Search Results (211)

Background/Objectives: Tenosynovitis is a common feature of psoriatic arthritis (PsA) and is typically assessed using semi-quantitative magnetic resonance imaging (MRI) scoring. However, visual scoring s variability. This study evaluates a fully automated, deep-learning approach for ankle tenosynovitis segmentation and volume-based quantification from MRI in psoriatic arthritis (PsA) patients. Methods: We analyzed 364 ankle 3T MRI scans from 71 PsA patients. Four tenosynovitis pathologies were manually scored and used to create ground truth segmentations through a human–machine workflow. For each pathology, 30 annotated scans were used to train a deep-learning segmentation model based on the nnUNet framework, and 20 scans were used for testing, ensuring patient-level disjoint sets. Model performance was evaluated using Dice scores. Volumetric pathology measurements from test scans were compared to radiologist scores using Spearman correlation. Additionally, 218 serial MRI pairs were assessed to analyze the relationship between changes in pathology volume and changes in visual scores. Results: The segmentation model achieved promising performance on the test set, with mean Dice scores ranging from 0.84 to 0.92. Pathology volumes correlated with visual scores across all test MRIs (Spearman ρ = 0.52–0.62). Volume-based quantification captured changes in inflammation over time and identified subtle progression not reflected in semi-quantitative scores. Conclusions: Our automated segmentation tool enables fast and accurate quantification of ankle tenosynovitis in PsA patients. It may enhance sensitivity to disease progression and complement visual scoring through continuous, volume-based metrics. Full article

In this article, we present a case of a 49-year-old woman presenting with a recurrent metastatic neuroendocrine tumor. Background: Insulinomas are neuroendocrine tumors derived from beta cells of the pancreas that secrete insulin. Usually, they are benign tumors; however, metastatic insulinomas are an extremely rare malignant form of these tumors, carrying a significantly worse prognosis. Case Presentation: A 49-year-old woman, a patient in the University Hospital in Wroclaw in the Department of Endocrinology, Diabetes and Isotope Therapy, first presented with abdominal pain in 2009, when ultrasound and further examination led to the diagnosis of a tumor in the pancreas (a solid pseudopapillary tumor of the pancreas—meta NET G2), and the patient underwent distal pancreatectomy with splenectomy. For ten years, she was under observation, and her symptoms, such as abdominal pain, nausea, weight loss, and general weakness, reappeared in 2019. Then, magnetic resonance imaging (MRI) showed a lesion in the liver, and further histopathology revealed neuroendocrine tumor (NET) metastasis to the liver. In 2022, the patient presented with loss of consciousness and convulsion, loss of weight, and hypoglycemia after meals. In April 2022, the daily glycemic profile was recorded and a 72 h fasting test was performed; however, their results excluded insulinoma. Positron emission tomography–computed tomography (PET-CT) with 18F-fluorodeoxyglucose (18F-FDG) and PET with gallium-68-DOTA-(Tyr3)-octreotate (68Ga-DOTA-TATE) showed a metastatic proliferative process in the liver. Persistent hypoglycemia led to another hospitalization in May 2022, and repeated tests allowed for the diagnosis of insulinoma. Treatment with somatostatin analogs and diazoxide was started. A CT scan in November 2022 and a PET scan in January 2023 showed new metastases to the liver, bones, and cervical lymph nodes, and it was decided to intensify the treatment. In May 2023, the patient was qualified for Lutathera treatment for insulinoma at the University Clinical Hospital in Poznań. In June 2023, another disturbing symptom was reported by the patient, a painful lump in the breast. During diagnostics, metastases with high proliferation markers were found in both breasts. Two months later, in August 2023, the patient received another dose of Lutathera. In October 2023, significant progression of liver lesions, metastases to bones of the spine, ribs, and pelvis, and periaortic and pelvic lymphadenopathy were found as well as elevated values of neuron-specific enolase and calcitonin. The patient was also referred to the Palliative Medicine Home Hospice. In consultation with the Lower Silesian Cancer Center, the decision was made to forgo further treatment with PRRT and initiate systemic chemotherapy. Despite the chosen treatment, the patient died on 27/DEC/2023. Conclusions: This case report can serve clinicians, as it presents a case of an extremely rare and insidious tumor, metastatic insulinoma. Full article

