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Advances in Diagnostic Imaging and Interpretation in Pediatric Radiology

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A Special Issue of Diagnostics (ISSN 2075-4418) belonging to the section "Medical Imaging and Theranostics".

Deadline for manuscript submissions: 31 December 2026 | Viewed by 4247

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Editor

Dr. André Lollert

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Guest Editor

Department of Diagnostic and Interventional Radiology, Section of Pediatric Radiology, Medical Center of the Johannes Gutenberg-University, Mainz, Germany
Interests: pediatric MR imaging; imaging of patients with metabolic diseases; imaging of chest wall de-formities; novel ultrasound techniques; pediatric cardiovascular imaging; quantitative imag-ing techniques

Special Issue Information

Dear Colleagues,

I am pleased to invite you to contribute your work to the Special Issue, “Advances in Diagnostic Imaging and Interpretation in Pediatric Radiology”, to be published in Diagnostics. Pediatric imaging differs significantly from general / adult radiology, most importantly due to the wide range of patients, beginning with premature infants with a body weight of less than 500 g, and ranging to adolescents with an adult patient stature. In addition, novel imaging techniques are frequently developed for adults and thus have to be adapted to be used in pediatric patients.

This Special Issue aims to promote research in all fields of pediatric imaging, as well as clinico-radiologic and interdisciplinary diagnostics. Not only radiologists, but also colleagues from clinical disciplines are encouraged to submit their work.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following: pediatric MRI, novel CT techniques (e. g., photon-counting CT) for pediatric imaging, pediatric applications of novel ultrasound techniques, application of artificial intelligence in pediatric imaging, role of imaging for the diagnostic work-up of rare diseases, and nuclear medicine in pediatrics.

I look forward to receiving your contributions.

Dr. André Lollert
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Diagnostics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

pediatric radiology
pediatric MRI
pediatric CT
photon-counting CT
pediatric ultrasound
clinico-radiologic diagnostics
rare diseases
quantitative imaging
artificial intelligence
nuclear medicine

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Published Papers (6 papers)

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Editorial

Jump to: Research, Review

4 pages, 158 KB

Open AccessEditorial

Current State and Future Directions of Diagnostic Imaging and Interpretation in Pediatric Radiology

by André Lollert

Diagnostics 2026, 16(7), 1007; https://doi.org/10.3390/diagnostics16071007 - 27 Mar 2026

Viewed by 663

Abstract

Pediatric radiology is an inherently technology-dependent medical subspecialty [...] Full article

(This article belongs to the Special Issue Advances in Diagnostic Imaging and Interpretation in Pediatric Radiology)

Research

Jump to: Editorial, Review

14 pages, 440 KB

Open AccessArticle

Anatomical Evaluation of Localized Mandibular Trabecular Texture Differences in Children with Hypodontia Using Radiographic Fractal Analysis

by Mert Nahir and Canan Bayraktar Nahir

Diagnostics 2026, 16(16), 2627; https://doi.org/10.3390/diagnostics16162627 - 19 Aug 2026

Viewed by 234

Abstract

Background/Objectives: This study aimed to evaluate mandibular trabecular bone structure in children with and without hypodontia using fractal analysis (FA) and to determine whether fractal dimension (FD) values vary according to hypodontia pattern and the localization of the affected alveolar region. Methods: This study included 75 children aged 8–12 years, divided into three age- and gender-matched groups: controls without agenesis (Group 1, n = 25), mandibular second premolar agenesis (Group 2, n = 25), and agenesis of both mandibular first and second premolars (Group 3, n = 25). Panoramic radiographs were analyzed using a semi-automated FA method involving manual ROI placement followed by automated image processing and FD calculation. FD values were measured in three regions of interest (ROIs): the mandibular condyle (ROI1), mandibular angle (ROI2), and alveolar region corresponding to the agenetic area (ROI3). Results: FD values did not differ significantly by age or gender in any ROI (p > 0.05). The pattern of FD differences among the study groups varied significantly according to anatomical region, as demonstrated by the significant Group × ROI interaction (p < 0.001). Post hoc comparisons showed that the most pronounced intergroup difference occurred in ROI3, where Group 2 had a significantly lower FD value (0.78 ± 0.26) than Group 1 (1.10 ± 0.21) and Group 3 (1.04 ± 0.23). Conclusions: Mandibular trabecular texture differences in children with hypodontia appeared to be localized mainly to the alveolar region corresponding to tooth agenesis. The lower FD value observed in the mandibular second premolar agenesis group suggests that these regional differences may be related to the anatomical localization of the agenetic area rather than to the number of missing teeth alone. Although such findings may help draw attention to site-specific alveolar changes during radiographic assessment, they are based on two-dimensional panoramic radiographic texture analysis and should be regarded as preliminary and hypothesis-generating. Full article

