Is oropharyngoesophageal scintigraphy the method of choice for assessing dysphagia in systemic sclerosis? A single center experience.

OBJECTIVES: To evaluate the performance of oropharyngoesophageal scintigraphy (OPES) in the assessment of dysphagia in patients with systemic sclerosis (SSc), and to compare OPES results with those of barium esophagogram. METHODS: Adult SSc patients who underwent OPES for the assessment of dysphagia were enrolled. OPES was performed with both liquid and semisolid boluses and provided information regarding oropharyngeal transit time, esophageal transit time (ETT), oropharyngeal retention index (OPRI), esophageal retention index (ERI), and site of bolus retention. Barium esophagogram results were also collected. RESULTS: Fifty-seven SSc patients (87.7% female, mean age 57.7 years) with dysphagia were enrolled. OPES identified at least one alteration in each patient and findings were generally worse for the semisolid bolus. Esophageal motility was widely impaired with 89.5% of patients with an increased semisolid ERI, and middle-lower esophagus was the most frequent site of bolus retention. However, oropharyngeal impairment was highlighted by widespread increased OPRI, especially in anti-topoisomerase I positivity. Older patients and with longer disease duration presented slower semisolid ETT (p = 0.029 and p = 0.002, respectively). Eleven patients with dysphagia had a negative barium esophagogram: all of them presented some alterations in OPES parameters. CONCLUSION: OPES revealed a marked SSc esophageal impairment, in terms of both slowed transit time and increased bolus retention, but also shed light on oropharyngeal swallowing alterations. OPES showed high sensitivity, being able to detect swallowing alterations in dysphagic patients with negative barium esophagogram. Therefore, the use of OPES for the assessment of SSc-related dysphagia in clinical practice should be promoted.

[18F]Fluorocholine PET/CT-guided stereotactic body radiotherapy in patients with recurrent oligometastatic prostate cancer.

BACKGROUND: In the last years, functional imaging has given a significant contribution to the clinical decision-making of biochemically relapsed prostate cancer (PCa). Hereby, we present a prospective study aiming to validate the role of [18F]Fluoro-Methyl Choline ([18F]FMCH) PET/CT in the selection of PCa patients suitable for stereotactic body radiotherapy (SBRT). METHODS: Patients with biochemical recurrence limited up to three lesions revealed by [18F]FMCH PET/CT were enrolled in the present study and treated with SBRT on all active lesions. Systemic therapy-free survival since the [18F]FMCH PET/CT was considered as the primary endpoint. RESULTS: Forty-six patients were evaluated, and a total of 67 lesions were treated. After a median follow-up of 28.9 months, systemic therapy was started in 30 patients (65.2%) and median systemic therapy-free survival was 39.1 months (95% CI 6.5-68.6); 6, 12, and 24-month ratios were 93.5%, 73.9%, and 63.1%, respectively. At univariate Cox regression analysis, Delta PSA demonstrated an impact on systemic therapy-free survival (p < 0.001). CONCLUSIONS: Based on our findings, [18F]FMCH PET/CT can identify oligometastatic prostate cancer patients suitable for SBRT, resulting in a systemic therapy-free survival of 39.1 months.

Advancing Pediatric Sarcomas through Radiomics: A Systematic Review and Prospective Assessment Using Radiomics Quality Score (RQS) and Methodological Radiomics Score (METRICS).

Pediatric sarcomas, rare malignancies of mesenchymal origin, pose diagnostic and therapeutic challenges. In this review, we explore the role of radiomics in reshaping our understanding of pediatric sarcomas, emphasizing methodological considerations and applications such as diagnostics and predictive modeling. A systematic review conducted up to November 2023 identified 72 papers on radiomics analysis in pediatric sarcoma from PubMed/MEDLINE, Web of Knowledge, and Scopus. Following inclusion and exclusion criteria, 10 reports were included in this review. The studies, predominantly retrospective, focus on Ewing sarcoma and osteosarcoma, utilizing diverse imaging modalities, including CT, MRI, PET/CT, and PET/MRI. Manual segmentation is common, with a median of 35 features extracted. Radiomics Quality Score (RQS) and Methodological Radiomics Score (METRICS) assessments reveal a consistent emphasis on non-radiomic features, validation criteria, and improved methodological rigor in recent publications. Diagnostic applications dominate, with innovative studies exploring prognostic and treatment response aspects. Challenges include feature heterogeneity and sample size variations. The evolving landscape underscores the need for standardized methodologies. Despite challenges, the diagnostic and predictive potential of radiomics in pediatric oncology is evident, paving the way for precision medicine advancements.

Sentinel Lymph Node Mapping in Lung Cancer: A Pilot Study for the Detection of Micrometastases in Stage I Non-Small Cell Lung Cancer.

