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Abstract Early survival prediction is vital for the clinical management of cancer patients, as tumors can be better controlled with personalized treatment planning. Traditional survival prediction methods are based on radiomics feature engineering and/or clinical indicators (e.g., cancer staging). Recently, survival prediction models with advances in deep learning techniques have achieved state-of-the-art performance in end-to-end survival prediction by exploiting deep features derived from medical images. However, existing models are heavily reliant on the prognostic information within primary tumors and cannot effectively leverage out-of-tumor prognostic information characterizing local tumor metastasis and adjacent tissue invasion. Also, existing models are sub-optimal in leveraging multi-modality medical images as they rely on empirically designed fusion strategies to integrate multi-modality information, where the fusion strategies are pre-defined based on domain-specific human prior knowledge and inherently limited in adaptability. Here, we present an Adaptive Multi-modality Segmentation-to-Survival model (AdaMSS) for survival prediction from multi-modality medical images. The AdaMSS can self-adapt its fusion strategy based on training data and also can adapt its focus regions to capture the prognostic information outside the primary tumors. Extensive experiments with two large cancer datasets (1380 patients from nine medical centers) show that our AdaMSS surmounts the state-of-the-art survival prediction performance (C-index: 0.804 and 0.757), demonstrating the potential to facilitate personalized treatment planning.

Abstract Background This study aimed to compare the diagnostic value of [68 Ga]Ga-DOTA-FAPI-04 and [18F]FDG PET/CT imaging for primary lesions and metastatic lymph nodes in patients with tonsil cancer. Method Twenty-one tonsil cancer patients who underwent [68 Ga]Ga-DOTA-FAPI-04 and [18F]FDG PET/CT scans within two weeks in our centre were retrospectively enrolled. The maximum standardized uptake value (SUVmax) and tumor-to-background ratio (TBR) of the two tracers were compared by using the Mann‒Whitney U test. In addition, the sensitivity, specificity, and accuracy of the two methods for diagnosing metastatic lymph nodes were analysed. Results In detecting primary lesions, the efficiency was higher for [68 Ga]Ga-DOTA-FAPI-04 PET/CT (20/22) than for [18F]FDG PET/CT (9/22). Although [68 Ga]Ga-DOTA-FAPI-04 uptake (SUVmax, 5.03 ± 4.06) was lower than [18F]FDG uptake (SUVmax, 7.90 ± 4.84, P = 0.006), [68 Ga]Ga-DOTA-FAPI-04 improved the distinction between the primary tumor and contralateral normal tonsillar tissue. The TBR was significantly higher for [68 Ga]Ga-DOTA-FAPI-04 PET/CT (3.19 ± 2.06) than for [18F]FDG PET/CT (1.89 ± 1.80) (p

Objective: The present study aimed to compare the diagnostic value of gallium-68-labeled fibroblast activation protein inhibitor positron emission tomography/computed tomography (68Ga-FAPI PET/CT) and fluorine-18-labeled fluorodeoxyglucose PET/CT (18F-FDG PET/CT) for detecting recurrent colorectal cancers (CRCs). Materials and Methods: Fifty-six patients (age: 18–80 years, 31 men and 25 women) with suspected recurrent CRC were enrolled and underwent 18F-FDG PET/CT and 68Ga-FAPI PET/CT sequentially within 1 week. The maximum standard uptake value (SUVmax), tumor-to-background ratio (TBR), and diagnostic accuracy were estimated and compared between the two modalities by using Student’s t-test. The Wilcoxon signed-rank test was used to compare peritoneal carcinoma index (PCI) scores between the two imaging modalities. Results: 68Ga-FAPI PET/CT showed higher sensitivity for detecting recurrence (93 % vs. 79 %); lymph node metastasis (89 % vs. 78 %), particularly peritoneal lymph node metastasis (92 % vs. 63 %); and metastatic implantation on the intestinal wall (100 % vs. 25 %) compared to 18F-FDG PET/CT. However, 68Ga-FAPI PET/CT showed lower sensitivity for detecting bone metastasis (67 % vs. 100 %). The mean SUVmax values of peritoneal metastases and metastatic implantation on the intestinal wall were 4.28 ± 2.70 and 7.58 ± 1.66 for 18F-FDG PET/CT and 5.66 ± 1.97 and 6.70 ± 0.25 for 68Ga-FAPI PET/CT, respectively. Furthermore, 68Ga-FAPI PET/CT showed significantly higher TBR for peritoneal metastatic lesions (4.22 ± 1.47 vs. 1.41 ± 0.89, p

Abstract Intercellular communication often relies on exosomes as messengers and is critical for cancer metastasis in hypoxic tumor microenvironment. Some circular RNAs (circRNAs) are enriched in cancer cell‐derived exosomes, but little is known about their ability to regulate intercellular communication and cancer metastasis. Here, by systematically analyzing exosomes secreted by non‐small cell lung cancer (NSCLC) cells, a hypoxia‐induced exosomal circPLEKHM1 is identified that drives NSCLC metastasis through polarizing macrophages toward to M2 type. Mechanistically, exosomal circPLEKHM1 promoted PABPC1‐eIF4G interaction to facilitate the translation of the oncostatin M receptor (OSMR), thereby promoting macrophage polarization for cancer metastasis. Importantly, circPLEKHM1‐targeted therapy significantly reduces NSCLC metastasis in vivo. circPLEKHM1 serves as a prognostic biomarker for metastasis and poor survival in NSCLC patients. This study unveils a new circRNA‐mediated mechanism underlying how cancer cells crosstalk with macrophages within the hypoxic tumor microenvironment to promote metastasis, highlighting the importance of exosomal circPLEKHM1 as a prognostic biomarker and therapeutic target for lung cancer metastasis.

Abstract Background The aim of this study was to evaluate the efficacy of fluorine 18 (18F) labeled fibroblast activation protein inhibitor (FAPI) in identifying mediastinal and hilar lymph node metastases and to develop a model to quantitatively and repeatedly identify lymph node status. Methods Twenty-seven patients with 137 lymph nodes were identified by two PET/CT images. The sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) of lymph node status were analyzed, and the optimal cut-off value was identified by ROC analysis. Results The SUVmax of metastatic lymph nodes on 18F-FAPI was higher than that on 18F-FDG PET/CT (10.87 ± 7.29 vs 6.08 ± 5.37, p

Abstract Bone metastasis is of common occurrence in renal cell carcinoma with poor prognosis, but no optimal treatment approach has been established for bone metastatic renal cell carcinoma. To explore the potential therapeutic targets for bone metastatic renal cell carcinoma, we profile single cell transcriptomes of 6 primary renal cell carcinoma and 9 bone metastatic renal cell carcinoma. We also include scRNA-seq data of early-stage renal cell carcinoma, late-stage renal cell carcinoma, normal kidneys and healthy bone marrow samples in the study to better understand the bone metastasis niche. The molecular properties and dynamic changes of major cell lineages in bone metastatic environment of renal cell carcinoma are characterized. Bone metastatic renal cell carcinoma is associated with multifaceted immune deficiency together with cancer-associated fibroblasts, specifically appearance of macrophages exhibiting malignant and pro-angiogenic features. We also reveal the dominance of immune inhibitory T cells in the bone metastatic renal cell carcinoma which can be partially restored by the treatment. Trajectory analysis showes that myeloid-derived suppressor cells are progenitors of macrophages in the bone metastatic renal cell carcinoma while monocytes are their progenitors in primary tumors and healthy bone marrows. Additionally, the infiltration of immune inhibitory CD47 + T cells is observed in bone metastatic tumors, which may be a result of reduced phagocytosis by SIRPA-expressing macrophages in the bone microenvironment. Together, our results provide a systematic view of various cell types in bone metastatic renal cell carcinoma and suggest avenues for therapeutic solutions.

