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Diagnostics
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Advanced Ultrasound Techniques in Diagnosis
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Advanced Ultrasound Techniques in Diagnosis

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Medical Imaging and Theranostics".

Deadline for manuscript submissions: 31 March 2026 | Viewed by 4154

Special Issue Editor

Dr. Laith Riyadh Sultan

E-Mail Website
Guest Editor
Clinical Research Core, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
Interests: advanced ultrasound imaging; contrast enhanced ultrasound; quantitative image analysis; computer-aided diagnosis; machine learning; radiomics

Special Issue Information

Dear Colleagues,

This Special Issue on “Advanced Ultrasound Techniques in Diagnosis” seeks to spotlight cutting-edge ultrasound innovations that are revolutionizing diagnostic accuracy across a wide spectrum of medical disciplines. With ultrasound continuing to evolve as the cornerstone of non-invasive imaging, this issue will delve into its latest breakthroughs, including contrast-enhanced ultrasound (CEUS), microvascular imaging (MVI), super-resolution imaging, elastography, and the integration of AI-powered technologies.

We invite high-impact contributions that introduce novel applications, report significant technical advancements, and validate the clinical implementations of these advanced ultrasound modalities. The scope spans quantitative analysis, ultrasound radiomics, multi-modal ultrasound integration, and the creation of new imaging protocols aimed at enhancing diagnostic precision. This Special Issue will explore transformative ultrasound techniques, offering a comprehensive platform for research bridging traditional and emerging ultrasound technologies, fostering innovation, and delivering actionable insights for improving patient outcomes, shaping the future of diagnostic imaging.

Dr. Laith Riyadh Sultan
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-blind 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

  • super-resolution imaging
  • microvascular imaging (MVI)
  • contrast-enhanced ultrasound
  • AI-guided ultrasound
  • quantitative analysis
  • diagnostic imaging

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (4 papers)