Blast-induced mild traumatic brain injury (mTBI) occurs when shock waves travel through blood vessels and cerebrospinal fluid, leading to cerebral demyelination, which results in cognitive impairments and neuropsychiatric issues that impact quality of life. This study aims to evaluate myelin changes in white matter in mice with mTBI induced by an open-field low-intensity blast (LIB) using a newly implemented 3D adiabatic T1ρ prepared fast spin echo (Adiab-T1ρ-FSE) sequence for quantitative T1ρ MRI mapping. Thirty male C57BL/6 mice, including 15 mTBI and 15 sham controls, were scanned on a 3T Bruker MRI scanner. Luxol fast blue (LFB) staining was performed to assess myelin content differences between the mTBI and sham control groups. A significantly higher T1ρ value in the medial corpus callosum (MCC) was found in mTBI mice compared to controls (126.8 ± 2.5 ms vs. 129.8 ± 2.5 ms; p < 0.001), consistent with the reduced myelin observed in LFB staining (0.80 ± 0.14 vs. 1.02 ± 0.06; p = 0.004). Moreover, a significant negative correlation between T1ρ and histological myelin content measurements was observed (r = −0.57, p = 0.02). Our findings demonstrate that T1ρ is a promising biomarker for detecting mTBI-associated demyelination in the brain. Full article

Objectives: The diagnostics of chronic kidney disease (CKD) consist of three basic groups of examinations: laboratory tests, radiological imaging and histopathological examinations. However, in the most severe clinical cases, where a fast, undisputed decision is required, histopathological tests are the only suitable option. Unfortunately, such tests require an invasive kidney biopsy, which is not possible in many patients. The aim of this study is to create an algorithm that can categorize CKD patients into active and non-active phases on the basis of MRI texture analysis and compare the results with histopathological examinations. Methods: MRI examinations were performed on healthy volunteers (group 1, N = 14) and CKD patients who also received kidney biopsy. The histopathological examination was used to divide the patients into active phase CKD (group 2, N = 58) and non-active phase CKD (group 3, N = 22). The T2-weighted MRI images were analyzed using a Support Vector Machine (SVM) model created with qMazDa software, which was trained to classify images into the appropriate group of CKD activity. Results: The following evaluation metrics were calculated for the final SVM models corresponding to confusion matrices: for texture analysis—balanced accuracy 81.6%, sensitivity 68.2–92.0%, specificity 82.5–97.5% and precision 62.5–95.8%; for texture and shape analysis—balanced accuracy 87.3%, sensitivity 77.3–100.0%, specificity 87.5–100.0% and precision 65.4–100.0%. Conclusions: Texture analysis of T2-weighted images associated with kidney shape features seems to be reliable method of assessing the state of ongoing CKD. Full article

Objective: The purpose of this study was to evaluate the accuracy and feasibility of magnetic resonance (MR)-guided periradicular nerve root injection therapy (PRT) using a 0.55 T magnetic resonance imaging (MRI) system with fast dynamic imaging in a phantom. Methods: Five radiologists with varying levels of experience in PRT performed nine randomly assigned PRT procedures: three under MR guidance, three under CT guidance using a fully integrated laser navigation system, and three under conventional CT guidance, all on a specialized phantom of the lumbar spine. The PRTs were assessed by two experienced neuroradiologists with expertise in interventions, using a scale of 1–5, as follows: 5 = excellent to very good, 4 = good, 3 = satisfactory 2 = bad, 1 = very bad. The puncture time and total intervention time were noted. Results: All procedures were technically successful. The subjective evaluation of the PRTs showed similar results with a median of 5 for all three guidance systems. Additionally, there was no significant difference with respect to pure puncture time (the period after needle path determination) among all PRTs (Mean ± SD): MR-guided 178 ± 117 s, CT-guided with laser system 186 ± 73 s, and the conventional CT-guided 218 ± 91 s (p = 0.482). However, the total procedure time including planning images was significantly higher for MR-guided PRT (700 ± 182 s) compared to CT guidance with laser system (366 ± 85 s) and conventional CT guidance (358 ± 150 s; p = 0.012). Conclusions: Real-time MRI-guided lumbosacral periradicular injection therapy utilizing a 0.55 T MRI system is feasible with similar puncture times to CT guidance but consumes more intervention time due to the duration of planning sequences. Limitation: The study utilized a stationary phantom made of homogeneous material, which provides an incomplete representation of real tissue properties and motion complexity applied to human beings. Full article