Abstract Objective To improve the PET image quality by a deep progressive learning (DPL) reconstruction algorithm and evaluate the DPL performance in lesion quantification. Methods We reconstructed PET images from 48 oncological patients using ordered subset expectation maximization (OSEM) and deep progressive learning (DPL) methods. The patients were enrolled into three overlapped studies: 11 patients for image quality assessment (study 1), 34 patients for sub-centimeter lesion quantification (study 2), and 28 patients for imaging of overweight or obese individuals (study 3). In study 1, we evaluated the image quality visually based on four criteria: overall score, image sharpness, image noise, and diagnostic confidence. We also measured the image quality quantitatively using the signal-to-background ratio (SBR), signal-to-noise ratio (SNR), contrast-to-background ratio (CBR), and contrast-to-noise ratio (CNR). To evaluate the performance of the DPL algorithm in quantifying lesions, we compared the maximum standardized uptake values (SUVmax), SBR, CBR, SNR and CNR of 63 sub-centimeter lesions in study 2 and 44 lesions in study 3. Results DPL produced better PET image quality than OSEM did based on the visual evaluation methods when the acquisition time was 0.5, 1.0 and 1.5 min/bed. However, no discernible differences were found between the two methods when the acquisition time was 2.0, 2.5 and 3.0 min/bed. Quantitative results showed that DPL had significantly higher values of SBR, CBR, SNR, and CNR than OSEM did for each acquisition time. For sub-centimeter lesion quantification, the SUVmax, SBR, CBR, SNR, and CNR of DPL were significantly enhanced, compared with OSEM. Similarly, for lesion quantification in overweight and obese patients, DPL significantly increased these parameters compared with OSEM. Conclusion The DPL algorithm dramatically enhanced the quality of PET images and enabled more accurate quantification of sub-centimeters lesions in patients and lesions in overweight or obese patients. This is particularly beneficial for overweight or obese patients who usually have lower image quality due to the increased attenuation.

Abstract Background The main problem of positron emission tomography/computed tomography (PET/CT) for lymph node (LN) staging is the high false positive rate (FPR). Thus, we aimed to explore a clinico-biological-radiomics (CBR) model via machine learning (ML) to reduce FPR and improve the accuracy for predicting the hypermetabolic mediastinal–hilar LNs status in lung cancer than conventional PET/CT. Methods A total of 260 lung cancer patients with hypermetabolic mediastinal–hilar LNs (SUVmax ≥ 2.5) were retrospectively reviewed. Patients were treated with surgery with systematic LN resection and pathologically divided into the LN negative (LN-) and positive (LN +) groups, and randomly assigned into the training (n = 182) and test (n = 78) sets. Preoperative CBR dataset containing 1738 multi-scale features was constructed for all patients. Prediction models for hypermetabolic LNs status were developed using the features selected by the supervised ML algorithms, and evaluated using the classical diagnostic indicators. Then, a nomogram was developed based on the model with the highest area under the curve (AUC) and the lowest FPR, and validated by the calibration plots. Results In total, 109 LN− and 151 LN + patients were enrolled in this study. 6 independent prediction models were developed to differentiate LN− from LN + patients using the selected features from clinico-biological-image dataset, radiomics dataset, and their combined CBR dataset, respectively. The DeLong test showed that the CBR Model containing all-scale features held the highest predictive efficiency and the lowest FPR among all of established models (p

Abstract Objective Intra-tumoral heterogeneity of 18F‐fluorodeoxyglucose (18F‐FDG) uptake has been proven to be a surrogate marker for predicting treatment outcome in various tumors. However, the value of intra-tumoral heterogeneity in metastatic Human epidermal growth factor receptor 2(HER2) positive breast cancer (MHBC) remains unknown. The aim of this study was to evaluate 18F‐FDG uptake heterogeneity to predict the treatment outcome of the dual target therapy with Trastuzumab and Pertuzumab(TP) in MHBC. Methods Thirty-two patients with MHBC who underwent 18F-FDG positron emission tomography/computed tomography (PET/CT) scan before TP were enrolled retrospectively. The region of interesting (ROI) of the lesions were drawn, and maximum standard uptake value (SUVmax), mean standard uptake value (SUVmean), total lesion glycolysis (TLG), metabolic tumor volume (MTV) and heterogeneity index (HI) were recorded. Correlation between PET/CT parameters and the treatment outcome was analyzed by Spearman Rank Test. The ability to predict prognosis were determined by time‐dependent survival receiver operating characteristic (ROC) analysis. And the survival analyses were then estimated by Kaplan‐Meier method and compared by log‐rank test. Results The survival analysis showed that HI50% calculated by delineating the lesion with 50%SUVmax as threshold was a significant predictor of patients with MHBC treated by the treatment with TP. Patients with HI50% (≥ 1.571) had a significantly worse prognosis of progression free survival (PFS) (6.87 vs. Not Reach, p = 0.001). The area under curve (AUC), the sensitivity and the specificity were 0.88, 100% and 63.6% for PFS, respectively. Conclusion 18F-FDG uptake heterogeneity may be useful for predicting the prognosis of MHBC patients treated by TP.

Background: PSMA-negative but FDG-positive (PSMA−/FDG+) lesion in dual-tracer ( 68 Ga-PSMA and 18 F-FDG) positron emission tomography/computed tomography (PET/CT) is associated with an unfavorable response to Lutetium-177 ( 177 Lu)-PSMA-617. This study sought to develop both radiomics and clinical models for the precise prediction of the presence of PSMA−/FDG+ lesions in patients with castration-resistant prostate cancer (CPRC). Methods: A cohort of 298 patients who underwent dual-tracer PET/CT with a less than 5-day interval was included. The evaluation of the prognostic performance of the radiomics model drew upon the survival data derived from 40 patients with CRPC treated with 177 Lu-PSMA-617 in an external cohort. Two endpoints were evaluated: (a) prostate-specific antigen (PSA) response rate, defined as a reduction exceeding 50% from baseline and (b) overall survival (OS), measured from the initiation of 177 Lu-PSMA-617 to death from any cause. Results: PSMA−/FDG+ lesions were identified in 56 (18.8%) CRPC patients. Both radiomics (area under the curve [AUC], 0.83) and clinical models (AUC, 0.78) demonstrated robust performance in PSMA−/FDG+ lesion prediction. Decision curve analysis revealed that the radiomics model yielded a net benefit over the ‘screen all’ strategy at a threshold probability of ⩾4%. At a 5% probability threshold, the radiomics model facilitated a 21% reduction in 18 F-FDG PET/CT scans while only missing 2% of PSMA−/FDG+ cases. Patients with a low estimated score exhibited significantly prolonged OS (hazard ratio = 0.49, p = 0.029) and a higher PSA response rate (75% versus 35%, p = 0.011) compared to those with a high estimated score. Conclusion: This study successfully developed two models with accurate estimations of the risk associated with PSMA−/FDG+ lesions in CRPC patients. These models held potential utility in aiding the selection of candidates for 177 Lu-PSMA-617 treatment and guiding 68 Ga-PSMA PET/CT-directed radiotherapy.

Though the development of the diverse hypoxia-activated prodrugs (HAPs) has made great progresses in the last several decades, current cancer therapy based on HAPs still suffers many obstacles, e.g., poor therapeutic outcome owing to hard deep reaching to hypoxic region, and the occurrence of metastasis due to hypoxia. Inspired by engineered niches, a novel functional chitosan polymer (CS-FTP) is synthesized for construction of a hydrogel-based bio-niche (CS-FTP-gel) in aiming at remodeling tumor hypoxic microenvironment. The CS-FTP polymers are crosslinked to form a niche-like hydrogel via enzyme-mediated oxygen-consumable dimerization after injected into tumor, in which a HAP (i.e., AQ4N) could be physically encapsulated, resulting in enhanced tumor hypoxia to facilitate AQ4N-AQ4 toxic transformation for maximizing efficacy of chemotherapy. Furthermore, Pazopanib (PAZ) conjugated onto the CS backbone via ROS-sensitive linker undergoes a stimuli-responsive release behavior to promote antiangiogenesis for tumor starvation, eventually contributing to the inhibition of lung metastasis and synergistic action with AQ4N-based chemotherapy for an orthotopic 4T1 breast tumor model. This study provides a promising strategy for hypoxia-based chemotherapy and demonstrates an encouraging clinical potential for multifunctional hydrogel applicable for antitumor treatment.

