While whole-body multimodal medical imaging scanners have been increasingly recognized for more effective medical applications, the excessive long acquisition time in PET-MR scanning is a major obstacle in more efficient clinical practice. Deep learning-based MRI translation provides a potential solution to reduce scan duration. However, current models often focus on specific anatomical regions and face challenges for whole-body scans that consists of highly heterogeneous feature distributions mainly due to (1) different anatomical regions across whole-body, and (2) lesions or pathological tissues. This paper tackles the challenges through a novel Heterogeneity-Adaptive Diffusion Schrodinger Bridge (HA-DSB) framework. By explicitly modeling translation as stochastic transport between source and target distributions, HA-DSB incorporates region context embeddings derived from a vision-language model (VLM) to enable region-specific modeling. To enhance fidelity of the pathological tissue, lesion-aware metabolic prior from PET is integrated directly into the bridge dynamics through a dual-stage guidance mechanism. Specifically, a PET-guided noise modulation module adaptively scales spatial diffusion perturbations during the forward process, while PET features are leveraged during the reverse process to selectively amplify lesion-relevant structures via an attention mechanism. Experiments demonstrate the superiority of our method across different body regions in whole-body MRI translation and show improved translation quality in lesion areas under PET guidance. Our code is available at Github.

A 44-year-old woman, previously treated with surgery for breast cancer and a left frontal brain metastasis, presented with seizures. 18 F-FET PET/MRI demonstrated a 18 F-FET-avid, enhancing lesion at the prior brain surgical area, suggestive of recurrence. However, subsequent surgical pathology identified only gliosis, with no tumor. This case demonstrates a limitation of 18 F-FET PET/MRI in differentiating between benign and malignant intracranial lesions.

Nectin-4 is a promising theranostic target for cancers treatment due to its high abundance/expression in different cancer entities such as bladder cancer, breast cancer, and pancreatic cancer This study evaluated the biodistribution and radiation dosimetry of [⁶⁸Ga]Ga-DOTA-Sar¹⁰-Nectin-4 ([⁶⁸Ga]Ga-FZ-NR-1), a novel Nectin-4-targeting PET tracer developed by our team, to assess its safety and support its clinical translation. Eight patients with pathologically confirmed malignancies (breast cancer, pancreatic cancer, or bladder cancer) underwent whole-body (WB) PET/CT scans at 10, 40, and 180 min after the injection of [⁶⁸Ga]Ga-FZ-NR-1. The images were reconstructed using the Ordered Subset Expectation Maximization (OSEM) algorithm with TOF and PSF technology. The brain, salivary, heart, lungs, stomach, spleen, liver, gallbladder, pancreas, kidneys, colon, and prostate in males or uterus in females as target organs were semi-automatically segmented on PET/CT images using the Hermes Internal Radiation Dosimetry (HIRD) software toolkit. Time-activity curves (TACs) were obtained for these organs based on measured activity concentrations. The time-integrated activity coefficients (TIACs) of these target organs were calculated by integrating the TACs. Organ-specific absorbed doses and the total body effective dose were estimated using IDAC-Dose 2.1 software. Meanwhile, bladder dosimetry employed a standard voiding model. [⁶⁸Ga]Ga-FZ-NR-1 was cleared rapidly, primarily via the urinary system. The highest organ absorbed doses per injected activity unit were observed in the kidneys (2.24 × 10⁻¹ mGy/MBq) and bladder wall (1.24 × 10⁻¹ mGy/MBq). Other notable organs were the salivary glands, with an absorbed dose of approximately 2.54 × 10⁻² mGy/MBq. The estimated total body effective dose per injected activity unit was approximately 2.00 × 10⁻² mSv/MBq. Preliminary clinical imaging showed high tracer uptake in breast, pancreatic, and bladder cancer lesions, highlighting its promising diagnostic potential for detecting Nectin-4-expressing tumors. This human dosimetry assessment of [⁶⁸Ga]Ga-FZ-NR-1 showed a total body effective dose of approximately 2.00 × 10⁻² mSv/MBq, similar to other 68Gallium-labeled tracers. Organ absorbed doses were well within the accepted limits, suggesting a favorable radiation risk profile for clinical application as a PET imaging agent targeting Nectin-4. Initial clinical imaging results demonstrates that [⁶⁸Ga]Ga-FZ-NR-1 provides clear visualization of both primary tumors and metastases with high Nectin-4 expression levels.

