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Emerging Technologies for Medical Imaging - Diagnostics, Monitoring and Therapy...
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Emerging Technologies for Medical Imaging - Diagnostics, Monitoring and Therapy of Cancers

A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Nuclear Medicine & Radiology".

Deadline for manuscript submissions: closed (15 November 2020) | Viewed by 65615

Special Issue Editors

Prof. Dr. Mohsen Beheshti

E-Mail Website
Guest Editor
Professor & Head, Teaching & Research Division of Translational Nuclear Medicine, Deputy Director, Department of Nuclear Medicine, University Hospital, RWTH University Aachen, Pauwelsstrasse 30, 52074 Aachen, Germany
Interests: PET Imaging; Nuclear Medicine; Computed Tomography; PET/CT; Molecular Imaging; Medical Imaging Physics; Cancer Imaging
Prof. Dr. Felix M. Mottaghy

E-Mail Website
Guest Editor
1. Director, Department of Nuclear Medicine, University Hospital, RWTH University Aachen, Pauwelsstrasse 30, 52074 Aachen, Germany
2. Department of Radiology and Nuclear Medicine, Maastricht University Medical Center (MUMC+), P. Debeylaan 25, 6229 HX Maastricht, P.O. Box 5800, 6202 AZ Maastricht, The Netherlands
Interests: radiation detection; neuroimaging; medical image analysis; medical imaging

Special Issue Information

Dear Colleagues,

In the area of emerging approaches in personalized medicine, the diagnostic accuracy of tests, either imaging, lab values or genetic measures is one of the main cornerstones for its success. In this era, a theranostic approach using targeted radionuclide therapy has unique promise for personalized treatment of cancer, as both the targeting vehicle and the radionuclide can be tailored to the individual patient. In addition, the related information of medical imaging is used in initial decision making as well as in the monitoring of running therapies. Coming with the exponential development of information technologies and the extraordinary capacity of current software developments, with an important aspect being the ability to process huge amounts data in a very short time frame, imaging technologies as well as post processing approaches of imaging data have made an important progression in the past 10 years. In this Special Issue we would like to focus on new hardware and software developments that provide promising new aspects for improving patient care. Last but not least, the very important aspect of the use of artificial intelligence in image data acquisition, evaluation and postprocessing will be highlighted. The main focus in this Special Issue will be on all different aspects of molecular imaging and theranostic approaches evolving from this.

Prof. Dr. Mohsen Beheshti
Prof. Dr. Felix M. Mottaghy
Guest Editors

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. Journal of Clinical Medicine 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

  • Molecular imaging
  • Hybrid imaging
  • Positron emission tomography
  • MRI
  • CT
  • Artificial intelligence
  • Decision support
  • Theranostics

Published Papers (16 papers)

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Editorial

Jump to: Research, Review

4 pages, 166 KiB  
Editorial
Special Issue: Emerging Technologies for Medical Imaging Diagnostics, Monitoring and Therapy of Cancers
by Mohsen Beheshti and Felix M. Mottaghy
J. Clin. Med. 2021, 10(6), 1327; https://doi.org/10.3390/jcm10061327 - 23 Mar 2021
Viewed by 1670
Abstract
Molecular imaging and therapy play an increasingly important role in the field of “precision medicine” as an emergent prospect for management of the cancerous disease [...] Full article
(This article belongs to the Special Issue Emerging Technologies for Medical Imaging - Diagnostics, Monitoring and Therapy of Cancers)