Motion correction in magnetic resonance imaging (MRI) has become increasingly complex due to the high computational demands of iterative reconstruction algorithms and the heterogeneity of emerging computing platforms. However, the clinical applicability of these methods requires fast processing to ensure rapid and accurate diagnostics. Graphics processing units (GPUs) have demonstrated substantial performance gains in various reconstruction tasks. In this work, we present a GPU implementation of the reconstruction kernel for the generalized reconstruction by inversion of coupled systems (GRICS), an iterative joint optimization approach that enables 3D high-resolution image reconstruction with motion correction. Three implementations were compared: (i) a C++ CPU version, (ii) a Matlab–GPU version (with minimal code modifications allowing data storage in GPU memory), and (iii) a native GPU version using CUDA. Six distinct datasets, including various motion types, were tested. The results showed that the Matlab–GPU approach achieved speedups ranging from 1.2× to 2.0× compared to the CPU implementation, whereas the native CUDA version attained speedups of 9.7× to 13.9×. Across all datasets, the normalized root mean square error (NRMSE) remained on the order of ${10}^{-6}$ to ${10}^{-4}$, indicating that the CUDA-accelerated method preserved image quality. Furthermore, a roofline analysis was conducted to quantify the kernel’s performance on one of the evaluated datasets. The kernel achieved 250 GFLOP/s, representing a 15.6× improvement over the performance of the Matlab–GPU version. These results confirm that GPU-based implementations of GRICS can drastically reduce reconstruction times while maintaining diagnostic fidelity, paving the way for more efficient clinical motion-compensated MRI workflows. Full article

Real-time tumor-tracked radiotherapy with a linear accelerator-magnetic resonance (linac-MR) hybrid system requires accurate tumor delineation at a fast MR imaging rate. Various autocontouring methods have been previously evaluated against “gold standard” manual contours by experts. However, manually drawn contours have inherent intra- and inter-observer variations. We aim to quantify these variations and evaluate our tumor-autocontouring algorithm against the manual contours. Ten liver, ten prostate, and ten lung cancer patients were scanned using a 3 tesla (T) magnetic resonance imaging (MRI) scanner with a 2D balanced steady-state free precession (bSSFP) sequence at 4 frames/s. Three experts manually contoured the tumor in two sessions. For autocontouring, an in-house built U-Net-based autocontouring algorithm was used, whose hyperparameters were optimized for each patient, expert, and session (PES). For evaluation, (A) Automatic vs. Manual and (B) Manual vs. Manual contour comparisons were performed. For (A) and (B), three types of comparisons were performed: (a) same expert same session, (b) same expert different session, and (c) different experts, using Dice coefficient (DC), centroid displacement (CD), and the Hausdorff distance (HD). For (A), the algorithm was trained using one expert’s contours and its autocontours were compared to contours from (a)–(c). For Automatic vs. Manual evaluations (Aa–Ac), DC = 0.91, 0.86, 0.78, CD = 1.3, 1.8, 2.7 mm, and HD = 3.1, 4.6, 7.0 mm averaged over 30 patients were achieved, respectively. For Manual vs. Manual evaluations (Ba–Bc), DC = 1.00, 0.85, 0.77, CD = 0.0, 2.1, 2.8 mm, and HD = 0.0, 4.9, 7.2 mm were achieved, respectively. We have quantified the intra- and inter-observer variations in manual contouring of liver, prostate, and lung patients. Our PES-specific optimized algorithm generated autocontours with agreement levels comparable to these manual variations, but with high efficiency (54 ms/autocontour vs. 9 s/manual contour). Full article

Linear accelerator–magnetic resonance (linac-MR) hybrid systems allow for real-time magnetic resonance imaging (MRI)-guided radiotherapy for more accurate dose delivery to the tumor and improved sparing of the adjacent healthy tissues. However, for real-time tumor detection, it is unfeasible for a human expert to manually contour (gold standard) the tumor at the fast imaging rate of a linac-MR. This study aims to develop a neural network-based tumor autocontouring algorithm with patient-specific hyperparameter optimization (HPO) and to validate its contouring accuracy using in vivo MR images of cancer patients. Two-dimensional (2D) intrafractional MR images were acquired at 4 frames/s using 3 tesla (T) MRI from 11 liver, 24 prostate, and 12 lung cancer patients. A U-Net architecture was applied for tumor autocontouring and was further enhanced by implementing HPO using the Covariance Matrix Adaptation Evolution Strategy. Six hyperparameters were optimized for each patient, for which intrafractional images and experts’ manual contours were input into the algorithm to find the optimal set of hyperparameters. For evaluation, Dice’s coefficient (DC), centroid displacement (CD), and Hausdorff distance (HD) were computed between the manual contours and autocontours. The performance of the algorithm was benchmarked against two standardized autosegmentation methods: non-optimized U-Net and nnU-Net. For the proposed algorithm, the mean (standard deviation) DC, CD, and HD of the 47 patients were 0.92 (0.04), 1.35 (1.03), and 3.63 (2.17) mm, respectively. Compared to the two benchmarking autosegmentation methods, the proposed algorithm achieved the best overall performance in terms of contouring accuracy and speed. This work presents the first tumor autocontouring algorithm applicable to the intrafractional MR images of liver and prostate cancer patients for real-time tumor-tracked radiotherapy. The proposed algorithm performs patient-specific HPO, enabling accurate tumor delineation comparable to that of experts. Full article

