOM converters and also validate the images using DICOM capable image viewers. CONCLUSION: dicom_wsi represents the first step in a long process of DICOM adoption for WSI. It is the first open source implementation released in the developer friendly Python programming language and can be freely downloaded at .