Research

Jump to: Editorial, Review

12 pages, 792 KiB  
Article
MRI Texture Analysis for the Prediction of Stereotactic Radiosurgery Outcomes in Brain Metastases from Lung Cancer
by Jung Hyun Park, Byung Se Choi, Jung Ho Han, Chae-Yong Kim, Jungheum Cho, Yun Jung Bae, Leonard Sunwoo and Jae Hyoung Kim
J. Clin. Med. 2021, 10(2), 237; https://doi.org/10.3390/jcm10020237 - 11 Jan 2021
Cited by 3 | Viewed by 2102
Abstract
This study aims to evaluate the utility of texture analysis in predicting the outcome of stereotactic radiosurgery (SRS) for brain metastases from lung cancer. From 83 patients with lung cancer who underwent SRS for brain metastasis, a total of 118 metastatic lesions were [...] Read more.
This study aims to evaluate the utility of texture analysis in predicting the outcome of stereotactic radiosurgery (SRS) for brain metastases from lung cancer. From 83 patients with lung cancer who underwent SRS for brain metastasis, a total of 118 metastatic lesions were included. Two neuroradiologists independently performed magnetic resonance imaging (MRI)-based texture analysis using the Imaging Biomarker Explorer software. Inter-reader reliability as well as univariable and multivariable analyses were performed for texture features and clinical parameters to determine independent predictors for local progression-free survival (PFS) and overall survival (OS). Furthermore, Harrell’s concordance index (C-index) was used to assess the performance of the independent texture features. The primary tumor histology of small cell lung cancer (SCLC) was the only clinical parameter significantly associated with local PFS in multivariable analysis. Run-length non-uniformity (RLN) and short-run emphasis were the independent texture features associated with local PFS. In the non-SCLC (NSCLC) subgroup analysis, RLN and local range mean were associated with local PFS. The C-index of independent texture features was 0.79 for the all-patients group and 0.73 for the NSCLC subgroup. In conclusion, texture analysis on pre-treatment MRI of lung cancer patients with brain metastases may have a role in predicting SRS response. Full article
(This article belongs to the Special Issue Emerging Technologies for Medical Imaging - Diagnostics, Monitoring and Therapy of Cancers)
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14 pages, 2474 KiB  
Article
Application of Deep Learning in the Identification of Cerebral Hemodynamics Data Obtained from Functional Near-Infrared Spectroscopy: A Preliminary Study of Pre- and Post-Tooth Clenching Assessment
by Shinya Takagi, Shigemitsu Sakuma, Ichizo Morita, Eri Sugimoto, Yoshihiro Yamaguchi, Naoya Higuchi, Kyoko Inamoto, Yoshiko Ariji, Eiichiro Ariji and Hiroshi Murakami
J. Clin. Med. 2020, 9(11), 3475; https://doi.org/10.3390/jcm9113475 - 28 Oct 2020
Cited by 5 | Viewed by 1956
Abstract
In fields using functional near-infrared spectroscopy (fNIRS), there is a need for an easy-to-understand method that allows visual presentation and rapid analysis of data and test results. This preliminary study examined whether deep learning (DL) could be applied to the analysis of fNIRS-derived [...] Read more.
In fields using functional near-infrared spectroscopy (fNIRS), there is a need for an easy-to-understand method that allows visual presentation and rapid analysis of data and test results. This preliminary study examined whether deep learning (DL) could be applied to the analysis of fNIRS-derived brain activity data. To create a visual presentation of the data, an imaging program was developed for the analysis of hemoglobin (Hb) data from the prefrontal cortex in healthy volunteers, obtained by fNIRS before and after tooth clenching. Three types of imaging data were prepared: oxygenated hemoglobin (oxy-Hb) data, deoxygenated hemoglobin (deoxy-Hb) data, and mixed data (using both oxy-Hb and deoxy-Hb data). To differentiate between rest and tooth clenching, a cross-validation test using the image data for DL and a convolutional neural network was performed. The network identification rate using Hb imaging data was relatively high (80‒90%). These results demonstrated that a method using DL for the assessment of fNIRS imaging data may provide a useful analysis system. Full article
(This article belongs to the Special Issue Emerging Technologies for Medical Imaging - Diagnostics, Monitoring and Therapy of Cancers)
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11 pages, 1434 KiB  
Article
18F-FDG PET/MR versus MR Alone in Whole-Body Primary Staging and Restaging of Patients with Rectal Cancer: What Is the Benefit of PET?
by Yan Li, Laura Isabel Mueller, Jan Peter Neuhaus, Stefanie Bertram, Benedikt Michael Schaarschmidt, Aydin Demircioglu, Johannes Maximilian Ludwig, Julian Kirchner, Christoph Rischpler, Ken Herrmann, Onofrio Antonio Catalano and Lale Umutlu
J. Clin. Med. 2020, 9(10), 3163; https://doi.org/10.3390/jcm9103163 - 29 Sep 2020
Cited by 12 | Viewed by 1973
Abstract
Background: To investigate and compare the diagnostic performance of 18F-Fluorodeoxyglucose (18F-FDG) PET/MR and MR alone in whole-body primary staging and restaging of patients with rectal cancer. Methods: A retrospective analysis was performed to evaluate diagnostic accuracies of combined reading of [...] Read more.