Goal: This study evaluates the feasibility and outcome of a personalized MRI-based liver SBRT treatment planning platform with the SPION contrast agent Ferumoxytol^® (Sandoz Inc.; Princeton, NJ, USA) to maintain a superior real-time visualization of liver tumors and volumes of functional hepatic parenchyma for radiotherapy planning throughout multi-fractionated liver SBRT with online plan adaptations on an Elekta Unity 1.5 T MR-Linac (Elekta; Stockholm, Sweden). Materials and Methods: Patients underwent SPION-enhanced MRI on the Elekta Unity MR-Linac for improved tumor and functional hepatic parenchyma visualization. An automated contouring algorithm was applied for the delineation and subsequent guided avoidance of functional liver parenchyma volumes (FLVs) on the SPION-enhanced MR-Linac. Radiation dose constraints were adapted exclusively to FLV. Local control, toxicity, and survival were assessed with at least 6-month radiographic follow-up. Pre- and post-transplant outcomes were analyzed in the subset of patients with HCC and hepatic cirrhosis who completed SBRT as a bridge to liver transplant. Model of End-Stage Liver Disease (MELD-Na) was used to score hepatic function before and after SBRT. Results: With a median follow-up of 23 months (range: 3–40 months), 23 HCC patients (26 lesions treated) and 9 patients (14 lesions treated) with hepatic metastases received SBRT (mean dose: 48 Gy, range: 36–54 Gy) in 1–5 fractions. Nearly all patients in this study had pe-existing liver conditions, including hepatic cirrhosis (23), prior TACE (7), prior SBRT (18), or history of hepatic resection (2). Compared to the non-contrast images, SPIONs improved tumor visibility on post-SPION images on the background of negatively enhancing functionally active hepatic parenchyma. Prolonged SPION-contrast retention within hepatic parenchyma enabled per-fraction treatment adaptation throughout the entire multi-fraction treatment course. FLV loss (53%, p < 0.0001) was observed in cirrhotic patients, but functional and anatomic liver volumes remained consistent in non-cirrhotic patients. Mean dose to FLV was maintained within the liver threshold tolerance to radiation in all patients after the optimization of Step-and-Shoot Intensity-Modulated Radiotherapy (SS-IMRT) on the SPION-enhanced MRI-Linac. No radiation-induced liver disease was observed within 6 months post-SBRT, and the MELD-Na score in cirrhotic patients was not significantly elevated at 3-month intervals after SBRT completion. Conclusions: SPION Ferumoxytol^® administered intravenously as an alternative MRI contrast agent on the day of SBRT planning produces a long-lasting contrast effect between tumors and functional hepatic parenchyma for precision targeting and guided avoidance during the entire course of liver SBRT, enabling fast and accurate online plan adaptation on the 1.5 T Elekta Unity MR-Linac. This approach demonstrates a safe and effective bridging therapy for patients with hepatic cirrhosis, leading to low toxicity and favorable transplant outcomes. Full article

Hippocampal segmentation is essential in neuroimaging for evaluating conditions like Alzheimer’s dementia and mesial temporal sclerosis, where small volume changes can significantly impact normative percentiles. However, inaccurate segmentation is common due to the inclusion of non-hippocampal structures such as choroid plexus and cerebrospinal fluid (CSF), leading to volumetric overestimation and confounding of functional analyses. Current methods of assessment largely rely on virtual or manual ground truth labels, which can fail to capture these inaccuracies. To address this shortcoming, this study introduces a more direct voxel intensity-based method of segmentation assessment. Using paired precontrast and postcontrast T1-weighted MRIs, hippocampal segmentations were refined by adding marginal gray matter and removing marginal CSF and enhancement to determine a total required correction volume. Six segmentation algorithms—e2dhipseg, HippMapp3r, hippodeep, AssemblyNet, FastSurfer, and QuickNat—were implemented and compared. HippMapp3r and e2dhipseg, followed closely by hippodeep, exhibited the least total correction volumes, indicating superior accuracy. Dedicated hippocampal segmentation algorithms outperformed whole-brain methods. Full article