BACKGROUND:Lutetium-177 DOTA-TATE peptide receptor radionuclide therapy (PRRT) is an established and effective treatment modality for patients with metastatic neuroendocrine tumors (NETs). PURPOSE:This study aims to predict patient-absorbed doses from [177Lu]Lu-DOTA-TATE PRRT in the liver, kidney and lesion by utilizing patient-specific absorbed doses from pre-therapeutic [68Ga]Ga-DOTA-TATE PET/CT. METHODS:Before the treatment of cycle 1, 11 patients with NETs underwent PET/CT scans at 0.5, 1.0, 2.0 and 4.0 h after the injection of [68Ga]Ga-DOTA-TATE. Patients then received [177Lu]Lu-DOTA-TATE PRRT and underwent SPECT/CT scans at 4, 24, 96, and 168 h post-administration. The segmentations and dosimetry were performed by using a professional software. The linear regression model used the absorbed doses from [68Ga]Ga-DOTA-TATE alone as the predictor variable. The multiple linear regression model used the absorbed doses from [68Ga]Ga-DOTA-TATE and the relevant clinical biomarkers as the predictor variables. RESULTS:The mean absorbed doses from [177Lu]Lu-DOTA-TATE PRRT in kidney and liver were 4.1 and 2.1 Gy, respectively. In comparison, the mean absorbed doses from [68Ga]Ga-DOTA-TATE were significantly lower: 18.0 mGy and 11.0 mGy, respectively. For lesions, the maximum absorbed dose from [68Ga]Ga-DOTA-TATE ranged from 24.1 to 170.4 mGy, while the maximum absorbed dose from [177Lu]Lu-DOTA-TATE PRRT was significantly higher, ranging from 9.6 to 77.9 Gy. The linear regression model yielded moderate R-squared values of 0.50, 0.59, and 0.36 for kidney, liver and lesion, respectively. The performance of multiple linear regression model was better, with R-squared values increasing to 0.81, 0.77, and 0.84. CONCLUSION:Absorbed doses from [177Lu]Lu-DOTA-TATE PRRT can be accurately predicted. Moreover, our models are formalized into simple equations.

As body mass index (BMI) increases, the quality of 2-deoxy-2-[fluorine-18]fluoro-D-glucose (18F-FDG) positron emission tomography (PET) images reconstructed with ordered subset expectation maximization (OSEM) declines, negatively impacting lesion diagnostics. It is crucial to identify methods that ensure consistent diagnostic accuracy and maintain image quality. Deep progressive learning (DPL) algorithm, an Artificial Intelligence(AI)-based PET reconstruction technique, offers a promising solution. 150 patients underwent 18F-FDG PET/CT scans and were categorized by BMI into underweight, normal, and overweight groups. PET images were reconstructed using both OSEM and DPL and their image quality was assessed both visually and quantitatively. Visual assessment employed a 5-point Likert scale to evaluate overall score, image sharpness, image noise, and diagnostic confidence. Quantitative assessment parameters included the background liver image-uniformity-index ( IUI_Liver ) and signal-to-noise ratio ( SNR_Liver ). Additionally, 466 identifiable lesions were categorized by size: sub-centimeter and larger. We compared maximum standard uptake value ( SUV_max^Lesion ), signal-to-background ratio ( SBR_Lesion ), SNR_Lesion , contrast-to-background ratio ( CBR_Lesion ), and contrast-to-noise ratio ( CNR_Lesion ) of these lesions to evaluate the diagnostic performance of the DPL and OSEM algorithms across different lesion sizes and BMI categories. DPL produced superior PET image quality compared to OSEM across all BMI groups. The visual quality of DPL showed a slight decline with increasing BMI, while OSEM exhibited a more significant decline. DPL maintained a stable SNR_Liver across BMI increases, whereas OSEM exhibited increased noise. In the DPL group, quantitative image quality for overweight patients matched that of normal patients with minimal variance from underweight patients. In contrast, OSEM demonstrated significant declines in quantitative image quality with rising BMI. DPL yielded significantly higher contrast ( SBR_Lesion , SNR_Lesion , CBR_Lesion , CNR_Lesion ) and SUV_max^Lesion than OSEM for all lesions across all BMI categories. DPL consistently provided superior image quality and lesion diagnostic performance compared to OSEM across all BMI categories in 18F-FDG PET/CT scans. Therefore, we recommend using the DPL algorithm for 18F-FDG PET/CT image reconstruction in all BMI patients.

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 (SUV max ), 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 SUV max , 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.