Background: To investigate and compare the diagnostic performance of 18F-Fluorodeoxyglucose (18F-FDG) PET/MR and MR alone in whole-body primary staging and restaging of patients with rectal cancer. Methods: A retrospective analysis was performed to evaluate diagnostic accuracies of combined reading of PET/MR and MR alone in T, N and M staging against the reference standard. Inter-observer agreement regarding TNM staging was calculated separately for PET/MR and MR alone. Results: A total of 39 studies of 34 patients could be evaluated. Diagnostic accuracies of PET/MR and MR alone were the same in locoregional T staging. For predicting N+ stage, the specificity of combined reading of PET and MR (0.917 and 0.833 for reader 1 and 2, respectively) was slightly higher than MR alone (0.833 and 0.75) without significantly increasing the overall accuracy (0.783 vs. 0.783 and 0.783 vs. 0.739). For detecting distant metastasis, the sensitivities of PET/MR and MR alone were shown equal (1.0 vs. 1.0 and 0.938 vs. 0.938), while the specificity of PET/MR was marginally lower (0.87 vs. 0.913 and 0.826 vs. 0.87). The inter-observer agreements were good to excellent in M (κ = 0.64 and 0.637 for PET/MR and MR alone, p < 0.001) and N staging (0.819 and 0.738, p < 0.001).Conclusion: PET did not yield a significant improvement in diagnostic accuracy of PET/MR in TNM staging of rectal cancer, since MR alone facilitated accurate classification of disease stage with good to excellent inter-observer agreement. Full article
(This article belongs to the Special Issue Emerging Technologies for Medical Imaging - Diagnostics, Monitoring and Therapy of Cancers)
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16 pages, 5482 KiB  
Article
Additional Value of 2-[18F]FDG PET/CT Comparing to MRI in Treatment Approach of Anal Cancer Patients
by Reyhaneh Manafi-Farid, Alexander Kupferthaler, Helwig Wundsam, Georg Gruber, Reza Vali, Clemens Venhoda, Christine Track, Ali Beheshti, Werner Langsteger, Hans Geinitz and Mohsen Beheshti
J. Clin. Med. 2020, 9(9), 2715; https://doi.org/10.3390/jcm9092715 - 22 Aug 2020
Cited by 8 | Viewed by 2624
Abstract
Accurate staging and treatment planning are imperative for precise management in Anal Cancer (ACa) patients. We aimed to evaluate the additive and prognostic value of pre-treatment 2-[18F]fluoro-2-deoxy-d-glucose positron emission tomography/computed tomography (2-[18F]FDG PET/CT) in the staging and [...] Read more.
Accurate staging and treatment planning are imperative for precise management in Anal Cancer (ACa) patients. We aimed to evaluate the additive and prognostic value of pre-treatment 2-[18F]fluoro-2-deoxy-d-glucose positron emission tomography/computed tomography (2-[18F]FDG PET/CT) in the staging and management of ACa compared to magnetic resonance imaging (MRI). This retrospective study was conducted on 54 patients. Pre-treatment 2-[18F]FDG PET/CT studies and MRI reports were compared considering the primary tumor, pelvic lymph nodes, and metastatic lesions. The impact of 2-[18F]FDG PET/CT in the management and its prognostic value, using maximum standardized uptake value (SUVmax), were assessed. Discordant findings were found in 46.3% of patients (5 in T; 1 in T and N; 18 in N; and 1 in M stage). 2-[18F]FDG PET/CT resulted in up-staging in 9.26% and down-staging in 3.7% of patients. Perirectal lymph nodes were metabolically inactive in 12.9% of patients. Moreover, 2-[18F]FDG PET/CT resulted in management change in 24.1% of patients. Finally, SUVmax provided no prognostic value. 2-[18F]FDG PET/CT altered staging and management in a sizable number of patients in this study, and supports a need for a change in guidelines for it to be used as a routine complementary test in the initial management of ACa. Full article
(This article belongs to the Special Issue Emerging Technologies for Medical Imaging - Diagnostics, Monitoring and Therapy of Cancers)
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15 pages, 2119 KiB  
Article
Diagnostic Performance of [18F]Fluorocholine and [68Ga]Ga-PSMA PET/CT in Prostate Cancer: A Comparative Study
by Zeinab Paymani, Taryn Rohringer, Reza Vali, Wolfgang Loidl, Nafiseh Alemohammad, Hans Geinitz, Werner Langsteger and Mohsen Beheshti
J. Clin. Med. 2020, 9(7), 2308; https://doi.org/10.3390/jcm9072308 - 21 Jul 2020
Cited by 11 | Viewed by 4874
Abstract
The current study endeavored to closely compare the detection rate of 68-Gallium labelled prostate-specific membrane antigen ([68Ga]Ga-PSMA) versus [18F]Fluorocholine in men with prostate cancer (PC), to investigate the benefits and pitfalls of each modality in the setting of various [...] Read more.
The current study endeavored to closely compare the detection rate of 68-Gallium labelled prostate-specific membrane antigen ([68Ga]Ga-PSMA) versus [18F]Fluorocholine in men with prostate cancer (PC), to investigate the benefits and pitfalls of each modality in the setting of various patient characteristics. We retrospectively analyzed 29 biopsy-proven PC patients in two categories, staging and restaging, who underwent both scans within a maximum of 30 days of each other. Variables including patient demographics, prostate specific antigen (PSA) level, Gleason score, clinical course, and following treatments were recorded. The number and location of suspicious lesions as well as uptake values were noted. A total of 148 suspicious lesions were detected, of which 70.9% (105/148) were concordantly visualized in both imaging modalities. [68Ga]Ga-PSMA positron emission tomography/computed tomography (PET/CT) revealed a higher number of metastatic lesions per patients (91% vs 78%). The mean of maximum standardized uptake value (SUV max) in concordant lesions was significantly higher in [68Ga]Ga-PSMA compared to [18F]Fluorocholine PET/CT (14.6 ± 8.44 vs. 6.9 ± 3.4, p = 0.001). Discordant lesions were detected by both modalities, but more frequently by [68Ga]Ga-PSMA PET/CT (20.3% in [68Ga]Ga-PSMA versus 8.8% by [18F]Fluorocholine PET/CT). In patients with PSA levels below 1.0 ng/mL and <2.0 ng/mL, [18F]Fluorocholine PET/CT detection rate was half (57% and 55%, respectively) that of [68Ga]Ga-PSMA PET/CT. Tumor, nodes and metastases (TNM) staging, and subsequently patient management, was only influenced in 4/29 patients (14%), particularly by [68Ga]Ga-PSMA PET/CT with PSA values under 0.5 ng/mL. [68Ga]Ga-PSMA PET/CT revealed superior diagnostic performance to [18F]Fluorocholine PET/CT in staging and restaging of PC patients, especially in cases with low PSA levels. However, in a few hormone resistant high-risk PC patients, [18F]Fluorocholine PET/CT may improve overall diagnostic accuracy. Full article