The success of the PROfound, IPATential150, and TheraP trials promoted the transition from sequential treatment to therapeutic targets (TTs)‐guided precision treatment in metastatic castration‐resistant prostate cancer (mCRPC). The objective of this study was to evaluate the prevalence and prognostic value of TTs from these three trials. All included Chinese mCRPC patients underwent circulating tumor DNA (ctDNA) sequencing, PTEN status assessment, and dual‐tracer [68Ga‐prostate‐specific membrane antigen (PSMA) and 18F‐fluorodexyglucose (FDG)] positron emission tomography/computed tomography (PET/CT). Previous treatment with cabazitaxel, Lu‐PSMA or olaparib was unallowed. Patients with known significant sarcomatoid or spindle cell or neuroendocrine small cell components were also excluded. TTs were defined as positive as follows: (a) high PSMA and no PSMA−/FDG+ disease on dual‐tracer PET/CT scans; (b) defects in homologous recombination repair (HRR) genes in ctDNA; and (c) loss of PTEN immunohistochemistry staining in tumor tissue. The prevalence and prognostic value on progression‐free survival (PFS) of TTs were evaluated. A total of 106 consecutive mCRPC patients were included. The prevalence of positive PET/CT, HRR defect, and PTEN loss was 30%, 29% and 16%, respectively. Sixty‐three patients had at least one TT. Metastatic volume (odds ratio = 5.0; P = 0.017) was the only independent factor of positive TT in multivariate analysis. Seventy‐four patients received abiraterone after TT screening. Patients with positive PET/CT (P = 0.011) and HRR defect (P = 0.002) had a significantly shorter PFS after receiving abiraterone than patients with negative TTs. However, PTEN status was unrelated to PFS, which may be due to a less number of patients with PTEN loss (P = 0.952). Overall, patients with any positive TTs had a significantly shorter PFS after abiraterone than patients with negative TTs (P = 0.009). Nearly 60% of Chinese patients with mCRPC who had a poor prognosis on abiraterone were candidates for precision treatments based on the specific criteria of TTs.

Introduction: Photothermal therapy can be synergistically combined with chemotherapy to improve the therapeutic effect for colon cancer. However, conventional therapeutic agents have side effects in normal tissues, limiting their application. Objectives: To reduce these side effects, a smart agent (Cur@HKUST-1@PVP) whose functionality is triggered by the high content of endogenous hydrogen sulfide in colon tumors was engineered for photoacoustic imaging-guided combination of photothermal therapy and chemotherapy for colon tumors. Methods: After reacting with hydrogen sulfide, Cur@HKUST-1@PVP simultaneously generates CuS and releases curcumin. The generated CuS serves as an imaging agent for both photothermal therapy and photoacoustic imaging, while the released curcumin is used for chemotherapy. Results: In vivo photoacoustic imaging experiments demonstrated that Cur@HKUST-1@PVP can be used for selectively imaging colon cancer tumors. In vivo experiments in mice for treatment suggested that the endogenous hydrogen sulfide-activated combination of photothermal therapy and chemotherapy has a better treatment effect that photothermal therapy or chemotherapy treatment alone. Conclusion: The endogenous hydrogen sulfide-activated Cur@HKUST-1@PVP agent developed herein shows great potential for the accurate diagnosis and effective treatment of colon cancer.

Abstract Background Predictive biomarkers are needed to identify oestrogen receptor-positive, human epidermal growth factor receptor 2-negative (ER + /HER2-) metastatic breast cancer (MBC) patients who would likely benefit from cyclin-dependent kinase 4 and 6 inhibitors combined with endocrine therapy. Therefore, we performed an exploratory study to evaluate the tumour heterogeneity parameters based on 16α-18F-fluoro-17β-oestradiol (18F-FES)-PET imaging as a potential marker to predict progression-free survival (PFS) in MBC patients receiving palbociclib combined with endocrine therapy. Methods Fifty-six ER + MBC patients underwent 18F-FES-PET/CT before the initiation of palbociclib. 18F-FES uptake was quantified and expressed as the standardized uptake value (SUV). Interlesional heterogeneity was qualitatively identified according to the presence or absence of 18F-FES-negative lesions. Intralesional heterogeneity was measured by the SUV-based heterogeneity index (HI = SUVmax/SUVmean). Association with survival was evaluated using the Cox proportional hazards model. Results A total of 551 metastatic lesions were found in 56 patients: 507 lesions were identified as 18F-FES-positive, 38 lesions were distributed across 10 patients without 18F-FES uptake, and the remaining 6 were liver lesions. Forty-three patients obtained a clinical benefit, and 13 developed progressive disease (PD) within 24 weeks. Nine out of 10 patients with an 18F-FES-negative site developed PD, and the median PFS was only 2.4 months. Among 46 patients with only 18F-FES-positive lesions, only four patients had PD, and the median PFS was 23.6 months. There were statistically significant differences between the two groups (P

PurposeTo develop and interpret optimal predictive models to identify epidermal growth factor receptor (EGFR) mutation status and subtypes in patients with lung adenocarcinoma based on multicentric 18F-FDG PET/CT data, and further construct a prognostic model to predict their clinical outcome.MethodsThe 18F-FDG PET/CT imaging and clinical characters of 767 patients with lung adenocarcinoma from 4 cohorts were collected. Seventy-six radiomics candidates using cross-combination method to identity EGFR mutation status and subtypes were built. Further, Shapley additive explanations and local interpretable model-agnostic explanations were used for optimal models’ interpretation. Moreover, in order to predict the overall survival, a multivariate Cox proportional hazard model based on handcrafted radiomics features and clinical characteristics was constructed. The predictive performance and clinical net benefit of the models were evaluated via area under receiver operating characteristic (AUC), C-index and decision curve analysis. ResultsAmong the 76 radiomics candidates, light gradient boosting machine classifier (LGBM) combined with recursive feature elimination wrapped LGBM feature selection method achieved best performance in predicting EGFR mutation status (AUC reached 0.80, 0.61, 0.71 in the internal test cohort and two external test cohorts, respectively). And extreme gradient boosting classifier combined with support vector machine feature selection method achieved best performance in predicting EGFR subtypes (AUC reached 0.76, 0.63, 0.61 in the internal test cohort and two external test cohorts, respectively). The C-index of the Cox proportional hazard model achieved 0.863.ConclusionsThe integration of cross-combination method and the external validation from multi-center data achieved a good prediction and generalization performance in predicting EGFR mutation status and its subtypes. The combination of handcrafted radiomics features and clinical factors achieved good performance in predicting prognosis. With the urgent needs of multicentric 18F-FDG PET/CT trails, robust and explainable radiomics models have great potential in decision making and prognosis prediction of lung adenocarcinoma.

Abstract Introduction Definitive chemoradiotherapy has established the standard non-surgical treatment for locally advanced esophageal cancer. The standard dose of 50–50.4 Gy has been established decades ago and been confirmed in modern trials. The theorical advantage of better local control and technical advances for less toxicity have encouraged clinicians for dose escalation investigation. 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) have the potential to tailor therapy for esophageal patients not showing response to CRT and pioneers the PET-based dose escalation. Methods and analysis The ESO-Shanghai 12 trial is a prospective multicenter randomized phase 3 study in which patients are randomized to either 61.2 Gy or 50.4 Gy of radiation dose by PET response. Both groups undergo concurrent chemoradiotherapy with paclitaxel/cisplatin regimen for 2 cycles followed by consolidation chemotherapy for 2 cycles. Patients with histologically confirmed ESCC [T1N1-3M0, T2-4NxM0, TxNxM1 (Supraclavicular lymph node metastasis only), (AJCC Cancer Staging Manual, 8th Edition)] and without any prior treatment of chemotherapy, radiotherapy or surgery against esophageal cancer will be eligible. The primary endpoints included overall survival in PET/CT non-responders (SUVmax > 4.0) and overall survival in total population. Patients will be stratified by standardized uptake volume, gross tumor volume and tumor location. The enrollment could be ended, when the number of PET/CT non-responder reached 132 and the total population reached 646 for randomization. Ethics and dissemination This trial has been approved by the Fudan University Shanghai Cancer Center Institutional Review Board. Trial results will be disseminated via peer reviewed scientific journals and conference presentations. Trial registration The trial was initiated in 2018 and is currently recruiting patients. Trial registration number NCT03790553.

