-
Journal of Nuclear Medicine : Official... Apr 2020Radiomics is a rapidly evolving field of research concerned with the extraction of quantitative metrics-the so-called radiomic features-within medical images. Radiomic... (Review)
Review
Radiomics is a rapidly evolving field of research concerned with the extraction of quantitative metrics-the so-called radiomic features-within medical images. Radiomic features capture tissue and lesion characteristics such as heterogeneity and shape and may, alone or in combination with demographic, histologic, genomic, or proteomic data, be used for clinical problem solving. The goal of this continuing education article is to provide an introduction to the field, covering the basic radiomics workflow: feature calculation and selection, dimensionality reduction, and data processing. Potential clinical applications in nuclear medicine that include PET radiomics-based prediction of treatment response and survival will be discussed. Current limitations of radiomics, such as sensitivity to acquisition parameter variations, and common pitfalls will also be covered.
Topics: Humans; Image Processing, Computer-Assisted; Nuclear Medicine
PubMed: 32060219
DOI: 10.2967/jnumed.118.222893 -
Turkish Journal of Medical Sciences Aug 2018Takayasu arteritis (TAK) is a challenging chronic, granulomatous, large-vessel systemic vasculitis, mostly due to difficulties in early diagnosis and assessing actual... (Review)
Review
Takayasu arteritis (TAK) is a challenging chronic, granulomatous, large-vessel systemic vasculitis, mostly due to difficulties in early diagnosis and assessing actual disease activity. Since there are no specific diagnostic laboratory tests, biomarkers, or autoantibodies, many patients experience considerable delay in diagnosis. Remembering the possibility of TAK together with the use of acute phase responses and appropriate imaging studies may be helpful for early diagnosis. Since there may be discrepancies between systemic and vascular wall inflammation, using only acute phase responses is not reliable in assessing current disease activity. Therefore, physical examination and new imaging findings should also be used to assess current disease activity. Despite its limitations, the Indian Takayasu Clinical Activity Score (ITAS2010) may also be helpful for this purpose. The rationale of medical treatment is to suppress both vascular and systemic inflammation with appropriate systemic immunosuppression, including corticosteroids and conventional immunosuppressive agents. In cases of refractory disease activity, leflunomide and biologic agents such as TNF inhibitors and tocilizumab may be tried. In selected cases with persistent lesions that cannot be reversed with medical treatment, endovascular interventions including balloon angioplasty, stent and stent graft replacement, or surgery may be tried. However, such procedures should be performed after suppression of inflammation, i.e. during inactive disease. Prognosis of TAK is probably getting better with lower mortality rates reported in recent years, probably due to the use of more effective medical treatments as well as the use of endovascular interventions when necessary and available.
Topics: Antibodies, Monoclonal, Humanized; Biomarkers; Endovascular Procedures; Guidelines as Topic; Humans; Immunosuppressive Agents; Leflunomide; Physical Examination; Prognosis; Radiology, Interventional; Takayasu Arteritis
PubMed: 30114347
DOI: 10.3906/sag-1804-136 -
Strahlentherapie Und Onkologie : Organ... Oct 2020Magnetic resonance imaging (MRI) and amino acid positron-emission tomography (PET) of the brain contain a vast amount of structural and functional information that can... (Review)
Review
BACKGROUND
Magnetic resonance imaging (MRI) and amino acid positron-emission tomography (PET) of the brain contain a vast amount of structural and functional information that can be analyzed by machine learning algorithms and radiomics for the use of radiotherapy in patients with malignant brain tumors.
METHODS
This study is based on comprehensive literature research on machine learning and radiomics analyses in neuroimaging and their potential application for radiotherapy in patients with malignant glioma or brain metastases.
RESULTS
Feature-based radiomics and deep learning-based machine learning methods can be used to improve brain tumor diagnostics and automate various steps of radiotherapy planning. In glioma patients, important applications are the determination of WHO grade and molecular markers for integrated diagnosis in patients not eligible for biopsy or resection, automatic image segmentation for target volume planning, prediction of the location of tumor recurrence, and differentiation of pseudoprogression from actual tumor progression. In patients with brain metastases, radiomics is applied for additional detection of smaller brain metastases, accurate segmentation of multiple larger metastases, prediction of local response after radiosurgery, and differentiation of radiation injury from local brain metastasis relapse. Importantly, high diagnostic accuracies of 80-90% can be achieved by most approaches, despite a large variety in terms of applied imaging techniques and computational methods.