Mitochondrial 3-hydroxy-3-methylglutaryl-CoA synthase deficiency (HMGCS2D) is a rare metabolic disorder that impairs the body’s ability to produce ketone bodies and regulate energy metabolism. Diagnosing HMGCS2D is challenging because patients typically remain asymptomatic unless they experience fasting or illness. Due to the absence of reliable biochemical markers, genetic testing has become the definitive method for diagnosing HMGCS2D. This study included 19 patients from 14 unrelated families diagnosed with HMGCS2D in our department between October 2018 and October 2024. The clinical presentations, biochemical findings, molecular characteristics, and management strategies were systematically summarized and analyzed. Of the 19 cases studied, 16 were symptomatic, and 3 were asymptomatic. The onset of the first acute episode occurred between 10 days and 28 months of age. Triggers for the initial crisis in the symptomatic cases included poor feeding (93.8%), vomiting (56.3%), diarrhea (25.0%), and fever (18.8%). Clinical manifestations during the first episode were lethargy/coma (81.3%), rapid breathing (68.8%), hepatomegaly (56.3%), shock (37.5%), and seizures (18.8%). The biochemical abnormalities observed included elevated plasma transaminases (100%), metabolic acidosis (75%), hypoglycemia (56.3%), and elevated plasma ammonia levels (31.3%). Additionally, low free carnitine levels were found in seven cases, elevated C2 levels were found in one case, dicarboxylic aciduria was found in two cases, and ketonuria was found in two cases. Abnormal brain MRI findings were detected in three patients. Genetic analysis revealed seven HMGCS2 gene variants across the 19 cases. Notably, a novel variant, c.407A>T (p.D136V), was identified and has not been reported in any existing databases. Two common variants, c.559+1G>A and c.1090T>A (p.F364I), were present in 11 out of 19 cases (57.9%) and 10 out of 19 cases (55.5%), respectively. The implementation of a high glucose infusion and proactive management strategies—such as preventing prolonged fasting and providing enteral carbohydrate/glucose infusion during illness—effectively reduced the rate of acute relapses following accurate diagnosis. Currently, all 19 patients are alive, with ages ranging from 5 months to 14 years, and exhibit normal physical development. To the best of our knowledge, this study represents the first reported cases of HMGCS2D in Vietnamese patients. Our findings contribute to a broader understanding of the clinical phenotype and expand the known spectrum of HMGCS2 gene variants, enhancing current knowledge of this rare metabolic disorder. Full article

Background: Hypoglycemia in the case of persons without diabetes is a rare event, being usually, initially misinterpreted based on the symptoms that can mimic various diseases, especially of a neuro-psychiatric nature. In the case of the identification of insulin-mediated hypoglycemia, the evaluation of pancreatic neuroendocrine tumors, which represent the most common and worrisome causes of non-diabetic insulin-mediated hypoglycemia, must be considered. Case Report: We present the case of a 57-year-old patient, hospitalized for a history of approximately one month of recurrent episodes of symptoms suggestive for severe hypoglycemia. The biological evaluation performed during an episode of hypoglycemia showed a plasma glucose value of 44 mg/dL, insulinemia 16.3 µU/mL, C peptide 3.72 ng/mL, HbA1c 4.99%, absence of urinary ketone bodies and anti-insulin antibodies <0.03 U/mL. The CT and MRI examination showed a 15.3/15 mm rounded tumor in the pancreatic corporeo-caudal region. The pancreatic tumor formation was enucleated and the histopathological and immunohistochemical analysis confirmed the diagnosis of the pancreatic neuroendocrine tumor with a positive reaction for chromogranin A, synaptophysin and insulin, without malignancy features (Ki 67 positive in 1% of the tumor cells). The postoperative evolution was favorable, without episodes of hypoglycemia, the fasting insulinemia one day after surgery being 4.1 µU/mL and HbA1c at three weeks postoperatively being 5.51%. Conclusions: The management of patients with hyperinsulinemic hypoglycemia secondary to insulinoma involves multidisciplinary collaboration with an important role in recognizing symptoms suggestive of hypoglycemia in a person without diabetes, initiating biological and imaging evaluation, establishing the optimal therapeutic option and histopathological confirmation. Full article