Abstract Background Recently, immunotherapy has been used to treat metastatic triple‐negative breast cancer (mTNBC). Basic research has indicated a relation between tumor heterogeneity and the immune response. Tumor heterogeneity derived from 18F‐FDG PET/CT is a potential predictor of chemotherapy results; however, few studies have focused on immunotherapy. This study aims to develop a convenient and efficient measurement of tumor heterogeneity for the prediction of immunotherapy in mTNBC patients. Methods We enrolled mTNBC patients who received immunotherapy (PD‐1/PD‐L1 antibody) plus chemotherapy as first‐line treatment and underwent 18F‐FDG PET/CT scans before treatment. We defined a novel index representing tumor heterogeneity calculated from the standard uptake value (SUV) as IATH and IETH. Optimal cutoffs were determined using time‐dependent receiver operator characteristics (ROC) analysis. Results A total of 32 patients were enrolled and analyzed in this trial. A significantly longer median PFS was observed in the low SUVmax group than in the high SUVmax group (9.4 vs. 5.8 months, HR = 0.3, 95% CI 0.1–0.9, p = 0.025). The median PFS of low‐IATH patients was significantly longer than that of high‐IATH patients (HR = 0.3, 95% CI 0.1–0.8, p = 0.022). Similarly, patients with low IETH had significantly longer PFS than patients with high IETH (9.4 vs. 4.9 months, HR = 0.3, 95% CI 0.1–0.7, p = 0.01). Multivariate analysis demonstrated IETH as an independent predictor of PFS. Conclusions This study proposed a novel method to assess intratumor and intertumor heterogeneity among metastatic breast cancer patients and determined that baseline IETH derived from 18F‐FDG PET/CT could represent a simple and promising predictor for first‐line immunotherapy among mTNBC patients.

Brain metastases (BMs) of lung cancer are common malignant intracranial tumours associated with severe neurological symptoms and an abysmal prognosis. Prostate-specific membrane antigen (PSMA) has been reported to express significantly in a variety of solid tumours. However, the clinical applications of 68Ga-PSMA PET/CT and the mechanism of PSMA expression in patients with BMs of lung cancer have rarely been reported. Experiments with 68Ga-PSMA PET/CT and immunohistochemical staining were conducted to evaluate the expression of PSMA from seven patients with BMs of lung cancer who accepted surgical treatment in Fudan University Shanghai Cancer Center between October 2020 and October 2021. The mechanism of PSMA expression in BMs of lung cancer was explored by using single-cell RNA sequencing. The median maximum standardized uptake value (SUVmax) in BMs was higher than that in primary lung cancer (8.6 ± 2.8 vs. 3.6 ± 1.3, P

Abstract Background To develop and validate a survival model with clinico-biological features and 18F- FDG PET/CT radiomic features via machine learning, and for predicting the prognosis from the primary tumor of colorectal cancer. Methods A total of 196 pathologically confirmed patients with colorectal cancer (stage I to stage IV) were included. Preoperative clinical factors, serum tumor markers, and PET/CT radiomic features were included for the recurrence-free survival analysis. For the modeling and validation, patients were randomly divided into the training (n = 137) and validation (n = 59) set, while the 78 stage III patients [training (n = 55), and validation (n = 23)] was divided for the further experiment. After selecting features by the log-rank test and variable-hunting methods, random survival forest (RSF) models were built on the training set to analyze the prognostic value of selected features. The performance of models was measured by C-index and was tested on the validation set with bootstrapping. Feature importance and the Pearson correlation were also analyzed. Results Radiomics signature (containing four PET/CT features and four clinical factors) achieved the best result for prognostic prediction of 196 patients (C-index 0.780, 95% CI 0.634–0.877). Moreover, four features (including two clinical features and two radiomics features) were selected for prognostic prediction of the 78 stage III patients (C-index was 0.820, 95% CI 0.676–0.900). K–M curves of both models significantly stratified low-risk and high-risk groups (P

Abstract Chemodynamic therapy (CDT) has aroused extensive attention for conquering cancers because of its high specificity and low invasiveness. Quick generation of hydroxyl radicals (·OH) during CDT could induce more irreparable damage to cancer cells. The generation rate of ·OH could be magnified via the selection of suitable nanocatalysts or under the assistance of exogenous thermal energy from photothermal therapy (PTT). Here, we construct a kind of monodisperse core-shell Au@Cu2-xSe heterogeneous metal nanoparticles (NPs) for PTT boosted CDT synergistic therapy. Due to the localized surface plasmon resonance (LSPR) coupling effect in the core-shell structure, the photothermal conversion efficiency of Au@Cu2-xSe NPs is up to 56.6%. The in situ generated heat from photothermal can then accelerate the Fenton-like reaction at Cu+ sites to produce abundant ·OH, which will induce apoptotic cell death by attacking DNA, contributing to a heat-boosted CDT. Both in vitro and in vivo results showed that after this synergistic therapy, tumors could be remarkably suppressed. Guided by photoacoustic (PA) and computed tomography (CT) imaging, the therapeutic effects were more specified. Our results revealed that PA and CT dual-imaging-guided PTT boosted CDT synergistic therapy based on core-shell Au@Cu2-xSe NPs is an effective cancer treatment strategy. Graphical Abstract

ObjectiveDeep learning-based radiomics (DLR) has achieved great success in medical image analysis and has been considered a replacement for conventional radiomics that relies on handcrafted features. In this study, we aimed to explore the capability of DLR for the prediction of 5-year progression-free survival (PFS) in advanced nasopharyngeal carcinoma (NPC) using pretreatment PET/CT images.MethodsA total of 257 patients (170/87 patients in internal/external cohorts) with advanced NPC (TNM stage III or IVa) were enrolled. We developed an end-to-end multi-modality DLR model, in which a 3D convolutional neural network was optimized to extract deep features from pretreatment PET/CT images and predict the probability of 5-year PFS. The TNM stage, as a high-level clinical feature, could be integrated into our DLR model to further improve the prognostic performance. For a comparison between conventional radiomics and DLR, 1,456 handcrafted features were extracted, and optimal conventional radiomics methods were selected from 54 cross-combinations of six feature selection methods and nine classification methods. In addition, risk group stratification was performed with clinical signature, conventional radiomics signature, and DLR signature.ResultsOur multi-modality DLR model using both PET and CT achieved higher prognostic performance (area under the receiver operating characteristic curve (AUC) = 0.842 ± 0.034 and 0.823 ± 0.012 for the internal and external cohorts) than the optimal conventional radiomics method (AUC = 0.796 ± 0.033 and 0.782 ± 0.012). Furthermore, the multi-modality DLR model outperformed single-modality DLR models using only PET (AUC = 0.818 ± 0.029 and 0.796 ± 0.009) or only CT (AUC = 0.657 ± 0.055 and 0.645 ± 0.021). For risk group stratification, the conventional radiomics signature and DLR signature enabled significant difference between the high- and low-risk patient groups in both the internal and external cohorts (p < 0.001), while the clinical signature failed in the external cohort (p = 0.177).ConclusionOur study identified potential prognostic tools for survival prediction in advanced NPC, which suggests that DLR could provide complementary values to the current TNM staging.

