PET radiomics in lung cancer: advances and translational challenges.

Radiomics is an emerging field of medical imaging that aims at improving the accuracy of diagnosis, prognosis, treatment planning and monitoring non-invasively through the automated or semi-automated quantitative analysis of high-dimensional image features. Specifically in the field of nuclear medicine, radiomics utilizes imaging methods such as positron emission tomography (PET) and single photon emission computed tomography (SPECT) to evaluate biomarkers related to metabolism, blood flow, cellular activity and some biological pathways. Lung cancer ranks among the leading causes of cancer-related deaths globally, and radiomics analysis has shown great potential in guiding individualized therapy, assessing treatment response, and predicting clinical outcomes. In this review, we summarize the current state-of-the-art radiomics progress in lung cancer, highlighting the potential benefits and existing limitations of this approach. The radiomics workflow was introduced first including image acquisition, segmentation, feature extraction, and model building. Then the published literatures were described about radiomics-based prediction models for lung cancer diagnosis, differentiation, prognosis and efficacy evaluation. Finally, we discuss current challenges and provide insights into future directions and potential opportunities for integrating radiomics into routine clinical practice.

Accelerating histopathology workflows with generative AI-based virtually multiplexed tumour profiling.

Understanding the spatial heterogeneity of tumours and its links to disease initiation and progression is a cornerstone of cancer biology. Presently, histopathology workflows heavily rely on hematoxylin and eosin and serial immunohistochemistry staining, a cumbersome, tissue-exhaustive process that results in non-aligned tissue images. We propose the VirtualMultiplexer, a generative artificial intelligence toolkit that effectively synthesizes multiplexed immunohistochemistry images for several antibody markers (namely AR, NKX3.1, CD44, CD146, p53 and ERG) from only an input hematoxylin and eosin image. The VirtualMultiplexer captures biologically relevant staining patterns across tissue scales without requiring consecutive tissue sections, image registration or extensive expert annotations. Thorough qualitative and quantitative assessment indicates that the VirtualMultiplexer achieves rapid, robust and precise generation of virtually multiplexed imaging datasets of high staining quality that are indistinguishable from the real ones. The VirtualMultiplexer is successfully transferred across tissue scales and patient cohorts with no need for model fine-tuning. Crucially, the virtually multiplexed images enabled training a graph transformer that simultaneously learns from the joint spatial distribution of several proteins to predict clinically relevant endpoints. We observe that this multiplexed learning scheme was able to greatly improve clinical prediction, as corroborated across several downstream tasks, independent patient cohorts and cancer types. Our results showcase the clinical relevance of artificial intelligence-assisted multiplexed tumour imaging, accelerating histopathology workflows and cancer biology.

Tumor Heterogeneity in Gastrointestinal Cancer Based on Multimodal Data Analysis.

BACKGROUND: Gastrointestinal cancer cells display both morphology and physiology diversity, thus posing a significant challenge for precise representation by a single data model. We conducted an in-depth study of gastrointestinal cancer heterogeneity by integrating and analyzing data from multiple modalities. METHODS: We used a modified Canny algorithm to identify edges from tumor images, capturing intricate nonlinear interactions between pixels. These edge features were then combined with differentially expressed mRNA, miRNA, and immune cell data. Before data integration, we used the K-medoids algorithm to pre-cluster individual data types. The results of pre-clustering were used to construct the kernel matrix. Finally, we applied spectral clustering to the fusion matrix to identify different tumor subtypes. Furthermore, we identified hub genes linked to these subtypes and their biological roles through the application of Weighted Gene Co-expression Network Analysis (WGCNA) and Gene Ontology (GO) enrichment analysis. RESULTS: Our investigation categorized patients into three distinct tumor subtypes and pinpointed hub genes associated with each. Genes MAGI2-AS3, MALAT1, and SPARC were identified as having a differential impact on the metastatic and invasive capabilities of cancer cells. CONCLUSION: By harnessing multimodal features, our study enhances the understanding of gastrointestinal tumor heterogeneity and identifies biomarkers for personalized medicine and targeted treatments.

Development and preclinical characterization of a novel radiotheranostic EphA2-targeting bicyclic peptide.

