Multidisciplinary management of patients with liver metastases (LM) requires a precision medicine approach, based on adequate profiling of tumor biology and robust biomarkers. Radiomics, defined as ...the high-throughput identification, analysis, and translational applications of radiological textural features, could fulfill this need. The present review aims to elucidate the contribution of radiomic analyses to the management of patients with LM. We performed a systematic review of the literature through the most relevant databases and web sources. English language original articles published before June 2020 and concerning radiomics of LM extracted from CT, MRI, or PET-CT were considered. Thirty-two papers were identified. Baseline higher entropy and lower homogeneity of LM were associated with better survival and higher chemotherapy response rates. A decrease in entropy and an increase in homogeneity after chemotherapy correlated with radiological tumor response. Entropy and homogeneity were also highly predictive of tumor regression grade. In comparison with RECIST criteria, radiomic features provided an earlier prediction of response to chemotherapy. Lastly, texture analyses could differentiate LM from other liver tumors. The commonest limitations of studies were small sample size, retrospective design, lack of validation datasets, and unavailability of univocal cut-off values of radiomic features. In conclusion, radiomics can potentially contribute to the precision medicine approach to patients with LM, but interdisciplinarity, standardization, and adequate software tools are needed to translate the anticipated potentialities into clinical practice.
Adult-type diffuse gliomas are treated with a multimodality treatment approach that includes radiotherapy both in the primary setting, and in the case of progressive or recurrent disease. Radiation ...necrosis represents a major complication of radiotherapy. Recurrent disease and treatment-related changes are often indistinguishable using conventional imaging methods. The present systematic review aims at assessing the diagnostic role of PET imaging using different radiopharmaceuticals in differentiating radiation necrosis and disease relapse in irradiated adult-type diffuse gliomas. We conducted a comprehensive literature search using the PubMed/MEDLINE and EMBASE databases for original research studies of interest. In total, 436 articles were assessed for eligibility. Ten original papers, published between 2014 and 2022, were selected. Four articles focused on
FFDG, seven on amino acid tracers (
FFET
= 3 and
CMET
= 4), one on
CCHO, and one on
GaGa-PSMA. Visual assessment, semi-quantitative methods, and radiomics were applied for image analysis. Furthermore, 2/10 papers were comparative studies investigating different radiopharmaceuticals. The present review, the first one on the topic in light of the new 2021 CNS WHO classification, highlighted the usefulness of PET imaging in distinguishing radiation necrosis and tumour recurrence, but revealed high heterogeneity among studies.
Purpose
The aim of this study was to evaluate the role of imaging features derived from
18
FFDG-PET/CT to provide in vivo characterization of breast cancer (BC).
Methods
Images from 43 patients with ...a first diagnosis of BC were reviewed. Images were acquired before any treatment. Histological data were derived from pretreatment biopsy or surgical histological specimen; these included tumor type, grade, ER and PgR receptor status, lymphovascular invasion, Ki67 index, HER2 status, and molecular subtype. Standard parameters (SUV
mean
, TLG, MTV) and advanced imaging features (histogram-based and shape and size features) were evaluated. Univariate analysis, hierarchical clustering analysis, and exact Fisher’s test were used for statistical analysis of data. Imaging-derived metrics were reduced evaluating the mutual correlation within group of features as well as the mutual correlation between groups of features to form a signature.
Results
A significant correlation was found between some advanced imaging features and the histological type. Different molecular subtypes were characterized by different values of two histogram-based features (median and energy). A significant association was observed between the imaging signature and luminal A and luminal B HER2 negative molecular subtype and also when considering luminal A, luminal B HER2-negative and HER2-positive groups. Similar results were found between the signature and all five molecular subtypes and also when considering the histological types of BC.
Conclusions
Our results suggest a complementary role of standard PET imaging parameters and advanced imaging features for the in vivo biological characterization of BC lesions.
Anti-PD-1 monoclonal antibodies yield high response rates in patients with relapsed/refractory classic Hodgkin lymphoma (cHL), but most patients will eventually progress. Allogeneic hematopoietic ...cell transplantation (alloHCT) after PD-1 blockade may be associated with increased toxicity, raising challenging questions about the role, timing, and optimal method of transplantation in this setting. To address these questions, we assembled a retrospective cohort of 209 cHL patients who underwent alloHCT after PD-1 blockade. With a median follow-up among survivors of 24 months, the 2-year cumulative incidences (CIs) of non-relapse mortality and relapse were 14 and 18%, respectively; the 2-year graft-versus-host disease (GVHD) and relapse-free survival (GRFS), progression-free survival (PFS), and overall survival were 47%, 69%, and 82%, respectively. The 180-day CI of grade 3-4 acute GVHD was 15%, while the 2-year CI of chronic GVHD was 34%. In multivariable analyses, a longer interval from PD-1 to alloHCT was associated with less frequent severe acute GVHD, while additional treatment between PD-1 and alloHCT was associated with a higher risk of relapse. Notably, post-transplant cyclophosphamide (PTCy)-based GVHD prophylaxis was associated with significant improvements in PFS and GRFS. While awaiting prospective clinical trials, PTCy-based GVHD prophylaxis may be considered the optimal transplantation strategy for this patient population.