(This article belongs to the Special Issue Emerging Technologies for Medical Imaging - Diagnostics, Monitoring and Therapy of Cancers)
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10 pages, 1336 KiB  
Article
[99mTc]Sestamibi SPECT Can Predict Proliferation Index, Angiogenesis, and Vascular Invasion in Parathyroid Patients: A Retrospective Study
by Nicoletta Urbano, Manuel Scimeca, Carmela Di Russo, Alessandro Mauriello, Elena Bonanno and Orazio Schillaci
J. Clin. Med. 2020, 9(7), 2213; https://doi.org/10.3390/jcm9072213 - 13 Jul 2020
Cited by 9 | Viewed by 4713
Abstract
The aim of this study was to evaluate the possible association among sestamibi uptake and the main histopathological characteristics of parathyroid lesions related to aggressiveness such as the proliferation index (Ki67 expression and mitosis), angiogenesis (number of vessels), and vascular invasion in hyperparathyroidism [...] Read more.
The aim of this study was to evaluate the possible association among sestamibi uptake and the main histopathological characteristics of parathyroid lesions related to aggressiveness such as the proliferation index (Ki67 expression and mitosis), angiogenesis (number of vessels), and vascular invasion in hyperparathyroidism patients. To this end, 26 patients affected by primary hyperparathyroidism subjected to both scintigraphy with [99mTc]Sestamibi and surgery/bioptic procedure were retrospectively enrolled. Hyperfunctioning of the parathyroid was detected in 19 patients. Our data showed a significant positive association among the sestamibi uptake and the proliferation index histologically evaluated both in terms of the number of Ki67 positive cells and mitosis. According to these data, lesions with a higher valuer of L/N (lesion to nonlesion ratio) frequently showed several vessels in tumor areas and histological evidence of vascular invasion. It is noteworthy that among patients with negative scintigraphy, 2 patients showed a neoplastic lesion after surgery (histological analysis). However, it is important to highlight that these lesions displayed very low proliferation indexes, which was evaluated in terms of number of both mitosis and Ki67-positive cells, some/rare vessels in the main lesion, and no evidence of vascular invasion. In conclusion, data obtained on patients with positive or negative scintigraphy support the hypothesis that sestamibi can be a tracer that is capable of predicting some biological characteristics of parathyroid tumors such as angiogenesis, proliferation indexes, and the invasion of surrounding tissues or vessels. Full article
(This article belongs to the Special Issue Emerging Technologies for Medical Imaging - Diagnostics, Monitoring and Therapy of Cancers)
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10 pages, 908 KiB  
Article
Non-Invasive Assessment of Breast Cancer Molecular Subtypes with Multiparametric Magnetic Resonance Imaging Radiomics
by Doris Leithner, Marius E. Mayerhoefer, Danny F. Martinez, Maxine S. Jochelson, Elizabeth A. Morris, Sunitha B. Thakur and Katja Pinker
J. Clin. Med. 2020, 9(6), 1853; https://doi.org/10.3390/jcm9061853 - 14 Jun 2020
Cited by 53 | Viewed by 6527
Abstract
We evaluated the performance of radiomics and artificial intelligence (AI) from multiparametric magnetic resonance imaging (MRI) for the assessment of breast cancer molecular subtypes. Ninety-one breast cancer patients who underwent 3T dynamic contrast-enhanced (DCE) MRI and diffusion-weighted imaging (DWI) with apparent diffusion coefficient [...] Read more.
We evaluated the performance of radiomics and artificial intelligence (AI) from multiparametric magnetic resonance imaging (MRI) for the assessment of breast cancer molecular subtypes. Ninety-one breast cancer patients who underwent 3T dynamic contrast-enhanced (DCE) MRI and diffusion-weighted imaging (DWI) with apparent diffusion coefficient (ADC) mapping were included retrospectively. Radiomic features were extracted from manually drawn regions of interest (n = 704 features per lesion) on initial DCE-MRI and ADC maps. The ten best features for subtype separation were selected using probability of error and average correlation coefficients. For pairwise comparisons with >20 patients in each group, a multi-layer perceptron feed-forward artificial neural network (MLP-ANN) was used (70% of cases for training, 30%, for validation, five times each). For all other separations, linear discriminant analysis (LDA) and leave-one-out cross-validation were applied. Histopathology served as the reference standard. MLP-ANN yielded an overall median area under the receiver-operating-characteristic curve (AUC) of 0.86 (0.77–0.92) for the separation of triple negative (TN) from other cancers. The separation of luminal A and TN cancers yielded an overall median AUC of 0.8 (0.75–0.83). Radiomics and AI from multiparametric MRI may aid in the non-invasive differentiation of TN and luminal A breast cancers from other subtypes. Full article
(This article belongs to the Special Issue Emerging Technologies for Medical Imaging - Diagnostics, Monitoring and Therapy of Cancers)
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9 pages, 1145 KiB  