Erythropoietin-producing hepatocellular receptor A2 (EphA2), is a receptor tyrosine kinase involved in cell-cell interactions. It is known to be overexpressed in various tumors and is associated with poor prognosis. EphA2 has been proposed as a target for theranostic applications. Low molecular weight peptide-based scaffolds with low nanomolar affinities have been shown to be ideal in such applications. Bicyclic peptides have emerged as an alternative to traditional peptides for this purpose, offering affinities comparable to antibodies due to their constrained nature, along with high tissue penetration, and improved stability compared to linear counterparts. This study presents the development and comprehensive in vitro and in vivo preclinical evaluation of BCY18469, a novel EphA2-targeting bicyclic peptide-based radiotheranostic agent. Methods: The EphA2-targeting Bicycle® peptide BCY18469 was identified through phage-display and chemically optimized. BCY18469 was radiolabeled with 68Ga, 177Lu and 111In. The physicochemical properties, binding affinity and internalization as well as specificity of the peptide were evaluated in vitro. In vivo PET/MR and SPECT/CT imaging studies were performed using [68Ga]Ga-BCY18469 and [111In]In-BCY18469, respectively, along with biodistribution of [177Lu]Lu-BCY18469 up to 24 h post injection in HT1080- and PC-3-tumor bearing BALB/c nu/nu EphA2-overexpressing xenograft mouse models. Results: The EphA2-targeting bicyclic peptide BCY18469 showed high binding affinity toward human and mouse EphA2 (1.9 and 3.8 nM, respectively). BCY18469 specifically bound and internalized into EphA2-expressing HT1080 cells. Imaging studies showed high tumor enrichment at early time-points (SUV of 1.7 g/mL at 1 h p.i. and 1.2 g/mL at 2 h p.i. in PET/MRI, HT1080 xenograft) with tumor contrast as early as 5 min p.i. and kidney-mediated clearance. Biodistribution studies revealed high early tumor uptake (19.5 ± 3.5 %ID/g at 1 h p.i., HT1080 xenograft) with SPECT/CT imaging further confirming these findings (5.7 ± 1.5 %ID/g at 1 h p.i., PC-3 xenograft). Conclusion: BCY18469 demonstrated high affinity, specific targeting of EphA2, a favorable biodistribution profile, and clearance through renal pathways. These findings underscore the potentially important role of bicyclic peptides in advancing radiotheranostic approaches and encourage additional translational research.

Demonstration of in-vivo simultaneous 3D imaging with 18F-FDG and Na131I using Compton-PET system.

Simultaneous imaging of the SPECT tracer 131I and PET tracer 18F is important in the diagnosis of high- and low-grade thyroid cancers because high-grade thyroid cancers have high 18F-FDG and low 131I uptake, while low-grade thyroid cancers have high 131I and low 18F-FDG uptake. In this study, Na131I and 18F-FDG were simultaneously imaged using the Compton-PET system, in vivo. The angular resolution and sensitivity of the Compton camera with 356 keV gamma ray measured using a 133Ba point source were 12.3° and 2 × 10-5, respectively. The spatial resolution and sensitivity of PET were measured with a 22Na point source. The transaxial and axial spatial resolutions of the PET at the center of the FOV were 1.15 mm and 2.04 mm, respectively. Its sensitivity was 1.2 × 10-4. In-vivo images of the 18F and 131I isotopes were simultaneously acquired from mice. These showed that 18F-FDG was active in the heart, brown fat, and brain, while Na131I was active in the thyroid, stomach, and bladder. Artifacts were found in the Compton camera images when the activity of 131I was much lower than that of 18F. This study demonstrates the potential of simultaneous clinical imaging of 18F and 131I.

[18F]FSPG-PET provides an early marker of radiotherapy response in head and neck squamous cell cancer.

The ability to image early treatment response to radiotherapy in head and neck squamous cell carcinoma (HNSCC) will enable the identification of radioresistant tumor volumes suitable for treatment intensification. Here, we propose the system xc - radiotracer (4S)-4-(3-[18F]fluoropropyl)-L-glutamate ([18F]FSPG) as a non-invasive method to monitor radiation response in HNSCC. We assessed temporal changes in cell death, antioxidant status, and [18F]FSPG retention following a single dose of 10 Gy irradiation in FaDU HNSCC cells. Next, using a fractionated course of radiotherapy, we assessed tumor volume changes and performed [18F]FSPG-PET imaging in FaDU-bearing mouse xenografts, followed by ex vivo response assessment. In cells, 10 Gy irradiation reduced [18F]FSPG retention, coinciding with the induction of apoptosis and the production of reactive oxygen species. In vivo, [18F]FSPG tumor retention was halved seven days after the start of treatment, which preceded radiotherapy-induced tumor shrinkage, thereby confirming [18F]FSPG-PET as an early and sensitive marker of radiation response.