BackgroundBreast cancer is a heterogeneous disease, and the human epidermal growth factor receptor 2 (HER2) expression may vary considerably between primary and metastatic lesions, or even within a single lesion. Repeated biopsies cannot always be performed. In this feasibility trial, we assessed whether a novel 68Ga-NOTA-MAL-MZHER2 (68Ga-HER2) affibody PET/CT could determine the HER2 status of each lesion if there was a clinical need for it.Methods68Ga-HER2 affibody PET/CT was performed in breast cancer patients if HER2 status remained unclear after standard examinations (including bone scan, 18F-FDG PET/CT, CT, and feasible biopsy). All available images for each patient were evaluated through an independent review of two committee-certified radiologists with nuclear medicine expertise. In case of discrepancy, adjudication by a third radiologist was performed as needed. All radiologists were blinded to the clinical information.ResultsTwenty-four patients were enrolled. 68Ga-HER2 affibody PET/CT was requested by physicians due to the following reasons: 6 with multiple primary cancers, 13 with metastases not amenable to biopsy or repeated biopsy, 6 with inconsistent HER2 status between primary and metastatic lesions, and 4 with different HER2 status within different metastases. The final PET report revealed that the 68Ga-HER2 affibody tumor uptake was considered positive in 16 patients, negative in 7 patients, and equivocal in one patient. The heterogeneity of 68Ga-HER2 affibody uptake was observed, with a maximal 8.5-fold difference within one patient and a maximal 11-fold difference between patients. 68Ga-HER2 affibody PET/CT demonstrated a high diagnostic accuracy in differentiating HER2-enriched breast cancer, with a sensitivity of 91.7% and a specificity of 84.6%, regardless of prior lines of anti-HER2 therapies.Conclusion68Ga-HER2 affibody PET/CT imaging could provide valuable information on HER2 expression of each tumor in the body of patients, which may help in personalized clinical decision-making. Its value is now under systemic assessment.

Abstract Background 99mTc bone scintigraphy (BS) is still the most common approach for the evaluation of bone metastasis in China. The purpose of this study was to investigate the necessity of BS as part of a routine preoperative workup for patients with cT1N0 subsolid lung cancer. Methods This was a prospective multicenter clinical trial (NCT03689439). Patients with cT1N0 subsolid nodules who were candidates for surgical resection were consecutively enrolled into the study. BS was performed preoperatively. The surgical plan could be changed if a positive result was detected. The primary endpoint was the incidence rate of the surgical plan being changed because of positive BS results. The secondary endpoint was the rate of positive BS findings and the rate of related complications. Results From November 2018 to July 2019, 691 patients were enrolled into the study. None of the patients had positive BS results and no surgical plans were changed by BS findings. There were 222 male and 469 female patients. The average age was 54.8 ± 3.7 years old. The average tumor diameter was 14.9 ± 4.2 mm. There were 282 patients with pure GGO nodules and 409 with part‐solid nodules. A total of 470 patients had a single nodule, while 221 patients had multifocal lesions. The number of patients whose pathological diagnosis was invasive adenocarcinoma, minimally invasive adenocarcinoma, adenocarcinoma in situ and mucinous adenocarcinoma was 357, 293, 32 and nine, respectively. The number of patients who underwent lobectomy, segmentectomy and wedge resection was 234, 199 and 258, respectively. Conclusions 99mTc bone scintigraphy is unnecessary in the preoperative workup for patients with cT1N0 subsolid lung cancer. Key points Significant findings of the study In this prospective study of 691 patients with cT1N0 subsolid lung cancer, no surgical plans were affected by positive bone scan findings. What this study adds We suggest physicians consider canceling BS from preoperative workup for cT1 subsolid lung cancer patients. Clinical trial registry number: NCT03689439.

Peritoneal implantation and lymph node metastasis have different driving mechanisms in ovarian cancer. Elucidating the underlying mechanism of lymph node metastasis is important for treatment outcomes. A new cell line, FDOVL, was established from a metastatic lymph node of a patient with primary platinum-resistant ovarian cancer and was then characterized. The effect of NOTCH1-p.C702fs mutation and NOTCH1 inhibitor on migration was evaluated in vitro and in vivo. Ten paired primary sites and metastatic lymph nodes were analyzed by RNA sequencing. The FDOVL cell line with serious karyotype abnormalities could be stably passaged and could be used to generated xenografts. NOTCH1-p.C702fs mutation was found exclusively in the FDOVL cell line and the metastatic lymph node. The mutation promoted migration and invasion in cell and animal models, and these effects were markedly repressed by the NOTCH inhibitor LY3039478. RNA sequencing confirmed CSF3 as the downstream effector of NOTCH1 mutation. Furthermore, the mutation was significantly more common in metastatic lymph nodes than in other peritoneal metastases in 10 paired samples (60% vs. 20%). The study revealed that NOTCH1 mutation is probably a driver of lymph node metastasis in ovarian cancer, which offers new ideas for the treatment of ovarian cancer lymph node metastasis with NOTCH inhibitors.

ObjectivesMantle cell lymphoma (MCL) represents a group of highly heterogeneous tumors, leading to a poor prognosis. Early prognosis prediction may guide the choice of therapeutic regimen. Thus, the purpose of this study was to investigate the potential application value of heterogeneity index (HI) in predicting the prognosis of MCL.MethodsA total of 83 patients with histologically proven MCL who underwent baseline fluorine-18-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) were retrospectively enrolled. The clinicopathologic index and PET/CT metabolic parameters containing maximum and mean standard uptake value (SUVmax and SUVmean), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and HI were evaluated. Receiver operating characteristic (ROC) curve analyses were performed to determine the optimal cutoff values of the parameters for progression-free survival (PFS) and overall survival (OS). Univariate and multivariate Cox regression were used to assess relationships between risk factors and recurrence. Kaplan–Meier plots were applied for survival analyses.ResultsIn univariate analyses, age [HR = 2.51, 95% CI = 1.20–5.24, p = 0.041 for body weight (BW)] and HI-BW (HR = 4.17, 95% CI = 1.00–17.38, p = 0.050) were significantly correlated with PFS. In multivariate analyses, age (HR = 2.61, 95% CI = 1.25–5.47, p = 0.011 for BW) and HI-BW (HR = 4.41, 95% CI = 1.06–18.41, p = 0.042) were independent predictors for PFS, but not for OS. B symptoms (HR = 5.00, 95% CI = 1.16–21.65, p = 0.031 for BW) were an independent prognostic factor for OS, but not for PFS. The other clinicopathologic index and PET/CT metabolic parameters were not related to outcome survival in MCL.ConclusionThe age and HI derived from baseline PET/CT parameters were significantly correlated with PFS in MCL patients.

BackgroundThe accurate definition of gross tumor volume (GTV) of esophageal squamous cell carcinoma (ESCC) can promote precise irradiation field determination, and further achieve the radiotherapy curative effect. This retrospective study is intended to assess the applicability of leveraging deep learning-based method to automatically define the GTV from 3D 18F-FDG PET/CT images of patients diagnosed with ESCC.MethodsWe perform experiments on a clinical cohort with 164 18F-FDG PET/CT scans. The state-of-the-art esophageal GTV segmentation deep neural net is first employed to delineate the lesion area on PET/CT images. Afterwards, we propose a novel equivalent truncated elliptical cone integral method (ETECIM) to estimate the GTV value. Indexes of Dice similarity coefficient (DSC), Hausdorff distance (HD), and mean surface distance (MSD) are used to evaluate the segmentation performance. Conformity index (CI), degree of inclusion (DI), and motion vector (MV) are used to assess the differences between predicted and ground truth tumors. Statistical differences in the GTV, DI, and position are also determined.ResultsWe perform 4-fold cross-validation for evaluation, reporting the values of DSC, HD, and MSD as 0.72 ± 0.02, 11.87 ± 4.20 mm, and 2.43 ± 0.60 mm (mean ± standard deviation), respectively. Pearson correlations (R2) achieve 0.8434, 0.8004, 0.9239, and 0.7119 for each fold cross-validation, and there is no significant difference (t = 1.193, p = 0.235) between the predicted and ground truth GTVs. For DI, a significant difference is found (t = −2.263, p = 0.009). For position assessment, there is no significant difference (left-right in x direction: t = 0.102, p = 0.919, anterior–posterior in y direction: t = 0.221, p = 0.826, and cranial–caudal in z direction: t = 0.569, p = 0.570) between the predicted and ground truth GTVs. The median of CI is 0.63, and the gotten MV is small.ConclusionsThe predicted tumors correspond well with the manual ground truth. The proposed GTV estimation approach ETECIM is more precise than the most commonly used voxel volume summation method. The ground truth GTVs can be solved out due to the good linear correlation with the predicted results. Deep learning-based method shows its promising in GTV definition and clinical radiotherapy application.