CONCLUSION
Clinical application of automated image analyses based on radiomics and artificial intelligence has a great potential for improving radiotherapy in patients with malignant brain tumors. However, a common problem associated with these techniques is the large variability and the lack of standardization of the methods applied.
Topics: Brain Neoplasms; Computational Biology; DNA Methylation; DNA Modification Methylases; DNA Repair Enzymes; Deep Learning; Diagnosis, Differential; Glioblastoma; Glioma; Humans; Image Processing, Computer-Assisted; Imaging Genomics; Isocitrate Dehydrogenase; Magnetic Resonance Imaging; Neoplasm Grading; Neoplasm Proteins; Neoplasm Recurrence, Local; Neuroimaging; Positron-Emission Tomography; Progression-Free Survival; Promoter Regions, Genetic; Radiation Oncology; Radiosurgery; Radiotherapy Planning, Computer-Assisted; Sensitivity and Specificity; Tumor Suppressor Proteins
PubMed: 32394100
DOI: 10.1007/s00066-020-01626-8 -
Abdominal Radiology (New York) Sep 2023The Society of Abdominal Radiology's Colorectal and Anal Cancer Disease-Focused Panel (DFP) first published a rectal cancer lexicon paper in 2019. Since that time, the... (Review)
Review
The Society of Abdominal Radiology's Colorectal and Anal Cancer Disease-Focused Panel (DFP) first published a rectal cancer lexicon paper in 2019. Since that time, the DFP has published revised initial staging and restaging reporting templates, and a new SAR user guide to accompany the rectal MRI synoptic report (primary staging). This lexicon update summarizes interval developments, while conforming to the original lexicon 2019 format. Emphasis is placed on primary staging, treatment response, anatomic terminology, nodal staging, and the utility of specific sequences in the MRI protocol. A discussion of primary tumor staging reviews updates on tumor morphology and its clinical significance, T1 and T3 subclassifications and their clinical implications, T4a and T4b imaging findings/definitions, terminology updates on the use of MRF over CRM, and the conundrum of the external sphincter. A parallel section on treatment response reviews the clinical significance of near-complete response and introduces the lexicon of "regrowth" versus "recurrence". A review of relevant anatomy incorporates updated definitions and expert consensus of anatomic landmarks, including the NCCN's new definition of rectal upper margin and sigmoid take-off. A detailed review of nodal staging is also included, with attention to tumor location relative to the dentate line and locoregional lymph node designation, a new suggested size threshold for lateral lymph nodes and their indications for use, and imaging criteria used to differentiate tumor deposits from lymph nodes. Finally, new treatment terminologies such as organ preservation, TNT, TAMIS and watch-and-wait management are introduced. This 2023 version aims to serve as a concise set of up-to-date recommendations for radiologists, and discusses terminology, classification systems, MRI and clinical staging, and the evolving concepts in diagnosis and treatment of rectal cancer.
Topics: Humans; Rectal Neoplasms; Anus Neoplasms; Rectum; Neoplasm Staging; Magnetic Resonance Imaging; Radiology
PubMed: 37145311
DOI: 10.1007/s00261-023-03893-2 -
Nature Cancer Oct 2022Immunotherapy is used to treat almost all patients with advanced non-small cell lung cancer (NSCLC); however, identifying robust predictive biomarkers remains...
Immunotherapy is used to treat almost all patients with advanced non-small cell lung cancer (NSCLC); however, identifying robust predictive biomarkers remains challenging. Here we show the predictive capacity of integrating medical imaging, histopathologic and genomic features to predict immunotherapy response using a cohort of 247 patients with advanced NSCLC with multimodal baseline data obtained during diagnostic clinical workup, including computed tomography scan images, digitized programmed death ligand-1 immunohistochemistry slides and known outcomes to immunotherapy. Using domain expert annotations, we developed a computational workflow to extract patient-level features and used a machine-learning approach to integrate multimodal features into a risk prediction model. Our multimodal model (area under the curve (AUC) = 0.80, 95% confidence interval (CI) 0.74-0.86) outperformed unimodal measures, including tumor mutational burden (AUC = 0.61, 95% CI 0.52-0.70) and programmed death ligand-1 immunohistochemistry score (AUC = 0.73, 95% CI 0.65-0.81). Our study therefore provides a quantitative rationale for using multimodal features to improve prediction of immunotherapy response in patients with NSCLC using expert-guided machine learning.