Decision-Tree Models Indicative of Microvascular Invasion on MRI Predict Survival in Patients with Hepatocellular Carcinoma Following Tumor Ablation.

Purpose: Histological microvascular invasion (MVI) is a risk factor for poor survival and early recurrence in hepatocellular carcinoma (HCC) after surgery. Its prognostic value in the setting of locoregional therapies (LRT), where no tissue samples are obtained, remains unknown. This study aims to establish CT-derived indices indicative of MVI on liver MRI with superior soft tissue contrast and evaluate their association with patient survival after ablation via interstitial brachytherapy (iBT) versus iBT combined with prior conventional transarterial chemoembolization (cTACE). Patients and Methods: Ninety-five consecutive patients, who underwent ablation via iBT alone (n = 47) or combined with cTACE (n = 48), were retrospectively included between 01/2016 and 12/2017. All patients received contrast-enhanced MRI prior to LRT. Overall (OS), progression-free survival (PFS), and time-to-progression (TTP) were assessed. Decision-tree models to determine Radiogenomic Venous Invasion (RVI) and Two-Trait Predictor of Venous Invasion (TTPVI) on baseline MRI were established, validated on an external test set (TCGA-LIHC), and applied in the study cohorts to investigate their prognostic value for patient survival. Statistics included Fisher's exact and t-test, Kaplan-Meier and cox-regression analysis, area under the receiver operating characteristic curve (AUC-ROC) and Pearson's correlation. Results: OS, PFS, and TTP were similar in both treatment groups. In the external dataset, RVI showed low sensitivity but relatively high specificity (AUC-ROC = 0.53), and TTPVI high sensitivity but only low specificity (AUC-ROC = 0.61) for histological MVI. In patients following iBT alone, positive RVI and TTPVI traits were associated with poorer OS (RVI: p < 0.01; TTPVI: p = 0.08), PFS (p = 0.04; p = 0.04), and TTP (p = 0.14; p = 0.03), respectively. However, when patients with combined cTACE and iBT were stratified by RVI or TTPVI, no differences in OS (p = 0.75; p = 0.55), PFS (p = 0.70; p = 0.43), or TTP (p = 0.33; p = 0.27) were observed. Conclusion: The study underscores the role of non-invasive imaging biomarkers indicative of MVI to identify patients, who would potentially benefit from embolotherapy via cTACE prior to ablation rather than ablation alone.

In vivo organoid growth monitoring by stimulated Raman histology.

Patient-derived tumor organoids have emerged as a crucial tool for assessing the efficacy of chemotherapy and conducting preclinical drug screenings. However, the conventional histological investigation of these organoids necessitates their devitalization through fixation and slicing, limiting their utility to a single-time analysis. Here, we use stimulated Raman histology (SRH) to demonstrate non-destructive, label-free virtual staining of 3D organoids, while preserving their viability and growth. This novel approach provides contrast similar to conventional staining methods, allowing for the continuous monitoring of organoids over time. Our results demonstrate that SRH transforms organoids from one-time use products into repeatable models, facilitating the efficient selection of effective drug combinations. This advancement holds promise for personalized cancer treatment, allowing for the dynamic assessment and optimization of chemotherapy treatments in patient-specific contexts.

Fibroblast Activation Protein-Directed Imaging Outperforms 18F-FDG PET/CT in Malignant Mesothelioma: A Prospective, Single-Center, Observational Trial.