Article
Prognostic Implications of Combined Imaging and Histologic Criteria in Squamous Cell Carcinoma with Mandibular Invasion
by Chena Lee, Yoon Joo Choi, Kug Jin Jeon, Dong Wook Kim, Woong Nam, Hyung Jun Kim, In-Ho Cha and Sang Sun Han
J. Clin. Med. 2020, 9(5), 1335; https://doi.org/10.3390/jcm9051335 - 3 May 2020
Cited by 4 | Viewed by 3132
Abstract
Prognosis prediction of squamous cell carcinoma (SCC) with mandibular invasion is controversial, and a more sophisticated staging system to aid prognosis could be developed with imaging characteristics of bone invasion. Imaging-feature analysis provides practical, stratified results for survival prognosis in oral SCC (OSCC) [...] Read more.
Prognosis prediction of squamous cell carcinoma (SCC) with mandibular invasion is controversial, and a more sophisticated staging system to aid prognosis could be developed with imaging characteristics of bone invasion. Imaging-feature analysis provides practical, stratified results for survival prognosis in oral SCC (OSCC) of the mandible, and imaging advances enable more detailed tumor visualization. We retrospectively evaluated significant bone-invasion features associated with poor outcomes in mandibular OSCC to assess the predictive value of staging criteria that combined imaging features and histologic grade (combined imaging–histology (IH) grade) in 65 patients (39 men, 26 women) with mandibular SCC diagnosed from 2006 to 2016. Clinicopathologic features, including T-stage and histologic grade, and prognosis were retrieved. Tumors were classified into three types by extent of mandibular invasion on pretreatment imaging studies. Moreover, we assessed the involvement of the mandibular canal. We examined the correlation of factors associated with locoregional recurrence and overall mortality. The Harrell Concordance Index (C-index) determined prognostic performance of predictors. Nineteen (29%) patients showed locoregional recurrence and 13 (20%) died. For locoregional recurrence and mortality rates, imaging-detected mandibular canal (MC) involvement is a stronger prognostic factor for recurrence (C-index = 0.61 > 0.58) and survival (C-index = 0.58 > 0.63) than histopathologically confirmed perineural invasion, as was the IH grade, especially IH Grade 3, which was significantly associated with worse locoregional recurrence (p < 0.02). Imaging-based staging showed higher prognostic performance than T-staging (C-index = 0.57 (recurrence), 0.60 (death)), when combined with histologic grading (C-index = 0.69 for both) or used alone (C-index = 0.63 (locoregional recurrence), 0.69 (death)). Overall survival was significantly stratified by Imaging type and IH grade. Therefore, analysis of imaging features provided more specific, practical results for survival prognosis in mandibular OSCC. Imaging advances can potentially provide detailed gross views of tumor masses to facilitate development of prognostic criteria for OSCC. Full article
(This article belongs to the Special Issue Emerging Technologies for Medical Imaging - Diagnostics, Monitoring and Therapy of Cancers)
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27 pages, 6406 KiB  
Article
Artificial Intelligence-Based Diagnosis of Cardiac and Related Diseases
by Muhammad Arsalan, Muhammad Owais, Tahir Mahmood, Jiho Choi and Kang Ryoung Park
J. Clin. Med. 2020, 9(3), 871; https://doi.org/10.3390/jcm9030871 - 23 Mar 2020
Cited by 32 | Viewed by 4768
Abstract
Automatic chest anatomy segmentation plays a key role in computer-aided disease diagnosis, such as for cardiomegaly, pleural effusion, emphysema, and pneumothorax. Among these diseases, cardiomegaly is considered a perilous disease, involving a high risk of sudden cardiac death. It can be diagnosed early [...] Read more.
Automatic chest anatomy segmentation plays a key role in computer-aided disease diagnosis, such as for cardiomegaly, pleural effusion, emphysema, and pneumothorax. Among these diseases, cardiomegaly is considered a perilous disease, involving a high risk of sudden cardiac death. It can be diagnosed early by an expert medical practitioner using a chest X-Ray (CXR) analysis. The cardiothoracic ratio (CTR) and transverse cardiac diameter (TCD) are the clinical criteria used to estimate the heart size for diagnosing cardiomegaly. Manual estimation of CTR and other diseases is a time-consuming process and requires significant work by the medical expert. Cardiomegaly and related diseases can be automatically estimated by accurate anatomical semantic segmentation of CXRs using artificial intelligence. Automatic segmentation of the lungs and heart from the CXRs is considered an intensive task owing to inferior quality images and intensity variations using nonideal imaging conditions. Although there are a few deep learning-based techniques for chest anatomy segmentation, most of them only consider single class lung segmentation with deep complex architectures that require a lot of trainable parameters. To address these issues, this study presents two multiclass residual mesh-based CXR segmentation networks, X-RayNet-1 and X-RayNet-2, which are specifically designed to provide fine segmentation performance with a few trainable parameters compared to conventional deep learning schemes. The proposed methods utilize semantic segmentation to support the diagnostic procedure of related diseases. To evaluate X-RayNet-1 and X-RayNet-2, experiments were performed with a publicly available Japanese Society of Radiological Technology (JSRT) dataset for multiclass segmentation of the lungs, heart, and clavicle bones; two other publicly available datasets, Montgomery County (MC) and Shenzhen X-Ray sets (SC), were evaluated for lung segmentation. The experimental results showed that X-RayNet-1 achieved fine performance for all datasets and X-RayNet-2 achieved competitive performance with a 75% parameter reduction. Full article
