OBJECTIVE: We comprehensively characterized a large pediatric cohort with focal cortical dysplasia (FCD) type 1 to expand the phenotypic spectrum and to identify predictors of postsurgical outcomes. METHODS: We included pediatric patients with histopathological diagnosis of isolated FCD type 1 and at least 1 year of postsurgical follow-up. We systematically reanalyzed clinical, electrophysiological, and radiological features. The results of this reanalysis served as independent variables for subsequent statistical analyses of outcome predictors. RESULTS: All children (N = 31) had drug-resistant epilepsy with varying impacts on neurodevelopment and cognition (presurgical intelligence quotient [IQ]/developmental quotient scores = 32-106). Low presurgical IQ was associated with abnormal slow background electroencephalographic (EEG) activity and disrupted sleep architecture. Scalp EEG showed predominantly multiregional and often bilateral epileptiform activity. Advanced epilepsy magnetic resonance imaging (MRI) protocols identified FCD-specific features in 74.2% of patients (23/31), 17 of whom were initially evaluated as MRI-negative. In six of eight MRI-negative cases, fluorodeoxyglucose-positron emission tomography (PET) and subtraction ictal single photon emission computed tomography coregistered to MRI helped localize the dysplastic cortex. Sixteen patients (51.6%) underwent invasive EEG. By the last follow-up (median = 5 years, interquartile range = 3.3-9 years), seizure freedom was achieved in 71% of patients (22/31), including seven of eight MRI-negative patients. Antiseizure medications were reduced in 21 patients, with complete withdrawal in six. Seizure outcome was predicted by a combination of the following descriptors: age at epilepsy onset, epilepsy duration, long-term invasive EEG, and specific MRI and PET findings. SIGNIFICANCE: This study highlights the broad phenotypic spectrum of FCD type 1, which spans far beyond the narrow descriptions of previous studies. The applied multilayered presurgical approach helped localize the epileptogenic zone in many previously nonlesional cases, resulting in improved postsurgical seizure outcomes, which are more favorable than previously reported for FCD type 1 patients.

• MeSH
• Child MeSH
• Electroencephalography * methods   MeSH
• Epilepsy MeSH
• Focal Cortical Dysplasia MeSH
• Cohort Studies MeSH
• Infant MeSH
• Humans MeSH
• Magnetic Resonance Imaging * MeSH
• Malformations of Cortical Development, Group I * surgery   complications   diagnostic imaging   MeSH
• Malformations of Cortical Development surgery   complications   diagnostic imaging   MeSH
• Adolescent MeSH
• Positron-Emission Tomography MeSH
• Child, Preschool MeSH
• Drug Resistant Epilepsy * surgery   diagnostic imaging   physiopathology   MeSH
• Treatment Outcome MeSH
• Check Tag
• Child MeSH
• Infant MeSH
• Humans MeSH
• Adolescent MeSH
• Male MeSH
• Child, Preschool MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

PURPOSE OF REVIEW: Upper tract urothelial carcinoma (UTUC) is a rare malignancy posing significant diagnostic and management challenges. This review provides an overview of the evidence supporting various imaging modalities and offers insights into future innovations in UTUC imaging. RECENT FINDINGS: With the growing use of advancements in computed tomography (CT) technologies for both staging and follow-up of UTUC patients, continuous innovations aim to enhance performance and minimize the risk of excessive exposure to ionizing radiation and iodinated contrast medium. In patients unable to undergo CT, magnetic resonance imaging serves as an alternative imaging modality, though its sensitivity is lower than CT. Positron emission tomography, particularly with innovative radiotracers and theranostics, has the potential to significantly advance precision medicine in UTUC. Endoscopic imaging techniques including advanced modalities seem to be promising in improved visualization and diagnostic accuracy, however, evidence remains scarce. Radiomics and radiogenomics present emerging tools for noninvasive tumor characterization and prognosis. SUMMARY: The landscape of imaging for UTUC is rapidly evolving, with significant advancements across various modalities promising improved diagnostic accuracy, patient outcomes, and safety.