The fibroblast activation protein (FAP) is highly expressed in tumor and stromal cells of mesothelioma and thus is an interesting imaging and therapeutic target. Previous data on PET imaging with radiolabeled FAP inhibitors (FAPIs) suggest high potential for superior tumor detection. Here, we report the data of a large malignant pleural mesothelioma cohort within a 68Ga-FAPI46 PET observational trial (NCT04571086). Methods: Of 43 eligible patients with suspected or proven malignant mesothelioma, 41 could be included in the data analysis of the 68Ga-FAPI46 PET observational trial. All patients underwent 68Ga-FAPI46 PET/CT, contrast-enhanced CT, and 18F-FDG PET/CT. The primary study endpoint was the association of 68Ga-FAPI46 PET uptake intensity and histopathologic FAP expression. Furthermore, secondary endpoints were detection rate and sensitivity, specificity, and positive and negative predictive values as compared with 18F-FDG PET/CT. Datasets were interpreted by 2 masked readers. Results: The primary endpoint was met, and the association between 68Ga-FAPI46 SUVmax or SUVpeak and histopathologic FAP expression was significant (SUVmax: r = 0.49, P = 0.037; SUVpeak: r = 0.51, P = 0.030).68Ga-FAPI46 and 18F-FDG showed similar sensitivity by histopathologic validation on a per-patient (100.0% vs. 97.3%) and per region (98.0% vs. 95.9%) basis. Per-region analysis revealed higher 68Ga-FAPI46 than 18F-FDG specificity (81.1% vs. 36.8%) and positive predictive value (87.5% vs. 66.2%). Conclusion: We confirm an association of 68Ga-FAPI46 uptake and histopathologic FAP expression in mesothelioma patients. Additionally, we report high sensitivity and superior specificity and positive predictive value for 68Ga-FAPI46 versus 18F-FDG.

Deep learning-based virtual H& E staining from label-free autofluorescence lifetime images.

Label-free autofluorescence lifetime is a unique feature of the inherent fluorescence signals emitted by natural fluorophores in biological samples. Fluorescence lifetime imaging microscopy (FLIM) can capture these signals enabling comprehensive analyses of biological samples. Despite the fundamental importance and wide application of FLIM in biomedical and clinical sciences, existing methods for analysing FLIM images often struggle to provide rapid and precise interpretations without reliable references, such as histology images, which are usually unavailable alongside FLIM images. To address this issue, we propose a deep learning (DL)-based approach for generating virtual Hematoxylin and Eosin (H&E) staining. By combining an advanced DL model with a contemporary image quality metric, we can generate clinical-grade virtual H&E-stained images from label-free FLIM images acquired on unstained tissue samples. Our experiments also show that the inclusion of lifetime information, an extra dimension beyond intensity, results in more accurate reconstructions of virtual staining when compared to using intensity-only images. This advancement allows for the instant and accurate interpretation of FLIM images at the cellular level without the complexities associated with co-registering FLIM and histology images. Consequently, we are able to identify distinct lifetime signatures of seven different cell types commonly found in the tumour microenvironment, opening up new opportunities towards biomarker-free tissue histology using FLIM across multiple cancer types.

Potential Application of the Myocardial Scintigraphy Agent [123I]BMIPP in Colon Cancer Cell Imaging.

[123I]ß-methyl-p-iodophenyl-pentadecanoic acid ([123I]BMIPP), which is used for nuclear medicine imaging of myocardial fatty acid metabolism, accumulates in cancer cells. However, the mechanism of accumulation remains unknown. Therefore, this study aimed to elucidate the accumulation and accumulation mechanism of [123I]BMIPP in cancer cells. We compared the accumulation of [123I]BMIPP in cancer cells with that of [18F]FDG and found that [123I]BMIPP was a much higher accumulation than [18F]FDG. The accumulation of [123I]BMIPP was evaluated in the presence of sulfosuccinimidyl oleate (SSO), a CD36 inhibitor, and lipofermata, a fatty acid transport protein (FATP) inhibitor, under low-temperature conditions and in the presence of etomoxir, a carnitine palmitoyl transferase I (CPT1) inhibitor. The results showed that [123I]BMIPP accumulation was decreased in the presence of SSO and lipofermata in H441, LS180, and DLD-1 cells, suggesting that FATPs and CD36 are involved in [123I]BMIPP uptake in cancer cells. [123I]BMIPP accumulation in all cancer cell lines was significantly decreased at 4 °C compared to that at 37 °C and increased in the presence of etomoxir in all cancer cell lines, suggesting that the accumulation of [123I]BMIPP in cancer cells is metabolically dependent. In a biological distribution study conducted using tumor-bearing mice transplanted with LS180 cells, [123I]BMIPP highly accumulated in not only LS180 cells but also normal tissues and organs (including blood and muscle). The tumor-to-intestine or large intestine ratios of [123I]BMIPP were similar to those of [18F]FDG, and the tumor-to-large-intestine ratios exceeded 1.0 during 30 min after [123I]BMIPP administration in the in vivo study. [123I]BMIPP is taken up by cancer cells via CD36 and FATP and incorporated into mitochondria via CPT1. Therefore, [123I]BMIPP may be useful for imaging cancers with activated fatty acid metabolism, such as colon cancer. However, the development of novel imaging radiotracers based on the chemical structure analog of [123I]BMIPP is needed.

