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Improving Imaging Diagnosis: From Conventional Radiology to Advanced Imaging Techniques

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

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 25234

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Special Issue Editors

Dr. Federica Vernuccio

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Guest Editor

Department of Radiology, University Hospital of Padova, Via Nicolò Giustiniani 2, 35128 Padova, Italy
Interests: abdominal imaging; emergency radiology; liver imaging; pancreatic imaging; radiomics; texture analysis
Special Issues, Collections and Topics in MDPI journals

Dr. Roberto Cannella

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Guest Editor

Department of Biomedicine, Neuroscience and Advanced Diagnostics (BiND), University Hospital “Paolo Giaccone”, Via del Vespro 129, 90127 Palermo, Italy
Interests: abdominal imaging; emergency radiology; liver imaging; pancreatic imaging; radiomics
Special Issues, Collections and Topics in MDPI journals

Dr. Albert Comelli

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Guest Editor

1. Ri.MED Foundation, via Bandiera 11, 90133 Palermo, Italy
2. Research Affiliate Long Term, Laboratory of Computational Computer Vision (LCCV), School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA
Interests: biomedical image processing and analysis; radiomics; artificial intelligence; machine learning; deep learning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue is aimed at providing updates on scientific diagnostic radiology and best-practice knowledge in radiology through the publication of original papers and state-of-the-art reviews on diagnostic imaging with clinically oriented papers. There will be a focus on diagnostic radiology that represents current clinical practice (i.e., X-ray, US, CT, and MRI), as well as on advanced imaging techniques that are currently under investigation, including precision and quantitative imaging (e.g., radiomics, texture analysis, and artificial intelligence) that will hopefully represent clinical practice in the future.

Dr. Federica Vernuccio
Dr. Roberto Cannella
Dr. Albert Comelli
Guest Editors

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 100 words) can be sent to the Editorial Office for announcement on this website.

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

oncology
precision medicine
emergency medicine
standardized reporting
texture analysis
imaging
MRI
CT
quantitative imaging
machine learning

Published Papers (9 papers)

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Research

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13 pages, 1324 KiB

Open AccessArticle

The Relationship between Planar and SPECT/CT Parameters and Functional Markers in Primary Hyperparathyroidism

by Guler Silov and Serpil Erdogan Ozbodur

Diagnostics 2023, 13(20), 3182; https://doi.org/10.3390/diagnostics13203182 - 11 Oct 2023

Viewed by 1135

Abstract

This study aimed to investigate the relationship between quantitative and volumetric parameters of technetium-99-methoxyisobutylisonitrile (99mTc-MIBI) single-photon emission computed tomography/computed tomography (SPECT/CT) imaging and hormonal and biochemical markers in primary hyperparathyroidism (PHPT) patients with single adenoma. In this retrospective study, 70 patients with a single adenoma who underwent 99mTc-MIBI imaging for the diagnosis of PHPT were examined. Early and delayed MIBI lesion/background ratios (eLBR and dLBR), early and delayed lesion/thyroid ratio (eLTR and dLTR), and retention index (RI) were calculated as planar dual-phase scintigraphy parameters. Adenoma volume (Svol) and parathormone (PTH)/Svol ratio were measured as SPECT/CT-derived parameters. Calcium levels exhibited a positive correlation with eLBR (r = 0.33, p < 0.001), dLBR (r = 0.29, p = 0.01), dLTR (r = 0.31, p < 0.001), and PTH/Svol (r = 0.38, p < 0.001). PTH did not correlate with planar parameters and Svol. Among the imaging parameters, only the PTH/Svol ratio showed a negative correlation with phosphorus levels (r = −0.29, p = 0.02). For predicting disease severity, the PTH/Svol ratio exhibited similar diagnostic performance to PTH and phosphorus levels but outperformed the eLBR and dLBR. Both planar and SPECT-derived parameters can provide valuable insights into the functional status of the parathyroid adenoma and the associated disease severity. PTH/Svol ratio, combining imaging and laboratory findings to provide a more comprehensive approach to patient care, could be an exciting new indicator. Full article

(This article belongs to the Special Issue Improving Imaging Diagnosis: From Conventional Radiology to Advanced Imaging Techniques)

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11 pages, 1879 KiB

Open AccessArticle

Exploring the Utility of Cardiovascular Magnetic Resonance Radiomic Feature Extraction for Evaluation of Cardiac Sarcoidosis

by Nouf A. Mushari, Georgios Soultanidis, Lisa Duff, Maria G. Trivieri, Zahi A. Fayad, Philip M. Robson and Charalampos Tsoumpas

Diagnostics 2023, 13(11), 1865; https://doi.org/10.3390/diagnostics13111865 - 26 May 2023