Abstract Background Postoperative pathologic risk factors (PRFs) could increase the recurrence rate in early-stage uterine cervical squamous cancer (ECSC). Our study intended to explore the efficiency of 18F-FDG PET/CT for assessing the pathologic risk status (PRS) in ECSC patients. Methods This retrospective study was performed in 240 ECSC patients with stage IA2-IIA2 (FIGO 2009), who underwent preoperative PET/CT scans and subsequent radical surgery between January 2010 and July 2015. Intermediate-risk (tumour diameter ≥ 4 cm, stromal invasion depth ≥ 1/2, lymphovascular space invasion (LVSI)), and high-risk factors (parametria involvement, positive surgery margin, pelvic lymph node metastasis) were confirmed by postoperative pathology. Patients with none of these PRFs were at a low risk for relapse. One of these PRFs was defined as positive risk. The relationship between each PRF and 18F-FDG uptake was analysed by t-test. Chi-square tests and logistic regression analyses were used to determine the efficiency of PET/CT parameters for assessing the PRS. The area under the curve (AUC) was used as an indicator for predictive efficiency. Results Patients with higher SUVmax (p

Abstract To investigate the feasibility and effectiveness of prostate‐specific membrane antigen (PSMA) imaging to make response assessment regarding novel hormone treatment and to predict the outcomes for metastatic castration‐resistant prostate cancer (mCRPC) patients. This retrospective study enrolled 68 mCRPC patients who had daily received a novel hormone agent named abiraterone. Tc‐99m PSMA single‐photon emission computed tomography (SPECT/CT) was performed at the baseline (SPECT/CT1) and after 3‐6 months of treatment (SPECT/CT2). The treatment response was determined by visual analysis based on molecular imaging PSMA (miPSMA) scores framework and was compared with conventional biochemical analysis. We chose either the hottest lesion (target A) or five of the hottest lesions (target B) to calculate the tumor/background ratio (TBR) and the maximum standardized uptake value (SUVmax) and compared their performances in predicting progression‐free survival (PFS). Changes in PSMA expression between SPECT/CT1 and SPECT/CT2 were well associated with the results of the visual analysis. The TBR and the SUVmax of both targets were significantly associated with the baseline serum PSA level (P

Abstract Background Intratumoral heterogeneity has an enormous effect on patient treatment and outcome. The purpose of the current study was to establish and validate a nomogram with intratumoral heterogeneity derived from 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) for prognosis of 5-Year progression-free survival (PFS) of patients with nasopharyngeal carcinoma (NPC). Methods A total of 171 NPC patients who underwent pretreatment 18F-FDG PET/CT were retrospectively enrolled. Data was randomly divided into training cohort (n = 101) and validation cohort (n = 70). The clinicopathologic parameters and the following PET parameters were analyzed: maximum and mean standardized uptake value (SUVmax, SUVmean), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and heterogeneity index (HI, SUVmax/SUVmean) for primary tumor and maximal neck lymph node. Cox analyses were performed on PFS in the training cohort. A prognostic nomogram based on this model was developed and validated. Results For the primary tumor, MTV-2.5, TLG-2.5, MTV-70%, and TLG-70% were significantly correlated with PFS. For the maximal neck lymph node, short diameter and HI were significantly correlated with PFS. Among the clinicopathologic parameters, M stage was a significant prognostic factor for recurrence. In multivariate analysis, M stage (P = 0.006), TLG-T-70% (P = 0.002), and HI-N (P = 0.018) were independent predictors. Based on this prognostic model, a nomogram was generated. The C-index of this model was 0.74 (95% CI: 0.63–0.85). For the cross validation, the C-index for the model was 0.73 (95% CI: 0.62–0.83) with the validation cohort. Patients with a risk score of ≥111 had poorer survival outcomes than those with a risk score of 0–76 and 77–110. Conclusions Intratumoral heterogeneity derived from 18F-FDG PET/CT could predict long-term outcome in patients with primary NPC. A combination of PET parameters and the TNM stage enables better stratification of patients into subgroups with different PFS rates.

To evaluate hepatobiliary-specific contrast agent (CA) mangafodipir trisodium (Mn-DPDP)–enhanced magnetic resonance imaging (MRI) for predicting the therapeutic efficacy of the vascular disrupting agent combretastatin A4 phosphate (CA4P) in rats with primary and secondary liver tumors, 36 primary hepatocellular carcinomas (HCCs) were raised by diethylnitrosamine gavage in 16 male rats, in 6 of which one rhabdomyosarcomas (R1) was intrahepatically implanted as secondary liver tumors. On a 3.0T MR scanner with a wrist coil, tumors were monitored weekly by T2-/T1-weighted images (T2WI/T1WI) and characterized by Mn-DPDP-enhanced MRI. CA4P-induced intratumoral necrosis was depicted by nonspecific gadoterate meglumine (Gd-DOTA)–enhanced MRI before and 12 h after therapy. Changes of tumor-to-liver contrast (ΔT/L) on Mn-DPDP-enhanced images were analyzed. In vivo MRI findings were verified by postmortem microangiography and histopathology. Rat models of primary HCCs in a full spectrum of differentiation and secondary R1 liver tumors were successfully generated. Mn-DPDP-enhanced ΔT/L was negatively correlated with HCC differentiation grade (P

Objective Primary mediastinal B-cell lymphoma (PMBCL) lacks standard treatment regimens. This study aimed to identify the disease’s clinical features and prognostic factors. Methods This retrospective study included 56 patients with PMBCL. Patient demographic details and clinicopathological characteristics were summarized, and their effects on progression-free survival (PFS) and overall survival (OS) were analyzed. Results The median patient age was 29 years (range, 14–56). Twenty-two patients received DA-EPOCH-R (dose-adjusted etoposide, vincristine, and doxorubicin for 96 hours with bolus doses of cyclophosphamide and oral prednisone, as well as rituximab), and 34 patients received R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, prednisone). Clinical/laboratory parameters, overall response rates, and 5-year PFS and OS rates did not differ between the treatment groups. Kaplan–Meier analysis indicated that late-stage disease and a higher International Prognostic Index (IPI) were associated with shorter PFS and OS. Furthermore, patients with B symptoms and first-line treatment non-responders exhibited worse OS. 18 Fluorodeoxyglucose-positron emission tomography/computed tomography quantitative parameters, such as higher metabolic tumor volume (MTV) and total lesion glycolysis (TLG), were corrected with shorter PFS. Conclusions This study revealed that stage IV disease, higher IPI, and B symptoms were poor prognostic factors in patients with PMBCL. Significantly, higher MTV and TLG portended worse PFS.

Abstract Combinations of immune checkpoint therapies show encouraging results in the treatment of many human cancers. However, the higher costs and greater side effects of such combinations compared with single‐agent immunotherapies limit their further applications. In this work, a novel smart agent, KN046@19F‐ZIF‐8, is developed to overcome these limitations. KN046 is a novel recombinant humanized PD‐L1/CTLA‐4 bispecific single‐domain antibody‐Fc fusion protein, which can bind to both PD‐L1 and CTLA‐4 effectively. ZIF‐8 is a smart delivery system, which can safely and effectively deliver KN406 to a tumor. In vitro and in vivo results demonstrate that the smart agent KN046@19F‐ZIF‐8 not only improves the immune response rate of the antibody drug in treatment of tumors but also reduces its toxic side effects, thereby achieving excellent antitumor efficacy. This study provides an engineering strategy for clinical applications of a more effective immunotherapy.