A Near-Infrared-II Excitable Pyridinium Probe with 1000-Fold ON/OFF Ratio for γ-Glutamyltranspeptidase and Cancer Detection.

Activity-based detection of γ-Glutamyltranspeptidase (GGT) using near-infrared (NIR) fluorescent probes is a promising strategy for early cancer diagnosis. Although NIR pyridinium probes show high performance in biochemical analysis, the aggregation of both the probes and parental fluorochromes in biological environments is prone to result in a low signal-to-noise ratio (SBR), thus affecting their clinical applications. Here, we develop a GGT-activatable aggregate probe called OTBP-G for two-photon fluorescence imaging in various biological environments under 1040 nm excitation. By rationally tunning the hydrophilicity and donor-acceptor strength, we enable a synergistic effect between twisted intramolecular charge transfer and intersystem crossing processes and realize a perfect dark state for OTBP-G before activation. After the enzymatic reaction, the parental fluorochrome exhibits bright aggregation-induced emission peaking at 670 nm. The fluorochrome-to-probe transformation can induce 1000-fold fluorescence ON/OFF ratio, realizing in vitro GGT detection with an SBR > 900. Activation of OTBP-G occurs within 1 min in vivo, showing an SBR > 400 in mouse ear blood vessels. OTBP-G can further enable the early detection of pulmonary metastasis in breast cancer by topically spraying, outperforming the clinical standard hematoxylin and eosin staining. We anticipate that the in-depth study of OTBP-G can prompt the development of early cancer diagnosis and tumor-related physiological research. Moreover, this work highlights the crucial role of hydrophilicity and donor-acceptor strength in maximizing the ON/OFF ratio of the TICT probes and showcases the potential of OTBP as a versatile platform for activity-based sensing.

Increased [18F]FDG uptake of radiation-induced giant cells: a single-cell study in lung cancer models.

Positron emission tomography (PET), a cornerstone in cancer diagnosis and treatment monitoring, relies on the enhanced uptake of fluorodeoxyglucose ([18F]FDG) by cancer cells to highlight tumors and other malignancies. While instrumental in the clinical setting, the accuracy of [18F]FDG-PET is susceptible to metabolic changes introduced by radiation therapy. Specifically, radiation induces the formation of giant cells, whose metabolic characteristics and [18F]FDG uptake patterns are not fully understood. Through a novel single-cell gamma counting methodology, we characterized the [18F]FDG uptake of giant A549 and H1299 lung cancer cells that were induced by radiation, and found it to be considerably higher than that of their non-giant counterparts. This observation was further validated in tumor-bearing mice, which similarly demonstrated increased [18F]FDG uptake in radiation-induced giant cells. These findings underscore the metabolic implications of radiation-induced giant cells, as their enhanced [18F]FDG uptake could potentially obfuscate the interpretation of [18F]FDG-PET scans in patients who have recently undergone radiation therapy.

Protein nanoparticles as drug delivery systems for cancer theranostics.

Protein-based nanoparticles have garnered significant attention in theranostic applications due to their superior biocompatibility, exceptional biodegradability and ease of functionality. Compared to other nanocarriers, protein-based nanoparticles offer additional advantages, including biofunctionality and precise molecular recognition abilities, which make them highly effective in navigating complex biological environments. Moreover, proteins can serve as powerful tools with self-assembling structures and reagents that enhance cell penetration. And their derivation from abundant renewable sources and ability to degrade into harmless amino acids further enhance their suitability for biomedical applications. However, protein-based nanoparticles have so far not realized their full potential. In this review, we summarize recent advances in the use of protein nanoparticles in tumor diagnosis and treatment and outline typical methods for preparing protein nanoparticles. The review of protein nanoparticles may provide useful new insights into the development of biomaterial fabrication.

Challenges in the diagnosis and management of tumor-induced osteomalacia: A case report.