Lymphadenectomy represents a fundamental step in the staging and treatment of non-small cell lung cancer (NSCLC). To date, the extension of lymphadenectomy in early-stage NSCLC is a debated topic due to its possible complications. The detection of sentinel lymph nodes (SLNs) is a strategy that can improve the selection of patients in which a more extended lymphadenectomy is necessary. This pilot study aimed to refine lymph nodal staging in early-stage NSCLC patients who underwent robotic lung resection through the application of innovative intraoperative sentinel lymph node (SLN) identification and the pathological evaluation using one-step nucleic acid amplification (OSNA). Clinical N0 NSCLC patients planning to undergo robotic lung resection were selected. The day before surgery, all patients underwent radionuclide computed tomography (CT)-guided marking of the primary lung lesion and subsequently Single Photon Emission Computed Tomography (SPECT) to identify tracer migration and, consequently, the area with higher radioactivity. On the day of surgery, the lymph nodal radioactivity was detected intraoperatively using a gamma camera. SLN was defined as the lymph node with the highest numerical value of radioactivity. The OSNA amplification, detecting the mRNA of CK19, was used for the detection of nodal metastases in the lymph nodes, including SLN. From March to July 2021, a total of 8 patients (3 female; 5 male), with a mean age of 66 years (range 48-77), were enrolled in the study. No complications relating to the CT-guided marking or preoperative SPECT were found. An average of 5.3 lymph nodal stations were examined (range 2-8). N2 positivity was found in 3 out of 8 patients (37.5%). Consequently, pathological examination of lymph nodes with OSNA resulted in three upstages from the clinical IB stage to pathological IIIA stage. Moreover, in 1 patient (18%) with nodal upstaging, a positive node was intraoperatively identified as SLN. Comparing this protocol to the usual practice, no difference was found in terms of the operating time, conversion rate, and complication rate. Our preliminary experience suggests that sentinel lymph node detection, in association with the accurate pathological staging of cN0 patients achieved using OSNA, is safe and effective in the identification of metastasis, which is usually undetected by standard diagnostic methods.

Radiomics-Based Inter-Lesion Relation Network to Describe [18F]FMCH PET/CT Imaging Phenotypes in Prostate Cancer.

Advanced image analysis, including radiomics, has recently acquired recognition as a source of biomarkers, although there are some technical and methodological challenges to face for its application in the clinic. Among others, proper phenotyping of metastatic or systemic disease where multiple lesions coexist is an issue, since each lesion contributes to characterization of the disease. Therefore, the radiomic profile of each lesion should be modeled into a more complex architecture able to reproduce each "unit" (lesion) as a part of the "entire" (patient). This work aimed to characterize intra-tumor heterogeneity underpinning metastatic prostate cancer using an exhaustive innovative approach which consist of a i) feature transformation method to build an agnostic (i.e., irrespective of pre-existence knowledge, experience, and expertise) radiomic profile of lesions extracted from [18F]FMCH PET/CT, ii) qualitative assessment of intra-tumor heterogeneity of patients, iii) quantitative representation of the intra-tumor heterogeneity of patients in terms of the relationship between their lesions' profiles, to be associated with prognostic factors. We confirmed that metastatic prostate cancer patients encompassed lesions with different radiomic profiles that exhibited intra-tumor radiomic heterogeneity and that the presence of many radiomic profiles within the same patient impacted the outcome.

Tumor Progression from a Fibroblast Activation Protein Perspective: Novel Diagnostic and Therapeutic Scenarios for Colorectal Cancer.

In 2020, the Global Cancer Observatory estimated the incidence of colorectal cancer (CRC) at around 10.7% coupled with a mortality rate of 9.5%. The explanation for these values lies in the tumor microenvironment consisting of the extracellular matrix and cancer-associated fibroblasts (CAFs). Fibroblast activation protein (FAP) offers a promising target for cancer therapy since its functions contribute to tumor progression. Immunohistochemistry examination of FAP, fibronectin ED-B, and CXCR4 in primary tumors and their respective synchronous and/or metachronous metastases along with semiquantitative analysis have been carried out on histological samples of 50 patients diagnosed with metastatic CRC. The intensity of FAP, articulated by both "Intensity %" and "Intensity score", is lower in the first metastasis compared to the primary tumor with a statistically significant correlation. No significant correlations have been observed regarding fibronectin ED-B and CXCR4. Tumors that produce FAP have an ambivalent relationship with this protein. At first, they exploit FAP, but later they reduce its expressiveness. Although our study has not directly included FAP-Inhibitor (FAPI) PET/CT, the considerable expression of FAP reveals its potential as a diagnostic and therapeutic tool worthy of further investigation. This dynamic relationship between cancer and FAP has substantial diagnostic and therapeutic implications.

[18F]FMCH PET/CT biomarkers and similarity analysis to refine the definition of oligometastatic prostate cancer.

BACKGROUND: The role of image-derived biomarkers in recurrent oligometastatic Prostate Cancer (PCa) is unexplored. This paper aimed to evaluate [18F]FMCH 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 [18F]FMCH 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: [18F]FMCH 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 and hybrid imaging: the best match for personalized medicine in oncology.

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.