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Research

14 pages, 1017 KB  
Article
Illuminating the Intricacies: A Comparative Cross-Sectional Sonographic Evaluation of Degenerative Changes in Leiomyomas Through Post-Processing Technique
by Mahasin G. Hassan, Nouf Aldrees, Sadeem Aldawsari, Raghad Alanazi, Noura Alboqami, Maryem Alanazi, Renad Alanazi, Khadejah Alrashidi and Basim S. Almutairi
Diagnostics 2025, 15(23), 2943; https://doi.org/10.3390/diagnostics15232943 - 21 Nov 2025
Viewed by 296
Abstract
Background: Leiomyomas are benign tumors that may cause symptoms and affect fertility, requiring careful assessment. Magnetic Resonance Imaging (MRI) becomes crucial when ultrasonography results are inconclusive; however, it is expensive and time-consuming. Utilizing post-processing techniques could enhance the ultrasound results. Using ultrasound [...] Read more.
Background: Leiomyomas are benign tumors that may cause symptoms and affect fertility, requiring careful assessment. Magnetic Resonance Imaging (MRI) becomes crucial when ultrasonography results are inconclusive; however, it is expensive and time-consuming. Utilizing post-processing techniques could enhance the ultrasound results. Using ultrasound with Fiji (ImageJ) enables precise evaluation of leiomyoma degeneration and may reduce the need for MRI. Aim: This study aims to evaluate the effectiveness of a post-processing technique using Fiji (ImageJ) to detect degenerative changes in leiomyomas and compare these findings with those obtained from conventional ultrasound and MRI results. Methods: A cross-sectional analytical study was conducted at King Saud Medical City involving 41 females diagnosed with uterine leiomyomas using ultrasound and MRI. Ultrasound images were analyzed using Fiji software to identify degenerative changes and compare results with ultrasound and MRI reports. Results: ImageJ outperformed ultrasound across all diagnostic metrics, with higher sensitivity (84.2% vs. 63.2%), specificity (81.8% vs. 22.7%), and accuracy (82.9% vs. 41.5%). ROC analysis showed superior diagnostic performance of ImageJ (AUC = 0.830) compared to ultrasound (AUC = 0.429), with a significant correlation to MRI findings (p < 0.001). Fibroids with and without degeneration showed no significant differences in Fiji parameters (p > 0.05). Conclusions: Integrating post-processing tools such as ImageJ with ultrasound imaging significantly improves the detection of degenerative changes in uterine leiomyomas, potentially reducing dependence on costly and less accessible modalities like MRI. Future studies should utilize a prospective design with larger sample sizes to strengthen the validity and generalizability of these findings. Full article
(This article belongs to the Special Issue Advanced Ultrasound Techniques in Diagnosis)
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12 pages, 1072 KB  
Article
Microvascular Imaging of Hepatic Hemangiomas
by Hakan Baş and Süleyman Filiz
Diagnostics 2025, 15(22), 2917; https://doi.org/10.3390/diagnostics15222917 - 18 Nov 2025
Viewed by 627
Abstract
Background/Objectives: We aimed to characterize the microvascular imaging (MI) to demonstrate in hepatic hemangiomas in routine practice and to quantify the impact of lesion depth on MI signal detectability, and—when present—describe the distribution of MI appearances. Methods: In this single-center, retrospective study from [...] Read more.
Background/Objectives: We aimed to characterize the microvascular imaging (MI) to demonstrate in hepatic hemangiomas in routine practice and to quantify the impact of lesion depth on MI signal detectability, and—when present—describe the distribution of MI appearances. Methods: In this single-center, retrospective study from January 2021 to December 2023, we screened 91 patients with 121 focal hepatic lesions on ultrasound. Lesions without typical hemangioma enhancement on dynamic MRI or dynamic CT were excluded. Two radiologists independently assessed MI signals and patterns using the Jeon classification, blinded to clinical and CT/MRI data; inter-observer agreement was quantified with Cohen’s κ. Results: Of 121 screened lesions, 36 lacked typical enhancement and were excluded; 85 hemangiomas remained. A total of 13 were excluded for motion artifacts near the heart or pulsatile vessels, yielding 72 hemangiomas (61 patients) for analysis. No lesion showed flow on color or power Doppler. MI signals were detected in 68/72 hemangiomas (94.4%). Among signal-positive lesions (n = 68), the patterns were non-specific in 25.0% (17/68), nodular rim in 22.1% (15/68), strip rim in 17.6% (12/68), central dot-like in 16.2% (11/68), peripheral dot-like in 10.3% (7/68), and staining in 8.8% (6/68). Signal-negative lesions were deeper than signal-positive lesions (median depth: 85 mm vs. 41.5 mm; p < 0.05). The inter-observer agreement was very good (κ = 0.821, 95% CI 0.767–0.921). Conclusions: MI is a reproducible, contrast-free technique that demonstrates hemangioma vascularity with high detection rates, particularly in more superficial lesions. In this cohort, lesion depth rather than size was the primary determinant of MI signal detectability. MI should be considered complementary to CT/MRI and may be especially useful where contrast agents are unavailable or contraindicated. Full article
(This article belongs to the Special Issue Advanced Ultrasound Techniques in Diagnosis)
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13 pages, 1423 KB  
Article