Topics: Humans; Carcinoma, Non-Small-Cell Lung; Lung Neoplasms; Programmed Cell Death 1 Receptor; Radiology; Genomics
PubMed: 36038778
DOI: 10.1038/s43018-022-00416-8 -
Journal of Clinical Oncology : Official... Sep 2023The molecular classification of endometrial cancer (EC) has proven to have prognostic value and is predictive of response to adjuvant chemotherapy. Here, we investigate...
PURPOSE
The molecular classification of endometrial cancer (EC) has proven to have prognostic value and is predictive of response to adjuvant chemotherapy. Here, we investigate its predictive value for response to external beam radiotherapy (EBRT) and vaginal brachytherapy (VBT) in early-stage endometrioid EC (EEC).
METHODS
Data of the randomized PORTEC-1 trial (n = 714) comparing pelvic EBRT with no adjuvant therapy in early-stage intermediate-risk EC and the PORTEC-2 trial (n = 427) comparing VBT with EBRT in early-stage high-intermediate-risk EC were used. Locoregional (including vaginal and pelvic) recurrence-free survival was compared between treatment groups across the four molecular classes using Kaplan-Meier's methodology and log-rank tests.
RESULTS
A total of 880 molecularly classified ECs, 484 from PORTEC-1 and 396 from PORTEC-2, were included. The majority were FIGO-2009 stage I EEC (97.2%). The median follow-up was 11.3 years. No locoregional recurrences were observed in EC with a pathogenic mutation of DNA polymerase-ε (mut EC). In mismatch repair-deficient (MMRd) EC, locoregional recurrence-free survival was similar after EBRT (94.2%), VBT (94.2%), and no adjuvant therapy (90.3%; = .74). In EC with a p53 abnormality (p53abn EC), EBRT (96.9%) had a substantial benefit over VBT (64.3%) and no adjuvant therapy (72.2%; = .048). In EC with no specific molecular profile (NSMP EC), both EBRT (98.3%) and VBT (96.2%) yielded better locoregional control than no adjuvant therapy (87.7%; < .0001).
CONCLUSION
The molecular classification of EC predicts response to radiotherapy in stage I EEC and may guide adjuvant treatment decisions. Omitting radiotherapy seems to be safe in mut EC. The benefit of radiotherapy seems to be limited in MMRd EC. EBRT yields a significantly better locoregional recurrence-free survival than VBT or no adjuvant therapy in p53abn EC. VBT is the treatment of choice for NSMP EC as it is as effective as EBRT and significantly better than no adjuvant therapy for locoregional tumor control.
Topics: Female; Humans; Radiation Oncology; Endometrial Neoplasms; Brachytherapy; Combined Modality Therapy
PubMed: 37487144
DOI: 10.1200/JCO.23.00062 -
Journal of Applied Clinical Medical... Dec 2022This section focuses on the professional workforce comprised of the primary medical specialties that utilize ionizing radiation in their practices. Those discussed... (Review)
Review
This section focuses on the professional workforce comprised of the primary medical specialties that utilize ionizing radiation in their practices. Those discussed include the specialties of radiology and radiation oncology, as well as the subspecialties of radiology, namely diagnostic radiology, interventional radiology, nuclear radiology, and nuclear medicine. These professionals provide essential health care services, for example, the interpretation of imaging studies, the provision of interventional procedures, radionuclide therapeutic treatments, and radiation therapy. In addition, they may be called on to function as part of a radiologic emergency response team to care for potentially exposed persons following radiation events, for example, detonation of a nuclear weapon, nuclear power plant accidents, and transportation incidents. For these reasons, maintenance of an adequate workforce in each of these professions is essential to meeting the nation's future needs. Currently, there is a shortage for all physicians in the medical radiology workforce.