(This article belongs to the Special Issue Emerging Technologies for Medical Imaging - Diagnostics, Monitoring and Therapy of Cancers)
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25 pages, 11473 KiB  
Article
Artificial Intelligence-Based Mitosis Detection in Breast Cancer Histopathology Images Using Faster R-CNN and Deep CNNs
by Tahir Mahmood, Muhammad Arsalan, Muhammad Owais, Min Beom Lee and Kang Ryoung Park
J. Clin. Med. 2020, 9(3), 749; https://doi.org/10.3390/jcm9030749 - 10 Mar 2020
Cited by 125 | Viewed by 9387
Abstract
Breast cancer is the leading cause of mortality in women. Early diagnosis of breast cancer can reduce the mortality rate. In the diagnosis, the mitotic cell count is an important biomarker for predicting the aggressiveness, prognosis, and grade of breast cancer. In general, [...] Read more.
Breast cancer is the leading cause of mortality in women. Early diagnosis of breast cancer can reduce the mortality rate. In the diagnosis, the mitotic cell count is an important biomarker for predicting the aggressiveness, prognosis, and grade of breast cancer. In general, pathologists manually examine histopathology images under high-resolution microscopes for the detection of mitotic cells. However, because of the minute differences between the mitotic and normal cells, this process is tiresome, time-consuming, and subjective. To overcome these challenges, artificial-intelligence-based (AI-based) techniques have been developed which automatically detect mitotic cells in the histopathology images. Such AI techniques accelerate the diagnosis and can be used as a second-opinion system for a medical doctor. Previously, conventional image-processing techniques were used for the detection of mitotic cells, which have low accuracy and high computational cost. Therefore, a number of deep-learning techniques that demonstrate outstanding performance and low computational cost were recently developed; however, they still require improvement in terms of accuracy and reliability. Therefore, we present a multistage mitotic-cell-detection method based on Faster region convolutional neural network (Faster R-CNN) and deep CNNs. Two open datasets (international conference on pattern recognition (ICPR) 2012 and ICPR 2014 (MITOS-ATYPIA-14)) of breast cancer histopathology were used in our experiments. The experimental results showed that our method achieves the state-of-the-art results of 0.876 precision, 0.841 recall, and 0.858 F1-measure for the ICPR 2012 dataset, and 0.848 precision, 0.583 recall, and 0.691 F1-measure for the ICPR 2014 dataset, which were higher than those obtained using previous methods. Moreover, we tested the generalization capability of our technique by testing on the tumor proliferation assessment challenge 2016 (TUPAC16) dataset and found that our technique also performs well in a cross-dataset experiment which proved the generalization capability of our proposed technique. Full article
(This article belongs to the Special Issue Emerging Technologies for Medical Imaging - Diagnostics, Monitoring and Therapy of Cancers)
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9 pages, 2823 KiB  
Article
Breast-Specific Gamma Imaging with [99mTc]Tc-Sestamibi: An In Vivo Analysis for Early Identification of Breast Cancer Lesions Expressing Bone Biomarkers
by Nicoletta Urbano, Manuel Scimeca, Carmela Di Russo, Elena Bonanno and Orazio Schillaci
J. Clin. Med. 2020, 9(3), 747; https://doi.org/10.3390/jcm9030747 - 10 Mar 2020
Cited by 6 | Viewed by 2557
Abstract
The main purpose of this pilot investigation was to evaluate the possible relationship among [99mTc]Tc-Sestamibi uptake, the presence of breast osteoblast-like cells, and the expression of molecules involved in bone metabolism, such as estrogen receptor, bone morphogenetic proteins-2, and PTX3. To [...] Read more.
The main purpose of this pilot investigation was to evaluate the possible relationship among [99mTc]Tc-Sestamibi uptake, the presence of breast osteoblast-like cells, and the expression of molecules involved in bone metabolism, such as estrogen receptor, bone morphogenetic proteins-2, and PTX3. To this end, forty consecutive breast cancer patients who underwent both breast-specific gamma imaging with [99mTc]Tc-Sestamibi and breast bioptic procedure were retrospectively enrolled. From each diagnostic paraffin block collected in the study, histological diagnosis, immunohistochemical investigations, and energy dispersive X-ray microanalysis were performed. Our data highlight the possible use of breast-specific gamma imaging with [99mTc]Tc-Sestamibi for the early detection of breast cancer lesions expressing bone biomarkers in the presence of breast osteoblast-like cells. Specifically, we show a linear association among sestamibi uptake, the presence of breast osteoblast-like cells, and the expression of estrogen receptor, bone morphogenetics proteins-2, and PTX3. Notably, we also observed an increase of [99mTc]Tc-Sestamibi in breast cancer lesions with magnesium-substituted hydroxyapatite. In conclusion, in this pilot study we evaluated data from the nuclear medicine unit and anatomic pathology department on breast cancer osteotropism, identifying a new possible interpretation of Breast Specific Gamma Imaging with [99mTc]Tc-Sestamibi analysis. Full article
(This article belongs to the Special Issue Emerging Technologies for Medical Imaging - Diagnostics, Monitoring and Therapy of Cancers)
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Review