Quantifying “Medical Renal Disease”: A Pediatric Pilot Study Using Ultrasound Radiomics for Differentiating Acute Kidney Injury and Chronic Kidney Disease
by Laura De Leon-Benedetti, Laith R. Sultan, Hansel J. Otero, Tatiana Morales-Tisnés, Joya Sims, Kate Fitzpatrick, Julie C. Fitzgerald, Susan Furth, Benjamin L. Laskin and Bernarda Viteri
Diagnostics 2025, 15(16), 2112; https://doi.org/10.3390/diagnostics15162112 - 21 Aug 2025
Viewed by 1333
Abstract
Background: Differentiating acute kidney injury (AKI) from chronic kidney disease (CKD) in children remains a critical unmet need due to the limitations of current clinical and biochemical markers. Conventional ultrasound lacks the sensitivity to discern subtle parenchymal alterations. This study explores the application [...] Read more.
Background: Differentiating acute kidney injury (AKI) from chronic kidney disease (CKD) in children remains a critical unmet need due to the limitations of current clinical and biochemical markers. Conventional ultrasound lacks the sensitivity to discern subtle parenchymal alterations. This study explores the application of ultrasound radiomics—a novel, non-invasive, and quantitative image analysis method—for distinguishing AKI from CKD in pediatric patients. Methods: In this retrospective cross-sectional pilot study, kidney ultrasound images were obtained from 31 pediatric subjects: 8 with oliguric AKI, 14 with CKD, and 9 healthy controls. Renal parenchyma was manually segmented, and 124 advanced texture features were extracted using the open-source ©PyFeats. Features encompassed multiple categories (e.g., GLCM, GLSZM, WP). Statistical comparisons evaluated intergroup differences. Principal Component Analysis identified the top 10 most informative features, which were used to train supervised machine learning models. Model performance used five-fold cross-validation. Results: Radiomic analysis revealed significant intergroup differences (p < 0.05). CKD cases exhibited increased echogenicity and heterogeneity, particularly in GLCM and GLSZM features, consistent with chronic fibrosis. AKI cases displayed more homogeneous texture, likely reflecting edema or acute inflammation. While echogenicity separated diseased from healthy kidneys, it lacked specificity between AKI and CKD. Among ML models, XGBoost achieved the highest macro-averaged F1 score (0.90), followed closely by SVM and Random Forest, demonstrating strong classification performance. Conclusions: Radiomics-based texture analysis of grayscale ultrasound images effectively differentiated AKI from CKD in this pilot study, offering a promising, non-invasive imaging biomarker for pediatric kidney disease. These preliminary findings justify prospective validation in larger, multicenter cohorts. Full article
(This article belongs to the Special Issue Advanced Ultrasound Techniques in Diagnosis)
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11 pages, 4522 KB  
Article
Evaluation of Ovarian Stromal Microvascularity and Clinical-Hormonal Associations in Reproductive-Aged Women with Polycystic Ovary Morphology
by Hakan Baş and Süleyman Filiz
Diagnostics 2025, 15(11), 1376; https://doi.org/10.3390/diagnostics15111376 - 29 May 2025
Viewed by 1174
Abstract
Background/Objectives: This study aims to assess ovarian stromal vascularity using microvascular imaging in reproductive-aged women with polycystic ovarian morphology (PCOM) and to explore its associations with endocrine parameters and polycystic ovary syndrome (PCOS) phenotypes. Methods: We conducted a retrospective, single-center study between January [...] Read more.
Background/Objectives: This study aims to assess ovarian stromal vascularity using microvascular imaging in reproductive-aged women with polycystic ovarian morphology (PCOM) and to explore its associations with endocrine parameters and polycystic ovary syndrome (PCOS) phenotypes. Methods: We conducted a retrospective, single-center study between January 2021 and November 2023. Women aged 18–49 who met the PCOM criteria (≥20 follicles measuring 2–9 mm or an ovarian volume >10 cm3 in at least one ovary) were included. Pelvic ultrasound with MV-Flow Doppler imaging was used to quantify the stromal vascularity index (VI). On the same day, serum levels of FSH, LH, total and free testosterone, DHEAS, and estradiol were measured. PCOS phenotypes (A, C, D, and non-PCOS) were classified according to the Rotterdam criteria. Statistical analysis involved interobserver agreement using intraclass correlation coefficients (ICCs), correlation analysis for hormonal associations, and group comparisons using ANOVA. Results: A total of 111 women (mean age: 27.4 ± 6.1 years) were evaluated. The mean VI was 43.88 ± 19.84, with good interobserver agreement (ICC = 0.79; 95% CI: 0.65–0.88). VI was highest in Phenotype A (61.36 ± 10.11), followed by Phenotype C (42.57 ± 3.59), Phenotype D (26.47 ± 4.24), and Non-PCOS individuals (9.95 ± 5.44; p < 0.001). VI showed strong positive correlations with total testosterone (r = 0.797) and free testosterone (r = 0.778), and a moderate negative correlation with DHEAS (r = −0.483; p < 0.001). Conclusions: Microvascular imaging is a promising tool for quantifying ovarian stromal vascularity in PCOM. Its strong correlation with androgen levels, especially in hyperandrogenic phenotypes, highlights its potential role in enhancing diagnostic precision and deepening our understanding of PCOS pathophysiology. Full article
(This article belongs to the Special Issue Advanced Ultrasound Techniques in Diagnosis)
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