ObjectivesThe accurate assessment of lymph node metastases (LNMs) and the preoperative nodal (N) stage are critical for the precise treatment of patients with gastric cancer (GC). The diagnostic performance, however, of current imaging procedures used for this assessment is sub-optimal. Our aim was to investigate the value of preoperative 18F-FDG PET/CT radiomic features to predict LNMs and the N stage.MethodsWe retrospectively collected clinical and 18F-FDG PET/CT imaging data of 185 patients with GC who underwent total or partial radical gastrectomy. Patients were allocated to training and validation sets using the stratified method at a fixed ratio (8:2). There were 2,100 radiomic features extracted from the 18F-FDG PET/CT scans. After selecting radiomic features by the random forest, relevancy-based, and sequential forward selection methods, the BalancedBagging ensemble classifier was established for the preoperative prediction of LNMs, and the OneVsRest classifier for the N stage. The performance of the models was primarily evaluated by the AUC and accuracy, and validated by the independent validation methods. Analysis of the feature importance and the correlation were also conducted. We also compared the predictive performance of our radiomic models to that with the contrast-enhanced CT (CECT) and 18F-FDG PET/CT.ResultsThere were 185 patients—127 men, 58 women, with the median age of 62, and an age range of 22–86 years. One CT feature and one PET feature were selected to predict LNMs and achieved the best performance (AUC: 82.2%, accuracy: 85.2%). This radiomic model also detected some LNMs that were missed in CECT (19.6%) and 18F-FDG PET/CT (35.7%). For predicting the N stage, four CT features and one PET feature were selected (AUC: 73.7%, accuracy: 62.3%). Of note, a proportion of patients in the validation set whose LNMs were incorrectly staged by CECT (57.4%) and 18F-FDG PET/CT (55%) were diagnosed correctly by our radiomic model.ConclusionWe developed and validated two machine learning models based on the preoperative 18F-FDG PET/CT images that have a predictive value for LNMs and the N stage in GC. These predictive models show a promise to offer a potentially useful adjunct to current staging approaches for patients with GC.

ObjectivesMicrosatellite instability (MSI) status is an important hallmark for prognosis prediction and treatment recommendation of colorectal cancer (CRC). To address issues due to the invasiveness of clinical preoperative evaluation of microsatellite status, we investigated the value of preoperative 18F-FDG PET/CT radiomics with machine learning for predicting the microsatellite status of colorectal cancer patients.MethodsA total of 173 patients that underwent 18F-FDG PET/CT scans before operations were retrospectively analyzed in this study. The microsatellite status for each patient was identified as microsatellite instability-high (MSI-H) or microsatellite stable (MSS), according to the test for mismatch repair gene proteins with immunohistochemical staining methods. There were 2,492 radiomic features in total extracted from 18F-FDG PET/CT imaging. Then, radiomic features were selected through multivariate random forest selection and univariate relevancy tests after handling the imbalanced dataset through the random under-sampling method. Based on the selected features, we constructed a BalancedBagging model based on Adaboost classifiers to identify the MSI status in patients with CRC. The model performance was evaluated by the area under the curve (AUC), sensitivity, specificity, and accuracy on the validation dataset.ResultsThe ensemble model was constructed based on two radiomic features and achieved an 82.8% AUC for predicting the MSI status of colorectal cancer patients. The sensitivity, specificity, and accuracy were 83.3, 76.3, and 76.8%, respectively. The significant correlation of the selected two radiomic features with multiple effective clinical features was identified (p < 0.05).Conclusion18F-FDG PET/CT radiomics analysis with the machine learning model provided a quantitative, efficient, and non-invasive mechanism for identifying the microsatellite status of colorectal cancer patients, which optimized the treatment decision support.

objectiveDespite the heterogeneous biology of pancreatic cancer, similar surveillance schemas have been used. Identifying the high recurrence risk population and conducting prompt intervention may improve prognosis and prolong overall survival.MethodsOne hundred fifty-six resectable pancreatic cancer patients who had undergone 18F-FDG PET/CT from January 2013 to December 2018 were retrospectively reviewed. The patients were categorized into a training cohort (n = 109) and a validation cohort (n = 47). LIFEx software was used to extract radiomic features from PET/CT. The risk stratification system was based on predictive factors for recurrence, and the index of prediction accuracy was used to reflect both the discrimination and calibration.ResultsOverall, seven risk factors comprising the rad-score and clinical variables that were significantly correlated with relapse were incorporated into the final risk stratification system. The 1-year recurrence-free survival differed significantly among the low-, intermediate-, and high-risk groups (85.5, 24.0, and 9.1%, respectively; p < 0.0001). The C-index of the risk stratification system in the development cohort was 0.890 (95% CI, 0.835–0.945).ConclusionThe 18F-FDG PET/CT-based radiomic features and clinicopathological factors demonstrated good performance in predicting recurrence after pancreatectomy in pancreatic cancer patients, providing a strong recommendation for an adequate adjuvant therapy course in all patients. The high-risk recurrence population should proceed with closer follow-up in a clinical setting.

There is a balance between the fluorescence and photothermal properties of fluorescent molecules. Here, the authors report on an NIR-II fluorophore which binds with human serum albumin changing the equilibrium, increasing the photothermal efficiency, and demonstrate application of this for tumour ablation.

Constructing a hierarchical structure with tunable pore size is a practical method to improve the capacity of photocatalytic hydrogen production of catalysts. In this work, titanium dioxide/graphitic carbon nitride (TiO2/g-C3N4) nanofibers with hierarchical meso/macro-porous structure are fabricated by combining a one-step electrospinning method and calcination process, in which the hierarchical meso/macro-porous structure is developed by introducing polyvinylpyrrolidone and liquid paraffin into the electrospinning solution. Comprehensive characterizations reveal that the hierarchical meso/macro-porous TiO2/g-C3N4 nanofibers have improved ultraviolet-visible light absorption, the separation efficiency of carriers, and photocatalytic performance. The photocatalytic H2 evolution is up to 1202 μmol g−1 in 7 h, which is better than those of corresponding TiO2/g-C3N4 photocatalysts previously reported. This work provides a new strategy to build a hierarchical meso/macro-porous nanofiber and an ideal solution to improve the hydrogen production of TiO2/g-C3N4.

Background: In the setting of drug-resistant epilepsy (DRE), the success of surgery depends on the ability to accurately locate the epileptic foci to be resected or disconnected. However, the epileptic foci in a considerable percentage of the DRE patients cannot be adequately localised. This warrants the need for a reliable imaging strategy to identify the “concealed” epileptic regions. Methods: Brain specimens from DRE patients and kainate-induced epileptic mouse models were immuno-stained to evaluate the integrity of the blood-brain barrier (BBB). The expression of low-density lipoprotein receptor-related protein-1 (LRP1) in the epileptic region of DRE patients and kainate models was studied by immunofluorescence. A micellar-based LRP1-targeted paramagnetic probe (Gd3+-LP) was developed and its ability to define the epileptic foci was investigated by magnetic resonance imaging (MRI). Findings: The integrity of the BBB in the epileptic region of DRE patients and kainate mouse models were demonstrated. LRP1 expression levels in the epileptic foci of DRE patients and kainate models were 1.70–2.38 and 2.32–3.97 folds higher than in the control brain tissues, respectively. In vivo MRI demonstrated that Gd3+-LP offered 1.68 times higher (P