The present case report is aimed to highlight the difficulty and the reason for the delayed diagnosis of phosphaturic mesenchymal tumors, emphasizing the need of standardized protocols for diagnosis, surgery and follow-up in high-volume hospitals. The clinical signs and symptoms, diagnostic and therapeutic procedures, immunohistological features were analyzed. Delayed diagnosis of phosphaturic mesenchymal tumor was primarily due to non-specific clinical symptoms such as fatigue, muscular and bone pain, and multiple fractures. This cryptic clinical picture made the diagnosis tricky that led to treatment of patient for non-specific pain and stress fractures before to consider the tumor-induced osteomalacia syndrome. Some well-documented studies were found in the literature in which the history of trauma is a critical trigger of glomus tumors. Extra-subungual tumors most frequently occur in the knee and ankle regions, particularly among young adults, and the diagnosis is typically made approximately 7.2 years after initial symptom onset. The difficult tumor localization represented an additional obstacle to the prompt treatment, leading to delayed curative surgery.

Unsupervised mutual transformer learning for multi-gigapixel Whole Slide Image classification.

The classification of gigapixel Whole Slide Images (WSIs) is an important task in the emerging area of computational pathology. There has been a surge of interest in deep learning models for WSI classification with clinical applications such as cancer detection or prediction of cellular mutations. Most supervised methods require expensive and labor-intensive manual annotations by expert pathologists. Weakly supervised Multiple Instance Learning (MIL) methods have recently demonstrated excellent performance; however, they still require large-scale slide-level labeled training datasets that require a careful inspection of each slide by an expert pathologist. In this work, we propose a fully unsupervised WSI classification algorithm based on mutual transformer learning. The instances (i.e., patches) from gigapixel WSIs are transformed into a latent space and then inverse-transformed to the original space. Using the transformation loss, pseudo labels are generated and cleaned using a transformer label cleaner. The proposed transformer-based pseudo-label generator and cleaner modules mutually train each other iteratively in an unsupervised manner. A discriminative learning mechanism is introduced to improve normal versus cancerous instance labeling. In addition to the unsupervised learning, we demonstrate the effectiveness of the proposed framework for weakly supervised learning and cancer subtype classification as downstream analysis. Extensive experiments on four publicly available datasets show better performance of the proposed algorithm compared to the existing state-of-the-art methods.

68Ga-Fibroblast Activation Protein Inhibitor PET/CT Improves Detection of Intermediate and Low-Grade Sarcomas and Identifies Candidates for Radiopharmaceutical Therapy.

Fibroblast activation protein-α (FAP) is often highly expressed by sarcoma cells and by sarcoma-associated fibroblasts in the tumor microenvironment. This makes it a promising target for imaging and therapy. The level of FAP expression and the diagnostic value of 68Ga-FAP inhibitor (FAPI) PET for sarcoma subtypes are unknown. We assessed the diagnostic performance and accuracy of 68Ga-FAPI PET in various bone and soft-tissue sarcomas. Potential eligibility for FAP-targeted radiopharmaceutical therapy (FAP-RPT) was evaluated. Methods: This prospective observational trial enrolled 200 patients with bone and soft-tissue sarcoma who underwent 68Ga-FAPI PET/CT and 18F-FDG PET/CT (186/200, or 93%) for staging or restaging. The number of lesions detected and the uptake (SUVmax) of the primary tumor, lymph nodes, and visceral and bone metastases were analyzed. The Wilcoxon test was used for semiquantitative assessment. The association of 68Ga-FAPI uptake intensity, histopathologic grade, and FAP expression in sarcoma biopsy samples was analyzed using Spearman r correlation. The impact of 68Ga-FAPI PET on clinical management was investigated using questionnaires before and after PET/CT. Eligibility for FAP-RPT was defined by an SUVmax greater than 10 for all tumor regions. Results: 68Ga-FAPI uptake was heterogeneous among sarcoma subtypes. The 3 sarcoma entities with the highest uptake (mean SUVmax ± SD) were solitary fibrous tumor (24.7 ± 11.9), undifferentiated pleomorphic sarcoma (18.8 ± 13.1), and leiomyosarcoma (15.2 ± 10.2). Uptake of 68Ga-FAPI versus 18F-FDG was significantly higher in low-grade sarcomas (10.4 ± 8.5 vs. 7.0 ± 4.5, P = 0.01) and in potentially malignant intermediate or unpredictable sarcomas without a World Health Organization grade (not applicable [NA]; 22.3 ± 12.5 vs. 8.5 ± 10.0, P = 0.0004), including solitary fibrous tumor. The accuracy, as well as the detection rates, of 68Ga-FAPI was higher than that of 18F-FDG in low-grade sarcomas (accuracy, 92.2 vs. 80.0) and NA sarcomas (accuracy, 96.9 vs. 81.9). 68Ga-FAPI uptake and the histopathologic FAP expression score (n = 89) were moderately correlated (Spearman r = 0.43, P < 0.0002). Of 138 patients, 62 (45%) with metastatic sarcoma were eligible for FAP-RPT. Conclusion: In patients with low-grade and NA sarcomas, 68Ga-FAPI PET demonstrates uptake, detection rates, and accuracy superior to those of 18F-FDG PET. 68Ga-FAPI PET criteria identified eligibility for FAP-RPT in about half of sarcoma patients.

