Special Issue "Quantitative Imaging in Oncology"

A special issue of Tomography (ISSN 2379-139X).

Deadline for manuscript submissions: 30 December 2022 | Viewed by 1688

Special Issue Editor

Dr. Wonmo Sung
E-Mail Website
Guest Editor
Department of Biomedical Engineering, College of Medicine, The Catholic University of Korea, Seoul 06591, Korea
Interests: radiology; radiation oncology; medical physics; tumor

Special Issue Information

Dear Colleagues, 

The field of quantitative imaging analysis in oncology is rapidly evolving. Quantitative imaging in oncology has reached a critical mass of investigative capacity, ranging from molecular imaging to CT/MR-based imaging to image-guided radiation therapy. Imaging ability to diagnose and evaluate therapy response and forecast symptom development in cancer has advanced significantly. Moreover, advanced machine learning techniques, such as neural networks, are transforming the practice of quantitative imaging in oncology. Thus, this Special Issue is looking for papers, including the development and implementation of quantitative imaging methods, imaging protocols, software, and machine learning solutions for cancer patients.

Dr. Wonmo Sung
Guest Editor

Manuscript Submission Information

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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. Tomography is an international peer-reviewed open access semimonthly journal published by MDPI.

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Keywords

  • radiology
  • radiation therapy
  • quantitative imaging
  • tumor

Published Papers (3 papers)

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Research

Article
Chemical Exchange Saturation Transfer for Lactate-Weighted Imaging at 3 T MRI: Comprehensive In Silico, In Vitro, In Situ, and In Vivo Evaluations
Tomography 2022, 8(3), 1277-1292; https://doi.org/10.3390/tomography8030106 - 07 May 2022
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Abstract
Based on in silico, in vitro, in situ, and in vivo evaluations, this study aims to establish and optimize the chemical exchange saturation transfer (CEST) imaging of lactate (Lactate-CEST—LATEST). To this end, we optimized LATEST sequences using Bloch–McConnell simulations for optimal detection of [...] Read more.
Based on in silico, in vitro, in situ, and in vivo evaluations, this study aims to establish and optimize the chemical exchange saturation transfer (CEST) imaging of lactate (Lactate-CEST—LATEST). To this end, we optimized LATEST sequences using Bloch–McConnell simulations for optimal detection of lactate with a clinical 3 T MRI scanner. The optimized sequences were used to image variable lactate concentrations in vitro (using phantom measurements), in situ (using nine human cadaveric lower leg specimens), and in vivo (using four healthy volunteers after exertional exercise) that were then statistically analyzed using the non-parametric Friedman test and Kendall Tau-b rank correlation. Within the simulated Bloch–McConnell equations framework, the magnetization transfer ratio asymmetry (MTRasym) value was quantified as 0.4% in the lactate-specific range of 0.5–1 ppm, both in vitro and in situ, and served as the imaging surrogate of the lactate level. In situ, significant differences (p < 0.001) and strong correlations (τ = 0.67) were observed between the MTRasym values and standardized intra-muscular lactate concentrations. In vivo, a temporary increase in the MTRasym values was detected after exertional exercise. In this bench-to-bedside comprehensive feasibility study, different lactate concentrations were detected using an optimized LATEST imaging protocol in vitro, in situ, and in vivo at 3 T, which prospectively paves the way towards non-invasive quantification and monitoring of lactate levels across a broad spectrum of diseases. Full article
(This article belongs to the Special Issue Quantitative Imaging in Oncology)
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Article
Quantitative Assessment of Airway Changes in Fibrotic Interstitial Lung Abnormality Patients by Chest CT According to Cumulative Cigarette Smoking
Tomography 2022, 8(2), 1024-1032; https://doi.org/10.3390/tomography8020082 - 03 Apr 2022
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Abstract
Purpose: The aim of this study was to evaluate the role of Pi10 in patients with fibrotic interstitial lung abnormality (fibrotic ILA) in a chest CT, according to cumulative cigarette smoking. Methods: We retrospectively assessed 54 fibrotic ILA patients and 18 healthy non-smokers [...] Read more.
Purpose: The aim of this study was to evaluate the role of Pi10 in patients with fibrotic interstitial lung abnormality (fibrotic ILA) in a chest CT, according to cumulative cigarette smoking. Methods: We retrospectively assessed 54 fibrotic ILA patients and 18 healthy non-smokers (control) who underwent non-enhanced CT and pulmonary function tests. We quantitatively analyzed airway changes (the inner luminal area, airway inner parameter, airway wall thickness, Pi10, skewness, and kurtosis) in the chest CT of fibrotic ILA patients, and the fibrotic ILA patients were categorized into groups based on pack-years: light, moderate, heavy. Airway change data and pulmonary function tests among the three groups of fibrotic ILA patients were compared with those of the control group by one-way ANOVA. Results: Mean skewness (2.58 ± 0.36) and kurtosis (7.64 ± 2.36) in the control group were significantly different from those of the fibrotic ILA patients (1.89 ± 0.37 and 3.62 ± 1.70, respectively, p < 0.001). In fibrotic ILA group, only heavy smokers had significantly increased Pi10 (mean increase 0.04, p = 0.013), increased airway wall thickness of the segmental bronchi (mean increase 0.06 mm, p = 0.005), and decreased lung diffusing capacity for carbon monoxide (p = 0.023). Conclusion: Pi10, as a biomaker of quantitative CT in fibrotic ILA patients, can reveal that smoking affects airway remodeling. Full article
(This article belongs to the Special Issue Quantitative Imaging in Oncology)
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Article
Ipsilateral Recurrence of DCIS in Relation to Radiomics Features on Contrast Enhanced Breast MRI
Tomography 2022, 8(2), 596-606; https://doi.org/10.3390/tomography8020049 - 01 Mar 2022
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Abstract
The purpose of this retrospective study was to investigate the association between ipsilateral recurrence of ductal carcinoma in situ (DCIS) and radiomics features from DCIS and contralateral normal breast on contrast enhanced breast MR imaging. A total of 163 patients with DCIS who [...] Read more.
The purpose of this retrospective study was to investigate the association between ipsilateral recurrence of ductal carcinoma in situ (DCIS) and radiomics features from DCIS and contralateral normal breast on contrast enhanced breast MR imaging. A total of 163 patients with DCIS who underwent preoperative MR imaging between January 2010 and December 2014 were included (training cohort; n = 117, validation cohort; n = 46). Radiomics features were extracted from whole tumor volume of DCIS on early dynamic T1-subtraction images and from the contralateral normal breast on precontrast T1 and early dynamic T1-subtraction images. After feature selection, a Rad-score was established by LASSO Cox regression model. Performance of Rad-score was evaluated by the receiver operating characteristic (ROC) curve and Kaplan Meier curve with log rank test. The Rad-score was significantly associated with ipsilateral recurrence free survival (RFS). The low-risk group with a low Rad-score showed higher ipsilateral RFS than the high-risk group with a high Rad-score in both training and validation cohorts (p < 0.01). The Rad-score based on radiomics features from DCIS and contralateral normal breast on breast MR imaging showed the potential for prediction of ipsilateral RFS of DCIS. Full article
(This article belongs to the Special Issue Quantitative Imaging in Oncology)
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