Contrast Media & Molecular Imaging

Imaging Diagnostic and Pathology in the Management of Oncological-Patients


Status
Published

Lead Editor

1University of Rome “Tor Vergata”, Rome, Italy

2Albert Einstein Medical Center, Philadelphia, USA

3Harvard Medical School, Boston, USA

4Ospedali dei Colli Monaldi, Naples, Italy


Imaging Diagnostic and Pathology in the Management of Oncological-Patients

Description

Personalized medicine is one of the main objectives of both basic and translational cancer research. Nevertheless, it has become clear that the creation of personalized therapeutic protocols requires synergistic, transdisciplinary competencies. Indeed, new approved therapies rarely take into account both the interindividual variability and the aptitude of cancer cells to undergo those genetic and molecular adaptation involved in drug resistance phenomenon. Thus, although promising biomedical discoveries have been made, the setup of “patient-tailored” medical care is still far from becoming reality. Indeed, only rarely molecules that overcome preclinical trial steps are truly translatable to the clinical side for diagnostic or therapeutical purposes. The discrepancy between experimental data and the possible use in both diagnosis and therapy of new anticancer molecules is due to several causes: biological differences between human diseases and animal models, inconsistence of experimental plans, and/or wrong interpretation of the results. On note, in several proclinical studies no validation of data is performed by pathologists with long-term experience in cancer animal models.

Given these considerations, the realization of “patient-tailored” therapeutic anticancer protocols requires the synergic combination among expertise of several disciplines such as nuclear medicine and anatomic pathology seems evident. They constitute two fundamental approaches for the establishment of the diagnosis, the clinical monitoring, the evaluation of patients’ prognosis, and their response to therapy.

The main focus of this special issue will be on the precious contribution offered by a close alliance between imaging diagnostic (both nuclear medicine and radiology) and anatomic pathology to the scientific community. Indeed, the construction of a structured collaboration model between these disciplines can speed up the achievement of a medicine that takes into account the uniqueness of the human being.

We particularly take an interest in manuscripts reporting new data/hypothesis in the field of oncological research that are supported by the integration among radiological, molecular imaging and histopathological analysis.

Potential topics include but are not limited to the following:

  • Management of oncological patients in the digital era: from imaging diagnostic to digital pathology
  • Early prognostic/predictive markers of oncological diseases
  • New molecular prognostic/predictive factors for bone metastasis
  • Radiological, histological, chemical, and molecular analysis of breast microcalcifications: diagnostic and biological value
  • Choline and PSMA PET/CT in prostate cancer patients. In vivo and ex vivo investigations.
  • In vivo and ex vivo imaging of tumor-infiltrating immune cells
  • Circulating tumor markers (i.e., DNA and cancer cells)
  • Artificial intelligence techniques in digital image processing
  • New methods to match radiological, MRI, PET, and SPECT images to histological slides
  • Animal models and development of new oncological biomarkers

Articles

  • Special Issue
  • - Volume 2019
  • - Article ID 2513680
  • - Editorial

Imaging Diagnostic and Pathology in the Management of Oncological-Patients

Elena Bonanno | Nicola Toschi | ... | Orazio Schillaci
  • Special Issue
  • - Volume 2019
  • - Article ID 5982834
  • - Research Article

An Ad Hoc Random Initialization Deep Neural Network Architecture for Discriminating Malignant Breast Cancer Lesions in Mammographic Images

Andrea Duggento | Marco Aiello | ... | Nicola Toschi
  • Special Issue
  • - Volume 2019
  • - Article ID 5081909
  • - Research Article

Associations between Histogram Analysis Parameters Derived from DCE-MRI and Histopathological Features including Expression of EGFR, p16, VEGF, Hif1-alpha, and p53 in HNSCC

Hans Jonas Meyer | Leonard Leifels | ... | Alexey Surov
  • Special Issue
  • - Volume 2018
  • - Article ID 2136840
  • - Research Article

Spectral Photon-Counting Molecular Imaging for Quantification of Monoclonal Antibody-Conjugated Gold Nanoparticles Targeted to Lymphoma and Breast Cancer: An In Vitro Study

Mahdieh Moghiseh | Chiara Lowe | ... | Aamir Raja
  • Special Issue
  • - Volume 2018
  • - Article ID 9840962
  • - Research Article

Prostate Osteoblast-Like Cells: A Reliable Prognostic Marker of Bone Metastasis in Prostate Cancer Patients

Manuel Scimeca | Nicoletta Urbano | ... | Elena Bonanno
  • Special Issue
  • - Volume 2018
  • - Article ID 8494031
  • - Research Article

Nuclear Imaging Study of the Pharmacodynamic Effects of Debio 1143, an Antagonist of Multiple Inhibitor of Apoptosis Proteins (IAPs), in a Triple-Negative Breast Cancer Model

Pierre-Simon Bellaye | Alexandra Oudot | ... | Bertrand Collin
  • Special Issue
  • - Volume 2018
  • - Article ID 5247153
  • - Research Article

177Lu-DOTA-HYNIC-Lys(Nal)-Urea-Glu: Biokinetics, Dosimetry, and Evaluation in Patients with Advanced Prostate Cancer

Clara Santos-Cuevas | Guillermina Ferro-Flores | ... | Irma Soldevilla-Gallardo
  • Special Issue
  • - Volume 2018
  • - Article ID 5693058
  • - Research Article

Towards More Structure: Comparing TNM Staging Completeness and Processing Time of Text-Based Reports versus Fully Segmented and Annotated PET/CT Data of Non-Small-Cell Lung Cancer

Raphael Sexauer | Thomas Weikert | ... | Alexander W. Sauter
  • Special Issue
  • - Volume 2018
  • - Article ID 3417190
  • - Research Article

Is SUVmax Helpful in the Differential Diagnosis of Enlarged Mediastinal Lymph Nodes? A Pilot Study

Congcong Yu | Xiaotian Xia | ... | Xiaoli Lan
  • Special Issue
  • - Volume 2018
  • - Article ID 5308517
  • - Research Article

Automated Detection and Segmentation of Nonmass-Enhancing Breast Tumors with Dynamic Contrast-Enhanced Magnetic Resonance Imaging

Ignacio Alvarez Illan | Javier Ramirez | ... | Anke Meyer-Baese
Contrast Media & Molecular Imaging
 Journal metrics
Acceptance rate45%
Submission to final decision80 days
Acceptance to publication58 days
CiteScore2.440
Impact Factor1.984
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