• MeSH
• Carcinoma, Transitional Cell * diagnosis   diagnostic imaging   therapy   pathology   MeSH
• Humans MeSH
• Magnetic Resonance Imaging methods   MeSH
• Kidney Neoplasms diagnostic imaging   therapy   diagnosis   pathology   MeSH
• Ureteral Neoplasms diagnostic imaging   diagnosis   therapy   pathology   MeSH
• Tomography, X-Ray Computed methods   MeSH
• Positron-Emission Tomography methods   MeSH
• Neoplasm Staging MeSH
• Urologic Neoplasms diagnosis   diagnostic imaging   therapy   pathology   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Review MeSH

PURPOSE: The aim of this study was to develop a simple, robust, and easy-to-use calibration procedure for correcting misalignments in rosette MRI k-space sampling, with the objective of producing images with minimal artifacts. METHODS: Quick automatic calibration scans were proposed for the beginning of the measurement to collect information on the time course of the rosette acquisition trajectory. A two-parameter model was devised to match the measured time-varying readout gradient delays and approximate the actual rosette sampling trajectory. The proposed calibration approach was implemented, and performance assessment was conducted on both phantoms and human subjects. RESULTS: The fidelity of phantom and in vivo images exhibited significant improvement compared with uncorrected rosette data. The two-parameter calibration approach also demonstrated enhanced precision and reliability, as evidenced by quantitative T2*$$ {\mathrm{T}}_2^{\ast } $$ relaxometry analyses. CONCLUSION: Adequate correction of data sampling is a crucial step in rosette MRI. The presented experimental results underscore the robustness, ease of implementation, and suitability for routine experimental use of the proposed two-parameter rosette trajectory calibration approach.

• MeSH
• Algorithms * MeSH
• Artifacts * MeSH
• Phantoms, Imaging * MeSH
• Calibration MeSH
• Humans MeSH
• Magnetic Resonance Imaging * methods   MeSH
• Brain diagnostic imaging   MeSH
• Image Processing, Computer-Assisted * methods   MeSH
• Reproducibility of Results MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH

PURPOSE: Dual velocity encoding PC-MRI can produce spurious artifacts when using high ratios of velocity encoding values (VENCs), limiting its ability to generate high-quality images across a wide range of encoding velocities. This study aims to propose and compare dual-VENC correction methods for such artifacts. THEORY AND METHODS: Two denoising approaches based on spatiotemporal regularization are proposed and compared with a state-of-the-art method based on sign correction. Accuracy is assessed using simulated data from an aorta and brain aneurysm, as well as 8 two-dimensional (2D) PC-MRI ascending aorta datasets. Two temporal resolutions (30,60) ms and noise levels (9,12) dB are considered, with noise added to the complex magnetization. The error is evaluated with respect to the noise-free measurement in the synthetic case and to the unwrapped image without additional noise in the volunteer datasets. RESULTS: In all studied cases, the proposed methods are more accurate than the Sign Correction technique. Using simulated 2D+T data from the aorta (60 ms, 9 dB), the Dual-VENC (DV) error 0.82±0.07$$ 0.82\pm 0.07 $$ is reduced to: 0.66±0.04$$ 0.66\pm 0.04 $$ (Sign Correction); 0.34±0.04$$ 0.34\pm 0.04 $$ and 0.32±0.04$$ 0.32\pm 0.04 $$ (proposed techniques). The methods are found to be significantly different (p-value <0.05$$ <0.05 $$ ). Importantly, brain aneurysm data revealed that the Sign Correction method is not suitable, as it increases error when the flow is not unidirectional. All three methods improve the accuracy of in vivo data. CONCLUSION: The newly proposed methods outperform the Sign Correction method in improving dual-VENC PC-MRI images. Among them, the approach based on temporal differences has shown the highest accuracy.

• MeSH
• Algorithms * MeSH
• Aorta * diagnostic imaging   MeSH
• Artifacts * MeSH
• Phantoms, Imaging MeSH
• Image Interpretation, Computer-Assisted methods   MeSH
• Intracranial Aneurysm diagnostic imaging   MeSH
• Humans MeSH
• Magnetic Resonance Imaging * methods   MeSH
• Brain diagnostic imaging   MeSH
• Computer Simulation MeSH
• Image Processing, Computer-Assisted * methods   MeSH
• Signal-To-Noise Ratio * MeSH
• Reproducibility of Results MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH

BACKGROUND: Neuromuscular diseases (NMDs) are rare disorders characterized by progressive muscle fibre loss, leading to replacement by fibrotic and fatty tissue, muscle weakness and disability. Early diagnosis is critical for therapeutic decisions, care planning and genetic counselling. Muscle magnetic resonance imaging (MRI) has emerged as a valuable diagnostic tool by identifying characteristic patterns of muscle involvement. However, the increasing complexity of these patterns complicates their interpretation, limiting their clinical utility. Additionally, multi-study data aggregation introduces heterogeneity challenges. This study presents a novel multi-study harmonization pipeline for muscle MRI and an AI-driven diagnostic tool to assist clinicians in identifying disease-specific muscle involvement patterns. METHODS: We developed a preprocessing pipeline to standardize MRI fat content across datasets, minimizing source bias. An ensemble of XGBoost models was trained to classify patients based on intramuscular fat replacement, age at MRI and sex. The SHapley Additive exPlanations (SHAP) framework was adapted to analyse model predictions and identify disease-specific muscle involvement patterns. To address class imbalance, training and evaluation were conducted using class-balanced metrics. The model's performance was compared against four expert clinicians using 14 previously unseen MRI scans. RESULTS: Using our harmonization approach, we curated a dataset of 2961 MRI samples from genetically confirmed cases of 20 paediatric and adult NMDs. The model achieved a balanced accuracy of 64.8% ± 3.4%, with a weighted top-3 accuracy of 84.7% ± 1.8% and top-5 accuracy of 90.2% ± 2.4%. It also identified key features relevant for differential diagnosis, aiding clinical decision-making. Compared to four expert clinicians, the model obtained the highest top-3 accuracy (75.0% ± 4.8%). The diagnostic tool has been implemented as a free web platform, providing global access to the medical community. CONCLUSIONS: The application of AI in muscle MRI for NMD diagnosis remains underexplored due to data scarcity. This study introduces a framework for dataset harmonization, enabling advanced computational techniques. Our findings demonstrate the potential of AI-based approaches to enhance differential diagnosis by identifying disease-specific muscle involvement patterns. The developed tool surpasses expert performance in diagnostic ranking and is accessible to clinicians worldwide via the Myo-Guide online platform.

• MeSH
• Adult MeSH
• Internet MeSH
• Middle Aged MeSH
• Humans MeSH
• Magnetic Resonance Imaging * methods   MeSH
• Neuromuscular Diseases * diagnosis   diagnostic imaging   MeSH
• Machine Learning * MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

The study evaluates the efficacy of RETROICOR (Retrospective Image Correction) in mitigating physiological artifacts within multi-echo (ME) fMRI data. Two RETROICOR implementations were compared: applying corrections to individual echoes (RTC_ind) versus composite multi-echo data (RTC_comp). Data from 50 healthy participants were collected using diverse acquisition parameters, including multiband acceleration factors and varying flip angles, on a Siemens Prisma 3T scanner. Key metrics such as temporal signal-to-noise ratio (tSNR), signal fluctuation sensitivity (SFS), and variance of residuals demonstrated improved data quality in both RETROICOR models, particularly in moderately accelerated runs (multiband factors 4 and 6) with lower flip angles (45°). Differences between RTC_ind and RTC_comp were minimal, suggesting both methods are viable for practical applications. While the highest acceleration (multiband factor 8) degraded data quality, RETROICOR's compatibility with faster acquisition sequences was confirmed. These findings underscore the importance of optimizing acquisition parameters and noise correction techniques for reliable fMRI investigations.

• MeSH
• Artifacts * MeSH
• Adult MeSH
• Humans MeSH
• Magnetic Resonance Imaging * methods   MeSH
• Brain Mapping * methods   MeSH
• Young Adult MeSH
• Brain * diagnostic imaging   physiology   MeSH
• Image Processing, Computer-Assisted * methods   MeSH
• Signal-To-Noise Ratio MeSH
• Check Tag
• Adult MeSH
• Humans MeSH
• Young Adult MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

Nazolabiální cysta (NC), známá také jako Klestadtova cysta, je vzácná neodontogenní cystická leze měkkých tkání maxilofaciální oblasti, která predominantně postihuje ženy ve středním věku. Typicky bývá asymptomatická, může ale způsobovat otok v nazolabiální oblasti nebo nosní obturaci. Prezentované kazuistiky popisují případy dvou pacientek, kterým byla NC diagnostikována, ale každá podstoupila jiný typ operačního výkonu, nicméně s dobrým klinickým výsledkem v obou případech, kdy jsou obě bez obtíží a recidivy. Léze byla poprvé popsána v roce 1882 a později zkoumána Walterem Klestadtem v roce 1953. Diagnóza se obvykle provádí pomocí CT a MR, s chirurgickou excizí jako preferovanou metodou léčby. Recidiva po operaci je vzácná a prognóza velmi příznivá.