(This article belongs to the Special Issue Advances in Diagnostic Imaging and Interpretation in Pediatric Radiology)

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10 pages, 2170 KB

Open AccessArticle

External Validation of Deeplasia for Automated Bone Age Assessment Compared with Four Commercial AI Systems

by Johanna Pape, Roland Pfäffle, Franz Wolfgang Hirsch, Maciej Rosolowski and Daniel Gräfe

Diagnostics 2026, 16(16), 2568; https://doi.org/10.3390/diagnostics16162568 - 14 Aug 2026

Viewed by 310

Abstract

Background/Objectives: Artificial intelligence (AI)-based systems enable automated bone age (BA) assessment according to the Greulich and Pyle (G&P) method with expert-level performance. Deeplasia is a recently introduced deep learning-based approach that demonstrated promising results in previous studies. This study aimed to externally validate Deeplasia for G&P-based BA and chronological age (CA) estimation. Methods: This retrospective single-center study included two independent cohorts. For BA assessment, 306 children and adolescents aged 1–18 years were analyzed using the mean rating of three expert readers as the reference standard. For CA assessment, 1653 children and adolescents undergoing hand radiography after trauma were included after exclusion of pathological findings. Deeplasia was compared with four CE-certified AI systems. Performance was evaluated using mean error, mean absolute error (MAE), root mean squared error (RMSE), and Bland–Altman limits of agreement. Results: Deeplasia achieved a very good overall agreement with the human reference standard, with the lowest RMSE (0.59 years in boys, 0.55 years in girls) and MAE (0.45 years in boys, 0.43 years in girls). However, no significant differences between the AI systems were observed within the age range representing 90% of the clinically relevant cohort. Estimation of the CA was substantially less accurate than G&P-based BA assessment across all systems. All programs showed systematic overestimation of CA, particularly in adolescent girls. Conclusions: Compared to commercial AI systems, Deeplasia demonstrated excellent external validity for automated G&P-based BA assessment. However, the findings again highlight the intrinsic limitations of G&P-based models for precise CA estimation in contemporary pediatric populations. Full article

(This article belongs to the Special Issue Advances in Diagnostic Imaging and Interpretation in Pediatric Radiology)

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32 pages, 11450 KB

Open AccessArticle

A Dual-Branch Frequency-Aware Attention Framework for Rare Neurological Disease Classification from Brain MRI

by Madallah Alruwaili and Mahmood A. Mahmood

Diagnostics 2026, 16(11), 1749; https://doi.org/10.3390/diagnostics16111749 - 5 Jun 2026

Viewed by 426

Abstract

Background: Rare neurological diseases are challenging to diagnose from brain MRI because of their low prevalence, heterogeneous imaging patterns, and limited annotated datasets. Deep learning may support image-level recognition, but results from curated datasets without complete patient-level identifiers require cautious interpretation. Objectives: This study proposes RareNeuroXNet, a frequency-aware multi-branch attention framework for image-level classification of rare neurological diseases from brain MRI. The objective was to assess whether combining global anatomical, local fine-grained, and frequency-domain representations improves benchmark performance, calibration, and interpretability. Methods: RareNeuroXNet uses three complementary branches: a global branch for whole-image representation, a local branch for regional feature extraction, and an FFT magnitude-based frequency branch. Features are refined using CBAM attention, fused, and classified through a fully connected head. The model was evaluated on a balanced curated dataset with five rare neurological disease classes using five-fold cross-validation, ablation analysis, calibration metrics, internal baseline comparison, paired testing against DenseNet121 local-only, and Grad-CAM visualization. MCND was also used as a complementary cross-dataset neurological MRI benchmark, not as same-task external validation. Results: RareNeuroXNet achieved strong image-level internal benchmark performance, with accuracy of

0.9924 \pm 0.0061

, macro F1-score of

0.9924 \pm 0.0061

, macro AUROC of

0.9998 \pm 0.0002

, and macro AUPR of

0.9992 \pm 0.0007

. Calibration was favorable, with ECE of

0.0052 \pm 0.0029

and NLL of

0.0276 \pm 0.0159

. Ablation results showed that the local branch was the dominant contributor, while FFT and CBAM provided supportive refinement. Compared with DenseNet121 local-only, RareNeuroXNet showed modest classification gains and clearer calibration improvements. Conclusions: RareNeuroXNet demonstrated strong controlled image-level benchmark performance with high discrimination, stable cross-validation behavior, favorable calibration, and Grad-CAM interpretability. However, possible correlated slices, duplicate images, or subject overlap cannot be excluded. Future work should use patient-level, same-task, multi-center external validation and 3D multimodal MRI analysis. Full article