Background and Objectives: This study aimed to identify asymptomatic brain lesions in patients with β-thalassemia major (TM) and sickle cell anemia (SCA) and evaluate the correlation of these lesions with factors such as splenectomy, thrombocytosis, and blood transfusions. Materials and Methods: A total of 26 patients with thalassemia major and 23 patients with sickle cell anemia were included. Ischemic lesions were categorized as lacunar, small vessel, or multifocal. Variables including age, years of education, presence and type of MRI-detected ischemia, smoking status, hemoglobin, hematocrit, platelet count, ferritin levels, vitamin B12 levels, fasting blood sugar, splenectomy status, chelation therapy, and hydroxyurea treatment were compared between the two groups. Results: The mean age was 27.33 years in the thalassemia major group and 32.65 years in the sickle cell anemia group (p = 0.010). No statistically significant difference was observed in the distribution of ischemia types between the groups (p = 0.303). The thalassemia major group had a lower mean hemoglobin level (8.37 g/dL) compared to the sickle cell anemia group (9.57 g/dL) (p = 0.003). Ferritin levels were significantly higher in the thalassemia major group (2018.92 ng/mL) than in the sickle cell anemia group (660.39 ng/mL) (p < 0.001). Conclusions: Although ischemic lesions were more frequently observed in patients with sickle cell anemia, the difference was not statistically significant. These findings emphasize the importance of ongoing surveillance and individualized management to mitigate cerebrovascular risks in both patient populations. Full article

Background/Objectives: Accurate and reproducible spleen volume measurements are essential for assessing treatment response and disease progression in myelofibrosis. This study evaluates techniques for measuring spleen volume on abdominal MRI. Methods: In 20 patients with bone marrow biopsy-proven myelofibrosis, 5 observers independently measured spleen volume on 3 abdominal MRI pulse sequences, 3D-spoiled gradient echo T1, axial single-shot fast spin echo (SSFSE) T2, and coronal SSFSE T2, using ellipsoidal approximation, manual contouring, and 3D nnU-Net model-assisted contouring comparing coefficients of variation. Changes in spleen volume were compared to all information to assess which measurement technique tracked disease progression with the greatest accuracy. Results: The coefficient of variation in spleen volume measurements averaging over 3 sequences was significantly lower for model-assisted contouring, 1.6% and manual contouring, 3.5%, compared to ellipsoidal estimation from 3 dimensions measured on axial and coronal T2 images, 15, p < 0.001. In 4 subjects with divergent treatment response predictions, model-assisted contouring was consistent with all information while ellipsoidal estimation was not. Manual contouring tracked similarly to model-assisted contouring but required more operator time. Conclusions: Model-assisted segmentations provide efficient and more reproducible spleen volume measurements compared to estimates of spleen volume from ellipsoidal approximations and improve objective determinations of clinical trial enrollment eligibility based upon spleen volume as well as assessments of treatment response. Full article

Background: We aimed to measure the pacemaker- and defibrillator-induced distortion at 0.35T and 3.0T magnetic fields. Methods: The pacemaker/defibrillator was placed at the top center of a water-filled/MagPhan phantom, followed by a T1 scan at 3T and a TrueFISP scan at 0.35T. The extent of distortion (i.e., the distance from the device to the furthest signal loss/void/rings) in the water-filled phantom was measured in MIM. For geometrical distortion (i.e., dislocation of geometrical structures), the spheres in the MagPhan phantom were contoured and their distortion was calculated based on their manufacturing coordinate positions. Results: The maximum extent of distortion caused by the defibrillator was 18.8 cm at 0.35T and 5.8 cm at 3.0T. Similarly, the maximum extent of distortion caused by the pacemaker was 9.28 cm at 0.35T and 2.8 cm at 3.0T. Geometrical distortion measurements using the MagPhan phantom showed that the maximum distortion caused by the defibrillator was 12.8 mm at 0.35T and 13.2 mm at 3.0T. Likewise, the maximum distortion caused by the pacemaker was 8.7 mm at 0.35T and 6.0 mm at 3.0T. Conclusions: Defibrillators cause larger distortions/signal voids than pacemakers, and require careful consideration when performing MRI-based treatment planning. To minimize distortion, sequences with lower sensitivity to magnetic field inhomogeneity should be used. Full article