Nasolabial cyst (NC), also known as Klestadt‘s cyst, a is a rare non-odontogenic cystic lesion of the soft tissues in the maxillofacial area, predominantly affecting middle-aged women. It typically presents asymptomatically but can cause swelling in the nasolabial region or nasal obstruction. Case reports describe two patients diagnosed with NC who underwent different types of surgical procedures, both resulting in good clinical outcomes, with both patients remaining symptom-free and without recurrence. The lesion was first described in 1882 and later studied by Walter Klestadt in 1953. Dia gnosis is typically performed using CT and MRI, with surgical excision being the preferred method of treatment. Recurrence after surgery is rare, and the prognosis is very favourable.

• Keywords
• Klestadtova cysta,
• MeSH
• Cysts surgery   diagnosis   classification   MeSH
• Diagnosis, Differential MeSH
• Adult MeSH
• Nonodontogenic Cysts * surgery   diagnostic imaging   diagnosis   classification   MeSH
• Middle Aged MeSH
• Humans MeSH
• Magnetic Resonance Imaging methods   MeSH
• Nasal Obstruction diagnosis   etiology   MeSH
• Otorhinolaryngologic Surgical Procedures methods   MeSH
• Tomography, X-Ray Computed methods   MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Female MeSH
• Publication type
• Case Reports MeSH

Tools for post-operative localization of deep brain stimulation (DBS) electrodes may be of major benefit in the evaluation of the stimulation area. However, little is known about their precision. This study compares 3 different software packages used for DBS electrode localization. T1-weighted MRI images before and after the implantation of the electrodes into the subthalamic nucleus for DBS in 105 Parkinson's disease patients were processed using the pipelines implemented in Lead-DBS, SureTune4, and Brainlab. Euclidean distance between active contacts determined by individual software packages and in repeated processing by the same and by a different operator was calculated. Furthermore, Dice coefficient for overlap of volume of tissue activated (VTA) was determined for Lead-DBS. Medians of Euclidean distances between estimated active contact locations in inter-software package comparison ranged between 1.5 mm and 2 mm. Euclidean distances in within-software package intra- and inter-rater assessments were 0.6-1 mm and 1-1.7 mm, respectively. Median intra- and inter-rater Dice coefficients for VTAs were 0.78 and 0.75, respectively. Since the median distances are close to the size of the target nucleus, any clinical use should be preceded by careful review of the outputs.

• MeSH
• Deep Brain Stimulation * methods   instrumentation   MeSH
• Electrodes, Implanted * MeSH
• Middle Aged MeSH
• Humans MeSH
• Magnetic Resonance Imaging MeSH
• Subthalamic Nucleus surgery   MeSH
• Parkinson Disease * therapy   MeSH
• Aged MeSH
• Software MeSH
• Check Tag
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

BACKGROUND: Preoperative tumour size is a key prognostic marker in tailoring surgical treatment in early-stage cervical cancer. This post-hoc analysis assessed the accuracy of preoperative tumour size evaluation via imaging, utilizing data from the prospective, international, multicentre SENTIX study that evaluated safety of sentinel lymph node (SLN) biopsy without pelvic lymph node dissection in patients with early-stage cervical cancer. METHODS: Between 05/2016-09/2020, forty-seven sites across 18 countries enrolled cervical cancer patients (FIGO2018 stages 1A1/lymphovascular-space-invasion-positive to 1B2). Preoperative staging included pelvic MRI or ultrasound as mandatory imaging modalities. All patients underwent primary surgical treatment. Pathological assessment of surgical specimens served as reference standard for evaluating the accuracy of preoperative assessments. RESULTS: Among the 680 included patients, although the mean tumour size discrepancy between preoperative/pathological assessments was only 1.24 ± 8.891 mm, postoperative pT stage was upgraded in 187 (27.5 %) and downgraded in 74 (10.9 %) patients. Discrepancy of ≥10 mm was observed among 155 (22.8 %) patients across all stages, with underestimation in 105 (15.4 %), overestimation in 50 (7.4 %), and a positive correlation (P < 0.0001) between the pathological tumour size and the discrepancy in size assessment. If a maximum 2 cm tumour size threshold were applied to guide the decision between simple and radical hysterectomy, underestimation would result in inadequate surgical management for 9.0 % of patients, whereas overestimation would lead to unnecessarily radical procedures in 5.1 % of cases. CONCLUSIONS: The study highlights, that even with the use of modern imaging in preoperative staging, inaccuracies in tumour size assessment remain a common cause of up-/down-staging after surgery resulting in potential inappropriate planning of surgery, and thus in procedure that is either excessively or insufficiently radical. TRIAL REGISTRATION: ClinicalTrials.gov: NCT02494063.