Cited by 3 | Viewed by 1172

Abstract

Background: The aim of this study is to explore the utility of cardiac magnetic resonance (CMR) imaging of radiomic features to distinguish active and inactive cardiac sarcoidosis (CS). Methods: Subjects were classified into active cardiac sarcoidosis (CS_active) and inactive cardiac sarcoidosis (CS_inactive) based on PET-CMR imaging. CS_active was classified as featuring patchy [¹⁸F]fluorodeoxyglucose ([¹⁸F]FDG) uptake on PET and presence of late gadolinium enhancement (LGE) on CMR, while CS_inactive was classified as featuring no [¹⁸F]FDG uptake in the presence of LGE on CMR. Among those screened, thirty CS_active and thirty-one CS_inactive patients met these criteria. A total of 94 radiomic features were subsequently extracted using PyRadiomics. The values of individual features were compared between CS_active and CS_inactive using the Mann–Whitney U test. Subsequently, machine learning (ML) approaches were tested. ML was applied to two sub-sets of radiomic features (signatures A and B) that were selected by logistic regression and PCA, respectively. Results: Univariate analysis of individual features showed no significant differences. Of all features, gray level co-occurrence matrix (GLCM) joint entropy had a good area under the curve (AUC) and accuracy with the smallest confidence interval, suggesting it may be a good target for further investigation. Some ML classifiers achieved reasonable discrimination between CS_active and CS_inactive patients. With signature A, support vector machine and k-neighbors showed good performance with AUC (0.77 and 0.73) and accuracy (0.67 and 0.72), respectively. With signature B, decision tree demonstrated AUC and accuracy around 0.7; Conclusion: CMR radiomic analysis in CS provides promising results to distinguish patients with active and inactive disease. Full article

(This article belongs to the Special Issue Improving Imaging Diagnosis: From Conventional Radiology to Advanced Imaging Techniques)

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11 pages, 3390 KiB

Open AccessArticle

Motion-Corrected versus Conventional Diffusion-Weighted Magnetic Resonance Imaging of the Liver Using Non-Rigid Registration

by Je Seung Son, Hee Sun Park, Sungeun Park, Young Jun Kim, Mi Hye Yu, Sung Il Jung, Munyoung Paek and Marcel Dominik Nickel

Diagnostics 2023, 13(6), 1008; https://doi.org/10.3390/diagnostics13061008 - 7 Mar 2023

Cited by 1 | Viewed by 1690

Abstract

It is challenging to overcome motion artifacts in diffusion-weighted imaging (DWI) of the abdomen. This study aimed to evaluate the image quality of motion-corrected DWI of the liver using non-rigid registration in comparison with conventional DWI (c-DWI) in patients with liver diseases. Eighty-nine patients who underwent 3-T magnetic resonance imaging (MRI) of the liver were retrospectively included. DWI was performed using c-DWI and non-rigid motion-corrected (moco) DWI was performed in addition to c-DWI. The image quality and conspicuity of hepatic focal lesions were scored using a five-point scale by two radiologists and compared between the two DWI image sets. The apparent diffusion coefficient (ADC) was measured in three regions of the liver parenchyma and in hepatic focal lesions, and compared between the two DWI image sets. Moco-DWI achieved higher scores in image quality compared to c-DWI in terms of liver edge sharpness and hepatic vessel margin delineation. The conspicuity scores of hepatic focal lesions were higher in moco-DWI. The standard deviation values of ADC of the liver parenchyma were lower in the moco-DWI than in the c-DWI. Moco-DWI using non-rigid registration showed improved overall image quality and provided more reliable ADC measurement, with an equivalent scan time, compared with c-DWI. Full article

(This article belongs to the Special Issue Improving Imaging Diagnosis: From Conventional Radiology to Advanced Imaging Techniques)

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13 pages, 2563 KiB

Open AccessArticle

Texture Parameters Measured by UHF-MRI and CT Scan Provide Information on Bone Quality in Addition to BMD: A Biomechanical Ex Vivo Study

by Paul Knoepflin, Martine Pithioux, David Bendahan, François Poullain, Thomas Le Corroller, Cyprien Fabre, Vanessa Pauly, Maud Creze, Enrico Soldati, Pierre Champsaur and Daphne Guenoun

Diagnostics 2022, 12(12), 3143; https://doi.org/10.3390/diagnostics12123143 - 13 Dec 2022