(This article belongs to the Special Issue Advances in Diagnostic Imaging and Interpretation in Pediatric Radiology)

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11 pages, 3313 KB

Open AccessArticle

Evaluation of the Reliability of Radiographic and MRI Angles in Superior Femoral Epiphysiolysis: A Comparative Study

by Wassim Ben Abdennebi, Andreas Tsoupras, Eugénie Barras, Viola Sbampato, Romain Dayer, Giacomo De Marco, Oscar Vazquez, Christina Steiger, Amira Dhouib, Anne Tabard-Fougère and Dimitri Ceroni

Diagnostics 2026, 16(8), 1208; https://doi.org/10.3390/diagnostics16081208 - 17 Apr 2026

Viewed by 443

Abstract

Background/Objectives: Slipped Capital Femoral Epiphysis (SCFE) is a common, serious hip disorder in children and adolescents. Two-dimensional (2D) radiography is the gold standard for diagnosis but may not fully capture the deformity’s complexity, and it is vulnerable to positioning errors. Advances in three-dimensional (3D) imaging, such as computed tomography and magnetic resonance imaging (MRI), enable more accurate assessments. This study aimed to (1) assess the inter-rater reliability of 2D radiographic and 3D MRI measurements, and (2) evaluate the correlations and agreements between these outcomes. Methods: Patients were randomly selected from a cohort of patients aged under 16 years old and diagnosed with SCFE between January 2000 and December 2024. Southwick angles and posterior epiphyseal slip angles on 2D radiographs were independently measured by two orthopaedic surgeons. Posterior epiphyseal slip angles on 3D MRI were independently measured by two orthopaedic surgeons and two paediatric radiologists. Relationships between the three outcomes were evaluated using the Pearson correlation coefficient (r). Inter-rater reliability and agreements between the three outcomes were evaluated using the intraclass correlation coefficient (ICC) and the standard error measurement (SEM). Results: A total of 35 patients (35 hips) were recruited, with a mean age of 11.8 (1.2) years old and 19/35 (54%) females. Radiographic outcomes were moderately correlated (r < 0.75, p < 0.01) with MRI posterior epiphyseal slip angles. MRI posterior epiphyseal slip angles were systematically greater (16° on average) than both radiographic outcomes, regardless of whether contralateral correction was applied. The inter-rater reliability of radiographic outcomes was excellent (ICC > 0.85, SEM > 5.0°) and almost perfect (ICC > 0.95, SEM = 2.5°) for the MRI posterior epiphyseal slip angles measured by the paediatric radiologists. Conclusions: Findings suggest that while both diagnostic methods are reliable, radiographic measurements systematically underestimate epiphyseal slip severity by approximately 16° compared to MRI. This discrepancy could impact the accuracy of disease staging, leading to potential misclassifications. This highlights the need for a more standardised approach to evaluating SCFE, especially regarding the type of imaging used for angle measurement. Full article

(This article belongs to the Special Issue Advances in Diagnostic Imaging and Interpretation in Pediatric Radiology)

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Review

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16 pages, 3997 KB

Open AccessReview

CCTA of Pediatric Congenital Right Heart Obstructive Lesions: A Pictorial Review

by Zuofeng Zheng and Lei Xu

Diagnostics 2026, 16(13), 1959; https://doi.org/10.3390/diagnostics16131959 - 24 Jun 2026

Viewed by 1608

Abstract

Pediatric congenital right heart obstructive lesions encompass a spectrum of diseases that obstruct blood flow from the right atrium to the pulmonary artery. Right ventricular inflow obstructions include tricuspid valve abnormalities, such as Ebstein anomaly, tricuspid valve dysplasia, and tricuspid atresia. Right ventricular outflow obstructions include pulmonary valve stenosis, pulmonary atresia, and tetralogy of Fallot. Cardiac computed tomography angiography (CCTA) is a valuable tool for the diagnosis, treatment planning, and follow-up of these lesions. In this pictorial review, we highlight the diagnostic utility of CCTA in congenital right heart obstructive lesions, emphasizing its role in preoperative planning. Full article

(This article belongs to the Special Issue Advances in Diagnostic Imaging and Interpretation in Pediatric Radiology)

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