Topics: Humans; United States; Medicine; Nuclear Medicine; Diagnostic Imaging; Radiology, Interventional; Workforce
PubMed: 36382354
DOI: 10.1002/acm2.13799 -
The Lancet. Haematology May 2023Given the paucity of high-certainty evidence, and differences in opinion on the use of nuclear medicine for hematological malignancies, we embarked on a consensus... (Review)
Review
Given the paucity of high-certainty evidence, and differences in opinion on the use of nuclear medicine for hematological malignancies, we embarked on a consensus process involving key experts in this area. We aimed to assess consensus within a panel of experts on issues related to patient eligibility, imaging techniques, staging and response assessment, follow-up, and treatment decision-making, and to provide interim guidance by our expert consensus. We used a three-stage consensus process. First, we systematically reviewed and appraised the quality of existing evidence. Second, we generated a list of 153 statements based on the literature review to be agreed or disagreed with, with an additional statement added after the first round. Third, the 154 statements were scored by a panel of 26 experts purposively sampled from authors of published research on haematological tumours on a 1 (strongly disagree) to 9 (strongly agree) Likert scale in a two-round electronic Delphi review. The RAND and University of California Los Angeles appropriateness method was used for analysis. Between one and 14 systematic reviews were identified on each topic. All were rated as low to moderate quality. After two rounds of voting, there was consensus on 139 (90%) of 154 of the statements. There was consensus on most statements concerning the use of PET in non-Hodgkin and Hodgkin lymphoma. In multiple myeloma, more studies are required to define the optimal sequence for treatment assessment. Furthermore, nuclear medicine physicians and haematologists are awaiting consistent literature to introduce volumetric parameters, artificial intelligence, machine learning, and radiomics into routine practice.
Topics: Humans; Consensus; Nuclear Medicine; Artificial Intelligence; Hematologic Neoplasms; Molecular Imaging
PubMed: 37142345
DOI: 10.1016/S2352-3026(23)00030-3 -
International Journal of Radiation... Oct 2020The speed at which the COVID-19 pandemic spread across the globe and the accompanying need to rapidly disseminate knowledge have highlighted the inadequacies of the...
The speed at which the COVID-19 pandemic spread across the globe and the accompanying need to rapidly disseminate knowledge have highlighted the inadequacies of the traditional research/publication cycle, particularly the slowness and the fragmentary access globally to manuscripts and their findings. Scholarly communication has slowly been undergoing transformational changes since the introduction of the Internet in the 1990s. The pandemic response has created an urgency that has accelerated these trends in some areas. The magnitude of the global emergency has strongly bolstered calls to make the entire research and publishing lifecycle transparent and open. The global scientific community has collaborated in rapid, open, and transparent means that are unprecedented. The general public has been reminded of the important of science, and trusted communication of scientific findings, in everyday life. In addition to COVID-19-driven innovation in scholarly communication, alternative bibliometrics and artificial intelligence tools will further transform academic publishing in the near future.
Topics: Betacoronavirus; COVID-19; Coronavirus Infections; Humans; Information Dissemination; Pandemics; Pneumonia, Viral; Radiation Oncology; SARS-CoV-2; Scholarly Communication
PubMed: 32890542
DOI: 10.1016/j.ijrobp.2020.06.048 -
Radiotherapy and Oncology : Journal of... May 2020Quantitative imaging biomarkers show great potential for use in radiotherapy. Quantitative images based on microscopic tissue properties and tissue function can be used... (Review)
Review
Quantitative imaging biomarkers show great potential for use in radiotherapy. Quantitative images based on microscopic tissue properties and tissue function can be used to improve contouring of the radiotherapy targets. Furthermore, quantitative imaging biomarkers might be used to predict treatment response for several treatment regimens and hence be used as a tool for treatment stratification, either to determine which treatment modality is most promising or to determine patient-specific radiation dose. Finally, patient-specific radiation doses can be further tailored to a tissue/voxel specific radiation dose when quantitative imaging is used for dose painting. In this review, published standards, guidelines and recommendations on quantitative imaging assessment using CT, PET and MRI are discussed. Furthermore, critical issues regarding the use of quantitative imaging for radiation oncology purposes and resultant pending research topics are identified.
Topics: Humans; Magnetic Resonance Imaging; Positron-Emission Tomography; Radiation Oncology; Radiotherapy Planning, Computer-Assisted
PubMed: 32114268
DOI: 10.1016/j.radonc.2020.01.026