ObjectiveThe purpose of this study was to employ dual tracers 16α-[18F]fluoro-17β-estradiol (18F-FES) and [18F]fluorodeoxyglucose (18F-FDG) as imaging biomarkers in predicting progression-free survival (PFS) in ER-positive metastatic breast cancer (MBC) patients receiving fulvestrant therapy.MethodsWe retrospectively analyzed 35 HR+HER2- MBC patients who underwent 18F-FES and 18F-FDG PET/CT scans prior to fulvestrant therapy in our center. The SUVmax across all metastatic lesions on the PET/CT were assessed. The heterogeneity of ER expression was assigned by the presence of any 18F-FES negative lesions for patients with entirely 18F-FES positive lesions categorized into two groups by the median ratio of FES/FDG SUVmax, low FES/FDG, and high FES/FDG. PFS were estimated by the Kaplan-Meier method and compared by the log-rank test. Univariate and multivariate analyses were performed using the Cox proportional hazard model.ResultsIn total, 12 patients had both 18F-FES negative and positive lesions, indicating the heterogeneity of ER expression in metastatic lesions. These patients had a low median PFS of 5.5 months (95% CI 2.3–8.7). Of patients with entirely 18F-FES positive lesions, 11 had a low FES/FDG, and 12 had a high FES/FDG. These groups had a median PFS of 29.4 months (95% CI 2.3–56.5) and 14.7 months (95% CI 10.9–18.5), respectively. The patients were stratified in three categories based on incorporating both 18F-FES and 18F-FDG imaging results that were significantly correlated with PFS by univariate analysis (P < 0.001) and multivariate analysis (P = 0.006).Conclusion18F-FES and 18F-FDG PET could serve as prognostic imaging biomarkers for ER-positive MBC patients treated with fulvestrant therapy.

Compared to conventional cancer treatment, combination therapy based on well-designed nanoscale platforms may offer an opportunity to eliminate tumors and reduce recurrence and metastasis. In this study, we prepared multifunctional microspheres loading 131I-labeled hollow copper sulfide nanoparticles and paclitaxel (131I-HCuSNPs-MS-PTX) for imaging and therapeutics of W256/B breast tumors in rats. 18F-fluordeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) imaging detected that the expansion of the tumor volume was delayed (P

Abstract Background We aimed to evaluate the diagnostic performance of 99mTc-MIBI SPECT/CT and ultrasonography in patients with secondary hyperparathyroidism (SHPT), and explored the factors that affect the diagnostic performance. Methods 99mTc-MIBI SPECT/CT and ultrasonography were performed in 50 patients with SHPT within 1 month before they underwent surgery. Imaging results were confirmed by the pathology. Pearson correlation analysis was used to determine the correlation of PTH level with clinical data. The optimal cutoff value for predicting positive 99mTc-MIBI results was evaluated by ROC analysis in lesions diameter. Results Forty-nine patients had a positive 99mTc-MIBI imaging results and 39 patients had positive ultrasonography results. The sensitivities of 99mTc-MIBI and ultrasonography were 98.00% and 78.00%, respectively. A total of 199 lesions were resected in 50 patients. Among them, 183 lesions were proved to be parathyroid hyperplasia. On per-lesion basis analysis, the sensitivity and specificity of 99mTc-MIBI and ultrasonography were 59.34% and 75.00% vs 46.24% and 80.00%, respectively. The Pearson correlation analysis showed that the serum AKP and PTH level had a significant linear association (r = 0.699, P

Intravoxel incoherent motion has received extensive attention in brain studies for its potential as a non-invasive magnetic resonance perfusion method. However, studies on intravoxel incoherent motion imaging and crossed cerebellar diaschisis detection are relatively scarce. The aim of our study was to evaluate the feasibility of using intravoxel incoherent motion imaging in crossed cerebellar diaschisis diagnosis in subacute ischemic stroke patients by comparing results from intravoxel incoherent motion imaging, single-photon emission computed tomography, and arterial spin-labeling perfusion methods. In total, 39 patients with subacute ischemic stroke who underwent intravoxel incoherent motion, arterial spin-labeling, and single-photon emission computed tomography scanning were enrolled. Intravoxel incoherent motion-derived perfusion-related parameters including fast diffusion coefficient, vascular volume fraction, arterial spin-labeling-derived cerebral blood flow as well as single-photon emission computed tomography-derived cerebral blood flow of bilateral cerebellum were measured. A crossed cerebellar diaschisis-positive result was considered present with an asymmetry index ≥10% of single-photon emission computed tomography. In the crossed cerebellar diaschisis-positive group, fast diffusion coefficient, arterial spin-labeling-derived cerebral blood flow, and computed tomography-derived cerebral blood flow of the contralateral cerebellum decreased compared with those of the ipsilesional cerebellum; whereas vascular volume fraction significantly increased. The National Institutes of Health Stroke Scale score and infarct volume in the crossed cerebellar diaschisis-positive group were significantly higher than those in the crossed cerebellar diaschisis-negative group. A positive correlation was detected between the fast diffusion coefficient-based asymmetry index and the single-photon emission computed tomography-based asymmetry index, fast diffusion coefficient-based asymmetry, and arterial spin-labeling based asymmetry index; whereas the vascular volume fraction - based asymmetry index value had a negative correlation with the single-photon emission computed tomography-based asymmetry index and arterial spin-labeling based asymmetry index. Furthermore, the area under the receiver operating characteristic curve value of the arterial spin-labeling-based asymmetry index was 0.923. The fast diffusion coefficient derived from the intravoxel incoherent motion could be valuable for the assessment of crossed cerebellar diaschisis in supratentorial stroke patients.

Chemoresistance is a major cause of treatment failure in patients with lung cancer. Although the extensive efforts have been made in overcoming chemoresistance, the underlying mechanisms are still elusive. Cancer cells reprogram cellular metabolism to satisfy the demands of malignant phenotype. To reveal roles of cancer metabolism in regulating chemoresistance, we profiled the metabolic characteristics in paclitaxel-resistant lung cancer cells by flux assay. Glucose and oleate metabolism were significantly different between resistant and non-resistant cells. In addition, targeting metabolism as a strategy to overcome drug resistance was investigated using specific metabolic inhibitors. Inhibition of glycolysis and oxidative phosphorylation by 2-deoxyglucose and malonate, respectively, potentiated the effects of paclitaxel on nonresistant lung adenocarcinoma cells but not paclitaxel-resistant cells. By contrast, inhibition of lipolysis by mercaptoacetate or etomoxir synergistically inhibited drug-resistant lung adenocarcinoma cell proliferation. We conclude that lipolysis inhibition potentially be a therapeutic strategy to overcome drug resistance in lung cancer.

Most cancer cells exhibit a shift in glucose metabolic strategy, displaying increased glycolysis even with adequate oxygen supply. SUMO-specific proteases (SENPs) de-SUMOylate substrates including HIF1α and p53,two key regulators in cancer glucose metabolism, to regulate their activity, stability and subcellular localization. However, the role of SENPs in tumor glucose metabolism remains unclear. Here we report that SUMO-specific protease 2 (SENP2) negatively regulates aerobic glycolysis in MCF7 and MEF cells. Over-expression of SENP2 reduces the glucose uptake and lactate production, increasing the cellular ATP levels in MCF7 cells, while SENP2 knockout MEF cells show increased glucose uptake and lactate production along with the decreased ATP levels. Consistently, the MCF7 cells over-expressing SENP2 exhibit decreased expression levels of key glycolytic enzymes and an increased rate of glucose oxidation compared with control MCF7 cells, indicating inhibited glycolysis but enhanced oxidative mitochondrial respiration. Moreover, SENP2 over-expressing MCF7 cells demonstrated a reduced amount of phosphorylated AKT, whereas SENP2 knockout MEFs exhibit increased levels of phosphorylated AKT. Furthermore, inhibiting AKT phosphorylation by LY294002 rescued the phenotype induced by SENP2 deficiency in MEFs. In conclusion, SENP2 represses glycolysis and shifts glucose metabolic strategy, in part through inhibition of AKT phosphorylation. Our study reveals a novel function of SENP2 in regulating glucose metabolism.