Radiolabelled FGF-2 for Imaging Activated Fibroblasts in the Tumor Micro-Environment.

Tumor associated fibroblasts (TAFs) play a key role in tumor growth and metastatization. TAFs overexpress different biomarkers that are usually expressed at low levels in physiological conditions. Among them are the fibroblast growth factor receptors (FGFRs) that bind the fibroblast growth factors (FGFs). In particular, the overexpression of FGFR-2c in tumors has been associated with advanced clinical stages and increased metastatization. Here, we developed a non-invasive tool to evaluate, in vivo, the expression of FGFR-2c in metastatic cancer. This is based on 99mTc-labelled FGF-2. METHODS: 99mTc-FGF-2 was tested in vitro and in vivo in mice bearing allografts of sarcoma cells. Images of 99mTc-FGF-2 were acquired using a new portable high-resolution ultra-sensitive gamma camera for small animal imaging. RESULTS: FGF-2 was labeled with high specific activity but low labelling efficiency, thus requiring post-labeling purification by gel-filtration chromatography. In vitro binding to 2C human keratinocytes showed a Kd of 3.36 × 10-9 M. In mice bearing J774A.1 cell allografts, we observed high and rapid tumor uptake of 99mTc-FGF-2 with a high Tumor/Blood ratio at 24 h post-injection (26.1 %ID/g and 12.9 %ID) with low kidney activity and moderate liver activity. CONCLUSIONS: we labeled FGF-2 with 99mTc and showed nanomolar Kd in vitro with human keratinocytes expressing FGF-2 receptors. In mice, 99mTc-FGF-2 rapidly and efficiently accumulated in tumors expressing FGF-2 receptors. This new radiopharmaceutical could be used in humans to image TAFs.

Self-Assembly of Peptides as an Alluring Approach toward Cancer Treatment and Imaging.

Cancer is a severe threat to humans, as it is the second leading cause of death after cardiovascular diseases and still poses the biggest challenge in the world of medicine. Due to its higher mortality rates and resistance, it requires a more focused and productive approach to provide the solution for it. Many therapies promising to deliver favorable results, such as chemotherapy and radiotherapy, have come up with more negatives than positives. Therefore, a new class of medicinal solutions and a more targeted approach is of the essence. This review highlights the alluring properties, configurations, and self-assembly of peptide molecules which benefit the traditional approach toward cancer therapy while sparing the healthy cells in the process. As targeted drug delivery systems, self-assembled peptides offer a wide spectrum of conjugation, biocompatibility, degradability-controlled responsiveness, and biomedical applications, including cancer treatment and cancer imaging.

Reproducing RECIST lesion selection via machine learning: Insights into intra and inter-radiologist variation.

Background: The Response Evaluation Criteria in Solid Tumors (RECIST) aims to provide a standardized approach to assess treatment response in solid tumors. However, discrepancies in the selection of measurable and target lesions among radiologists using these criteria pose a significant limitation to their reproducibility and accuracy. This study aimed to understand the factors contributing to this variability. Methods: Machine learning models were used to replicate, in parallel, the selection process of measurable and target lesions by two radiologists in a cohort of 40 patients from an internal pan-cancer dataset. The models were trained on lesion characteristics such as size, shape, texture, rank, and proximity to other lesions. Ablation experiments were conducted to evaluate the impact of lesion diameter, volume, and rank on the selection process. Results: The models successfully reproduced the selection of measurable lesions, relying primarily on size-related features. Similarly, the models reproduced target lesion selection, relying mostly on lesion rank. Beyond these features, the importance placed by different radiologists on different visual characteristics can vary, specifically when choosing target lesions. Worth noting that substantial variability was still observed between radiologists in both measurable and target lesion selection. Conclusions: Despite the successful replication of lesion selection, our results still revealed significant inter-radiologist disagreement. This underscores the necessity for more precise guidelines to standardize lesion selection processes and minimize reliance on individual interpretation and experience as a means to bridge existing ambiguities.