Cited by 3 | Viewed by 1350

Abstract

The current definition of osteoporosis includes alteration of bone quality. The assessment of bone quality is improved by the development of new texture analysis softwares. Our objectives were to assess if proximal femoral trabecular bone texture measured in Ultra high field (UHF) 7 Tesla MRI and CT scan were related to biomechanical parameters, and if the combination of texture parameters and areal bone mineral density (aBMD) measured by dual-energy X-ray absorptiometry provided a better prediction of femoral failure than aBMD alone. The aBMD of 16 proximal femur ends from eight cadavers were investigated. Nineteen textural parameters were computed in three regions or volumes of interest for each specimen on UHF MRI and CT scan. Then, the corresponding failure load and failure stress were calculated thanks to mechanical compression test. aBMD was not correlated to failure load (R² = 0.206) and stress (R² = 0.153). The failure load was significantly correlated with ten parameters in the greater trochanter using UHF MRI, and with one parameter in the neck and the greater trochanter using CT scan. Eight parameters in the greater trochanter using UHF MRI combined with aBMD improved the failure load prediction, and seven parameters improved the failure stress prediction. Our results suggest that textural parameters provide additional information on the fracture risk of the proximal femur when aBMD is not contributive. Full article

(This article belongs to the Special Issue Improving Imaging Diagnosis: From Conventional Radiology to Advanced Imaging Techniques)

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14 pages, 4480 KiB

Open AccessArticle

Stability and Reproducibility of Radiomic Features Based on Various Segmentation Techniques on Cervical Cancer DWI-MRI

by Zarina Ramli, Muhammad Khalis Abdul Karim, Nuraidayani Effendy, Mohd Amiruddin Abd Rahman, Mohd Mustafa Awang Kechik, Mohamad Johari Ibahim and Nurin Syazwina Mohd Haniff

Diagnostics 2022, 12(12), 3125; https://doi.org/10.3390/diagnostics12123125 - 12 Dec 2022

Cited by 7 | Viewed by 1626

Abstract

Cervical cancer is the most common cancer and ranked as 4th in morbidity and mortality among Malaysian women. Currently, Magnetic Resonance Imaging (MRI) is considered as the gold standard imaging modality for tumours with a stage higher than IB2, due to its superiority in diagnostic assessment of tumour infiltration with excellent soft-tissue contrast. In this research, the robustness of semi-automatic segmentation has been evaluated using a flood-fill algorithm for quantitative feature extraction, using 30 diffusion weighted MRI images (DWI-MRI) of cervical cancer patients. The relevant features were extracted from DWI-MRI segmented images of cervical cancer. First order statistics, shape features, and textural features were extracted and analysed. The intra-class relation coefficient (ICC) was used to compare 662 radiomic features extracted from manual and semi-automatic segmentations. Notably, the features extracted from the semi-automatic segmentation and flood filling algorithm (average ICC = 0.952 0.009, p > 0.05) were significantly higher than the manual extracted features (average ICC = 0.897 0.011, p > 0.05). Henceforth, we demonstrate that the semi-automatic segmentation is slightly expanded to manual segmentation as it produces more robust and reproducible radiomic features. Full article

(This article belongs to the Special Issue Improving Imaging Diagnosis: From Conventional Radiology to Advanced Imaging Techniques)

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Review

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19 pages, 1206 KiB

Open AccessReview

Application of Multimodal MRI in the Early Diagnosis of Autism Spectrum Disorders: A Review

by Miaoyan Wang, Dandan Xu, Lili Zhang and Haoxiang Jiang

Diagnostics 2023, 13(19), 3027; https://doi.org/10.3390/diagnostics13193027 - 22 Sep 2023

Cited by 3 | Viewed by 2600

Abstract

Autism spectrum disorder (ASD) is a neurodevelopmental disorder in children. Early diagnosis and intervention can remodel the neural structure of the brain and improve quality of life but may be inaccurate if based solely on clinical symptoms and assessment scales. Therefore, we aimed to analyze multimodal magnetic resonance imaging (MRI) data from the existing literature and review the abnormal changes in brain structural–functional networks, perfusion, neuronal metabolism, and the glymphatic system in children with ASD, which could help in early diagnosis and precise intervention. Structural MRI revealed morphological differences, abnormal developmental trajectories, and network connectivity changes in the brain at different ages. Functional MRI revealed disruption of functional networks, abnormal perfusion, and neurovascular decoupling associated with core ASD symptoms. Proton magnetic resonance spectroscopy revealed abnormal changes in the neuronal metabolites during different periods. Decreased diffusion tensor imaging signals along the perivascular space index reflected impaired glymphatic system function in children with ASD. Differences in age, subtype, degree of brain damage, and remodeling in children with ASD led to heterogeneity in research results. Multimodal MRI is expected to further assist in early and accurate clinical diagnosis of ASD through deep learning combined with genomics and artificial intelligence. Full article