Jump to: Editorial, Research

16 pages, 266 KiB  
Review
Advances in Molecular Imaging and Radionuclide Therapy of Neuroendocrine Tumors
by Anna Yordanova, Hans-Jürgen Biersack and Hojjat Ahmadzadehfar
J. Clin. Med. 2020, 9(11), 3679; https://doi.org/10.3390/jcm9113679 - 16 Nov 2020
Cited by 16 | Viewed by 2480
Abstract
Neuroendocrine neoplasms make up a heterogeneous group of tumors with inter-patient and intra-patient variabilities. Molecular imaging can help to identify and characterize neuroendocrine tumors (NETs). Furthermore, imaging and treatment with novel theranostics agents offers a new, tailored approach to managing NETs. Recent advances [...] Read more.
Neuroendocrine neoplasms make up a heterogeneous group of tumors with inter-patient and intra-patient variabilities. Molecular imaging can help to identify and characterize neuroendocrine tumors (NETs). Furthermore, imaging and treatment with novel theranostics agents offers a new, tailored approach to managing NETs. Recent advances in the management of NETs aim to enhance the effectiveness of targeted treatment with either modifications of known substances or the development of new substances with better targeting features. There have been several attempts to increase the detectability of NET lesions via positron emission tomography (PET) imaging and improvements in pretreatment planning using dosimetry. Especially notable is PET imaging with the radionuclide Copper-64. Increasing interest is also being paid to theranostics of grade 3 and purely differentiated NETs, for example, via targeting of the C-X-C motif chemokine receptor 4 (CXCR4). The aim of this review is to summarize the most relevant recent studies, which present promising new agents in molecular imaging and therapy for NETs, novel combination therapies and new applications of existing molecular imaging modalities in nuclear medicine. Full article
(This article belongs to the Special Issue Emerging Technologies for Medical Imaging - Diagnostics, Monitoring and Therapy of Cancers)
21 pages, 1862 KiB  
Review
Impact of PET/CT for Assessing Response to Immunotherapy—A Clinical Perspective
by David Lang, Gerald Wahl, Nikolaus Poier, Sebastian Graf, David Kiesl, Bernd Lamprecht and Michael Gabriel
J. Clin. Med. 2020, 9(11), 3483; https://doi.org/10.3390/jcm9113483 - 28 Oct 2020
Cited by 26 | Viewed by 4923
Abstract
Cancer immunotherapy using immune-checkpoint inhibitors (ICI) has revolutionized the therapeutic landscape of various malignancies like non-small-cell lung cancer or melanoma. Pre-therapy response prediction and assessment during ICI treatment is challenging due to the lack of reliable biomarkers and the possibility of atypical radiological [...] Read more.
Cancer immunotherapy using immune-checkpoint inhibitors (ICI) has revolutionized the therapeutic landscape of various malignancies like non-small-cell lung cancer or melanoma. Pre-therapy response prediction and assessment during ICI treatment is challenging due to the lack of reliable biomarkers and the possibility of atypical radiological response patterns. Positron emission tomography/computed tomography (PET/CT) enables the visualization and quantification of metabolic lesion activity additional to conventional CT imaging. Various biomarkers derived from PET/CT have been reported as predictors for response to ICI and may aid to overcome the challenges clinicians currently face in the management of ICI-treated patients. In this narrative review, experts in nuclear medicine, thoracic oncology, dermatooncology, hemato- and internal oncology, urological and head/neck tumors performed literature reviews in their respective field and a joint discussion on the use of PET/CT in the context of ICI treatment. The aims were to give a clinical overview on present standards and evidence, to identify current challenges and fields of research and to enable an outlook to future developments and their possible implications. Multiple promising studies concerning ICI response assessment or prediction using biomarkers derived from PET/CT alone or as composite biomarkers have been identified for various malignancies and disease stages. Of interest, additional major incentives in the field may evolve from novel tracers specifically targeting immune-checkpoint molecules which could allow not only response assessment and prognosis, but also visualization of histological tumor cell properties like programmed death-ligand (PD-L1) expression in vivo. Despite the broad range of existing literature on PET/CT-derived biomarkers in ICI therapy, implications for daily clinical practice remain elusive. High-quality prospective data are urgently warranted to determine whether patients benefit from the application of PET/CT in terms of prognosis. At the moment, the lack of such evidence as well as the absence of standardized imaging methods and biomarkers still precludes PET/CT imaging to be included in the relevant clinical practice guidelines. Full article