• MeSH
• Sentinel Lymph Node Biopsy methods   MeSH
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Magnetic Resonance Imaging MeSH
• Uterine Cervical Neoplasms * pathology   surgery   diagnostic imaging   MeSH
• Preoperative Care methods   MeSH
• Prospective Studies MeSH
• Aged MeSH
• Neoplasm Staging MeSH
• Tumor Burden MeSH
• Ultrasonography MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Multicenter Study MeSH

OBJECTIVES: SENTIX was a prospective, single-arm, international multicenter study that evaluated sentinel lymph node biopsy without pelvic lymph node dissection in patients with early-stage cervical cancer. We aimed to evaluate the concordance between preoperative imaging modalities (magnetic resonance imaging (MRI) and ultrasound) and final pathology in the clinical staging of early-stage cervical cancer by post-hoc analysis of the SENTIX study data. METHODS: In total, 47 sites across 18 countries participated in the SENTIX study. Patients with Stage IA1/lymphovascular space invasion-positive to IB2 (International Federation of Gynecology and Obstetrics (FIGO) classification (2018)) cervical cancer, with usual histological types and no suspicious lymph nodes on imaging, were prospectively enrolled between May 2016 and October 2020. Preoperative pelvic clinical staging on either pelvic MRI or ultrasound examination was mandatory. Tumor size discrepancy (< 10 mm vs ≥ 10 mm) between imaging and pathology, as well as the negative predictive value (NPV) of MRI and ultrasound for parametrial involvement and lymph node macrometastasis, were analyzed. RESULTS: Among 690 eligible prospectively enrolled patients, MRI and ultrasound were used as the staging imaging modality in 322 (46.7%) and 298 (43.2%) patients, respectively. A discrepancy of tumor size ≥ 10 mm was reported between ultrasound and final pathology in 39/298 (13.1%) patients and between MRI and pathology in 53/322 (16.5%), with no significant difference in the accuracy of tumor measurement between the two imaging modalities. The NPV of ultrasound in assessing parametrial infiltration and lymph node involvement was 97.0% (95% CI, 0.95-0.99%) and 94.0% (95% CI, 0.91-0.97%), respectively, and that of MRI was 95.3% (95% CI, 0.93-0.98%) and 94.1% (95% CI, 0.92-0.97%), respectively, with no significant differences between the parameters. Ultrasound and MRI were comparable regarding the tumor size measurement (P = 0.452), failure to detect parametrial involvement (P = 0.624) and failure to detect macrometastases in sentinel lymph node (P = 0.876). CONCLUSIONS: Pelvic ultrasound examination and MRI had similar concordance with histology in the assessment of tumor size and of parametrial and lymph node invasion in early-stage cervical cancer. Ultrasound examination should be considered part of preoperative pelvic clinical staging in early-stage cervical cancer, especially in limited-resource regions where MRI is unavailable. © 2025 The Author(s). Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

• MeSH
• Sentinel Lymph Node Biopsy MeSH
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Lymphatic Metastasis diagnostic imaging   MeSH
• Lymph Nodes pathology   diagnostic imaging   MeSH
• Magnetic Resonance Imaging * methods   MeSH
• Uterine Cervical Neoplasms * pathology   diagnostic imaging   MeSH
• Pelvis diagnostic imaging   pathology   MeSH
• Predictive Value of Tests MeSH
• Preoperative Care methods   MeSH
• Prospective Studies MeSH
• Aged MeSH
• Neoplasm Staging methods   MeSH
• Ultrasonography methods   MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Multicenter Study MeSH
• Research Support, Non-U.S. Gov't MeSH