(This article belongs to the Special Issue Improving Imaging Diagnosis: From Conventional Radiology to Advanced Imaging Techniques)

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12 pages, 1762 KiB

Open AccessReview

Could Spinal Epidural Lipomatosis Be the Hallmark of Metabolic Syndrome on the Spine? A Literature Review with Emphasis on Etiology

by Valerio D’Agostino, Miriana Rosaria Petrera, Giuseppe Tedesco, Valerio Pipola, Federico Ponti and Paolo Spinnato

Diagnostics 2023, 13(2), 322; https://doi.org/10.3390/diagnostics13020322 - 16 Jan 2023

Cited by 5 | Viewed by 5920

Abstract

Spinal epidural lipomatosis is defined by an excessive amount of epidural fat in the spinal canal, usually in the lumbosacral tract: a well-known cause of lumbar pain and spinal stenosis with a possible wide range of neurological symptoms. Recent research data reveal that, nowadays, obesity has become the main cause of spinal epidural lipomatosis. Moreover, this condition was recently recognized as a previously unknown manifestation of metabolic syndrome. Radiological studies (CT and MRI) are the only tools that are able to diagnose the disease non-invasively. Indeed, radiologists play a key role in disease recognition, with subsequent possible implications on patients’ systemic health assessments. Despite its clinical importance, the condition is still underreported and neglected. The current literature review summarizes all the main etiologies of spinal epidural lipomatosis, particularly regarding its linkage with metabolic syndrome. An overview of disease characteristics from diagnosis to treatment strategies is also provided. Full article

(This article belongs to the Special Issue Improving Imaging Diagnosis: From Conventional Radiology to Advanced Imaging Techniques)

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15 pages, 19642 KiB

Open AccessReview

The Neoplastic Side of the Abdominal Wall: A Comprehensive Pictorial Essay of Benign and Malignant Neoplasms

by Giorgia Porrello, Roberto Cannella, Eduardo Alvarez-Hornia Pérez, Giuseppe Brancatelli and Federica Vernuccio

Diagnostics 2023, 13(2), 315; https://doi.org/10.3390/diagnostics13020315 - 15 Jan 2023

Cited by 1 | Viewed by 2846

Abstract

Abdominal wall neoplasms are usually benign and, in the majority of these cases, no further work-up or treatment is indicated. The percentage of malignant abdominal neoplasms, however, is not negligible. Radiologists play a pivotal role in identifying imaging features that should favor malignancy, including larger lesion size, edema, neurovascular involvement, and peripheral or inhomogeneous dynamic enhancement, thus indicating to the clinician the need for further work-up. Histopathology is the reference standard for the characterization of abdominal wall neoplasms. In patients undergoing surgery, radiological assessment is needed to guide the surgeon by providing a comprehensive anatomic guide of the tumor extension. We present a pictorial review of benign and malignant abdominal wall neoplasms that can be encountered on radiological examinations, with a main focus on CT and MRI features that help in narrowing the differential diagnosis. Full article

(This article belongs to the Special Issue Improving Imaging Diagnosis: From Conventional Radiology to Advanced Imaging Techniques)

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16 pages, 6138 KiB

Open AccessReview

The Benign Side of the Abdominal Wall: A Pictorial Review of Non-Neoplastic Diseases

by Giorgia Porrello, Federica Vernuccio, Eduardo Alvarez-Hornia Pérez, Giuseppe Brancatelli and Roberto Cannella

Diagnostics 2022, 12(12), 3211; https://doi.org/10.3390/diagnostics12123211 - 17 Dec 2022

Cited by 1 | Viewed by 5908

Abstract

The abdominal wall is the location of a wide spectrum of pathological conditions, from benign to malignant ones. Imaging is often recommended for the evaluation of known palpable abdominal masses. However, abdominal wall pathologies are often incidentally discovered and represent a clinical and diagnostic challenge. Knowledge of the possible etiologies and complications, combined with clinical history and laboratory findings, is crucial for the correct management of these conditions. Specific imaging clues can help the radiologist narrow the differential diagnosis and distinguish between malignant and benign processes. In this pictorial review, we will focus on the non-neoplastic benign masses and processes that can be encountered on the abdominal wall on cross-sectional imaging, with a particular focus on their management. Distinctive sonographic imaging clues, compared with computed tomography (CT) and magnetic resonance (MR) findings will be highlighted, together with clinical and practical tips for reaching the diagnosis and guiding patient management, to provide a complete diagnostic guide for the radiologist. Full article

(This article belongs to the Special Issue Improving Imaging Diagnosis: From Conventional Radiology to Advanced Imaging Techniques)

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