(This article belongs to the Special Issue Emerging Technologies for Medical Imaging - Diagnostics, Monitoring and Therapy of Cancers)
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24 pages, 2491 KiB  
Review
Targeted Palliative Radionuclide Therapy for Metastatic Bone Pain
by Reyhaneh Manafi-Farid, Fardad Masoumi, Ghasemali Divband, Bahare Saidi, Bahar Ataeinia, Fabian Hertel, Gregor Schweighofer-Zwink, Agnieszka Morgenroth and Mohsen Beheshti
J. Clin. Med. 2020, 9(8), 2622; https://doi.org/10.3390/jcm9082622 - 12 Aug 2020
Cited by 19 | Viewed by 6256
Abstract
Bone metastasis develops in multiple malignancies with a wide range of incidence. The presence of multiple bone metastases, leading to a multitude of complications and poorer prognosis. The corresponding refractory bone pain is still a challenging issue managed through multidisciplinary approaches to enhance [...] Read more.
Bone metastasis develops in multiple malignancies with a wide range of incidence. The presence of multiple bone metastases, leading to a multitude of complications and poorer prognosis. The corresponding refractory bone pain is still a challenging issue managed through multidisciplinary approaches to enhance the quality of life. Radiopharmaceuticals are mainly used in the latest courses of the disease. Bone-pain palliation with easy-to-administer radionuclides offers advantages, including simultaneous treatment of multiple metastatic foci, the repeatability and also the combination with other therapies. Several β¯- and α-emitters as well as pharmaceuticals, from the very first [89Sr]strontium-dichloride to recently introduced [223Ra]radium-dichloride, are investigated to identify an optimum agent. In addition, the combination of bone-seeking radiopharmaceuticals with chemotherapy or radiotherapy has been employed to enhance the outcome. Radiopharmaceuticals demonstrate an acceptable response rate in pain relief. Nevertheless, survival benefits have been documented in only a limited number of studies. In this review, we provide an overview of bone-seeking radiopharmaceuticals used for bone-pain palliation, their effectiveness and toxicity, as well as the results of the combination with other therapies. Bone-pain palliation with radiopharmaceuticals has been employed for eight decades. However, there are still new aspects yet to be established. Full article
(This article belongs to the Special Issue Emerging Technologies for Medical Imaging - Diagnostics, Monitoring and Therapy of Cancers)
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16 pages, 6901 KiB  
Review
Advancements in PARP1 Targeted Nuclear Imaging and Theranostic Probes
by Ramya Ambur Sankaranarayanan, Susanne Kossatz, Wolfgang Weber, Mohsen Beheshti, Agnieszka Morgenroth and Felix M. Mottaghy
J. Clin. Med. 2020, 9(7), 2130; https://doi.org/10.3390/jcm9072130 - 6 Jul 2020
Cited by 23 | Viewed by 4459
Abstract
The central paradigm of novel therapeutic approaches in cancer therapy is identifying and targeting molecular biomarkers. One such target is the nuclear DNA repair enzyme Poly-(ADP ribose) polymerase 1 (PARP1). Sensitivity to PARP inhibition in certain cancers such as gBRCAmut breast and [...] Read more.
The central paradigm of novel therapeutic approaches in cancer therapy is identifying and targeting molecular biomarkers. One such target is the nuclear DNA repair enzyme Poly-(ADP ribose) polymerase 1 (PARP1). Sensitivity to PARP inhibition in certain cancers such as gBRCAmut breast and ovarian cancers has led to its exploitation as a target. The overexpression of PARP1 in several types of cancer further evoked interest in its use as an imaging target. While PARP1-targeted inhibitors have fast developed and approved in this past decade, determination of PARP1 expression might help to predict the response to PARP inhibitor treatment. This has the potential of improving prognosis and moving towards tailored therapy options and/or dosages. This review summarizes the recent pre-clinical advancements in imaging and theranostic PARP1 targeted tracers. To assess PARP1 levels, several imaging probes with fluorescent or beta/gamma emitting radionuclides have been proposed and three have advanced to ongoing clinical evaluation. Apart from its diagnostic value in detection of primary tumors as well as metastases, this shall also help in delivering therapeutic radionuclides to PARP1 overexpressing tumors. Henceforth nuclear medicine has now advanced towards conjugating theranostic radionuclides to PARP1 inhibitors. This paves the way for a future of PARP1-targeted theranostics and personalized therapy. Full article
(This article belongs to the Special Issue Emerging Technologies for Medical Imaging - Diagnostics, Monitoring and Therapy of Cancers)
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