Background: Contrast-enhanced mammography (CEM) and contrast-enhanced magnetic resonance imaging (CE-MRI) are commonly used in the screening of breast cancer. The present systematic review aimed to ...summarize, critically analyse, and meta-analyse the available evidence regarding the role of CE-MRI and CEM in the early detection, diagnosis, and preoperative assessment of breast cancer. Methods: The search was performed on PubMed, Google Scholar, and Web of Science on 28 July 2021 using the following terms “breast cancer”, “preoperative staging”, “contrast-enhanced mammography”, “contrast-enhanced spectral mammography”, “contrast enhanced digital mammography”, “contrast-enhanced breast magnetic resonance imaging” “CEM”, “CESM”, “CEDM”, and “CE-MRI”. We selected only those papers comparing the clinical efficacy of CEM and CE-MRI. The study quality was assessed using the QUADAS-2 criteria. The pooled sensitivities and specificity of CEM and CE-MRI were computed using a random-effects model directly from the STATA “metaprop” command. The between-study statistical heterogeneity was tested (I2-statistics). Results: Nineteen studies were selected for this systematic review. Fifteen studies (1315 patients) were included in the metanalysis. Both CEM and CE-MRI detect breast lesions with a high sensitivity, without a significant difference in performance (97% and 96%, respectively). Conclusions: Our findings confirm the potential of CEM as a supplemental screening imaging modality, even for intermediate-risk women, including females with dense breasts and a history of breast cancer.
Cancer is the second cause of death and morbidity in Europe. Unfortunately, currently available treatments cannot permanently cure most cancers, especially when metastatic. New therapy approaches ...are, therefore, urgently needed. Radionuclide therapy deposits cytotoxic radiation by means of energetic particles (alfa, beta, and auger) labeled to a carrier that specifically targets cancer cells. Targeted Alpha Therapy is very promising, because alpha particles deliver high energy (i.e., cytotoxic effect) in a small range, binding a target cell population without significant harm to healthy tissues. The high linear energy transfer typical of alpha particles determines irreversible double-strand DNA breaks with per-unit absorbed doses of acute biologic effects three-to-seven times greater than the damage produced by external beam with photons or beta radiation. As consequence, cells—not equipped to efficiently repair this type of damage—typically undergo death. Therefore, Targeted Alpha Therapy is such a new approach to treat tumors. This article aimed to provide an overview (five “W”s and “How”) on Targeted Alpha Therapy.
Graphical Abstract
Background
The role of image-derived biomarkers in recurrent oligometastatic Prostate Cancer (PCa) is unexplored. This paper aimed to evaluate
18
FFMCH PET/CT radiomic analysis in patients with ...recurrent PCa after primary radical therapy. Specifically, we tested intra-patient lesions similarity in oligometastatic and plurimetastatic PCa, comparing the two most used definitions of oligometastatic disease.
Methods
PCa patients eligible for
18
FFMCH PET/CT presenting biochemical failure after first-line curative treatments were invited to participate in this prospective observational trial. PET/CT images of 92 patients were visually and quantitatively analyzed. Each patient was classified as oligometastatic or plurimetastatic according to the total number of detected lesions (up to 3 and up to 5 or > 3 and > 5, respectively). Univariate and intra-patient lesions' similarity analysis were performed.
Results
18
FFMCH PET/CT identified 370 lesions, anatomically classified as regional lymph nodes and distant metastases. Thirty-eight and 54 patients were designed oligometastatic and plurimetastatic, respectively, using a 3-lesion threshold. The number of oligometastic scaled up to 60 patients (thus 32 plurimetastatic patients) with a 5-lesion threshold. Similarity analysis showed high lesions' heterogeneity. Grouping patients according to the number of metastases, patients with oligometastatic PCa defined with a 5-lesion threshold presented lesions heterogeneity comparable to plurimetastic patients. Lesions within patients having a limited tumor burden as defined by three lesions were characterized by less heterogeneity.
Conclusions
We found a comparable heterogeneity between patients with up to five lesions and plurimetastic patients, while patients with up to three lesions were less heterogeneous than plurimetastatic patients, featuring different cells phenotypes in the two groups. Our results supported the use of a 3-lesion threshold to define oligometastatic PCa.
Artificial intelligence (AI) refers to a field of computer science aimed to perform tasks typically requiring human intelligence. Currently, AI is recognized in the broader technology radar within ...the five key technologies which emerge for their wide-ranging applications and impact in communities, companies, business, and value chain framework alike. However, AI in medical imaging is at an early phase of development, and there are still hurdles to take related to reliability, user confidence, and adoption. The present narrative review aimed to provide an overview on AI-based approaches (distributed learning, statistical learning, computer-aided diagnosis and detection systems, fully automated image analysis tool, natural language processing) in oncological hybrid medical imaging with respect to clinical tasks (detection, contouring and segmentation, prediction of histology and tumor stage, prediction of mutational status and molecular therapies targets, prediction of treatment response, and outcome). Particularly, AI-based approaches have been briefly described according to their purpose and, finally lung cancer—being one of the most extensively malignancy studied by hybrid medical imaging—has been used as illustrative scenario. Finally, we discussed clinical challenges and open issues including ethics, validation strategies, effective data-sharing methods, regulatory hurdles, educational resources, and strategy to facilitate the interaction among different stakeholders. Some of the major changes in medical imaging will come from the application of AI to workflow and protocols, eventually resulting in improved patient management and quality of life. Overall, several time-consuming tasks could be automatized. Machine learning algorithms and neural networks will permit sophisticated analysis resulting not only in major improvements in disease characterization through imaging, but also in the integration of multiple-omics data (i.e., derived from pathology, genomic, proteomics, and demographics) for multi-dimensional disease featuring. Nevertheless, to accelerate the transition of the theory to practice a sustainable development plan considering the multi-dimensional interactions between professionals, technology, industry, markets, policy, culture, and civil society directed by a mindset which will allow talents to thrive is necessary.
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