BACKGROUNDImproving and predicting tumor response to immunotherapy remains challenging. Combination therapy with a transforming growth factor-β receptor (TGF-βR) inhibitor that targets cancer-associated fibroblasts (CAFs) is promising for the enhancement of efficacy of immunotherapies. However, the effect of this approach in clinical trials is limited, requiring in vivo methods to better assess tumor responses to combination therapy.METHODSWe measured CAFs in vivo using the 68Ga-labeled fibroblast activation protein inhibitor-04 (68Ga-FAPI-04) for PET/CT imaging to guide the combination of TGF-β inhibition and immunotherapy. One hundred thirty-one patients with metastatic colorectal cancer (CRC) underwent 68Ga-FAPI and 18F-fluorodeoxyglucose (18F-FDG) PET/CT imaging. The relationship between uptake of 68Ga-FAPI and tumor immunity was analyzed in patients. Mouse cohorts of metastatic CRC were treated with the TGF-βR inhibitor combined with KN046, which blocks programmed death ligand 1 (PD-L1) and CTLA-4, followed by 68Ga-FAPI and 18F-FDG micro-PET/CT imaging to assess tumor responses.RESULTSPatients with metastatic CRC demonstrated high uptake rates of 68Ga-FAPI, along with suppressive tumor immunity and poor prognosis. The TGF-βR inhibitor enhanced tumor-infiltrating T cells and significantly sensitized metastatic CRC to KN046. 68Ga-FAPI PET/CT imaging accurately monitored the dynamic changes of CAFs and tumor response to combined the TGF-βR inhibitor with immunotherapy.CONCLUSION68Ga-FAPI PET/CT imaging is powerful in assessing tumor immunity and the response to immunotherapy in metastatic CRC. This study supports future clinical application of 68Ga-FAPI PET/CT to guide precise TGF-β inhibition plus immunotherapy in CRC patients, recommending 68Ga-FAPI and 18F-FDG dual PET/CT for CRC management.TRIAL REGISTRATIONCFFSTS Trial, ChiCTR2100053984, Chinese Clinical Trial Registry.FUNDINGNational Natural Science Foundation of China (82072695, 32270767, 82272035, 81972260).

Interventional therapy is very important in current clinical applications. However, the lack of quantifiable embolic agents to affect the therapeutic effects negatively. In the present study, we sought to prepare a novel embolic agent, 99mTc-Konjac glucoman/Poly(lactide-co-glycolide)@Polyethyleneimine@Diethylenetriaminepentaacetic acid (KGM/PLGA@PEI@DTPA)microspheres, which can be located and quantified noninvasively to further evaluate its biological effects in animal models. The KGM/PLGA microspheres were prepared with water/oil/water double emulsion-solvent evaporation. Subsequently, the surface modification was performed with PEI and DTPA as a bifunctional chelator to label the microspheres with 99mTc. The in vitro stability of 99mTc-KGM/PLGA@PEI@DTPA was determined through instant thin layer chromatography, and the in vitro cytotoxicity of KGM/PLGA@-PEI@DTPA was evaluated with CCK-8 assays. The location and quantitative calculation of 99mTc-KGM/PLGA@-PEI@DTPA in vivo were evaluated in rabbits through SPECT/CT, and the in vivo toxicity was assayed in rabbits.The microspheres showed no toxicity in vitro and in vivo, andthe diameter of microsphere was about 82.5 +/- 14.5 mu m (range 60-120 mu m). The 99mTc-KGM/PLGA@PEI@DTPA was stable in phosphate-buffered saline and 50% fetal bovine serum within 6 h. The Single-photon emission computed tomography/computed tomography(SPECT/CT) imaging and biodistribution results showed that microspheres were mainly distributed in the liver, kidney, and bladder, and excreted through the urinary system. And the dose of microspheres embolizing in the liver was approximately 2.54 mg, 50.79% of the total injection, an estimate calculated according to the gamma ray emission from 99mTc in SPECT/CT.Hence, the 99mTc-KGM/PLGA@PEI@DTPA may be as a quantitative embolic agent and provide potential clinical value for interventional therapy.

Abstract Background MRI or CT-based RECIST is the current clinical standard for evaluating the efficacy of radiation therapy. Typically, several months are required after treatment to determine the extent of tumor control, with the possibility of malignant progression. In this study, we synthesize a novel nanoscale 18F-AlF-labeled FAPI radiotracer and assess its capacity to monitor instant radiotherapy response by PET/CT in tumor xenografted mouse models and a patient with sarcoma, utilizing 18F-FDG, 68Ga-FAPI PET/CT imaging, and MRI imaging as controls. Results Current research has generated an 18F-AlF-FAPI radiotracer with an unique pharmacological architecture. The radiotracer 18F-AlF-FAPI was a colloid with a diameter of 100–200 nm. The diameter of AlF clusters ranges between 10 and 80 nm, and the majority of 18F-AlF-FAPI molecules comprise between 2 and 5 AlF clusters. In comparison to 68Ga-FAPI, 18F-AlF-FAPI has a distinct excretion mechanism and a significantly smaller background signal, resulting in a higher tumor-to-background ratio (TBR). After a single dose of 10 Gy of non-lethal X-ray therapy, the xenografted tumor in the mouse exhibited a high uptake of 18F-AlF-FAPI, followed by tumor progression. In a patient with sarcoma who underwent complete carbon ion radiotherapy (CIRT) treatment and tumor regression, tumor uptake of 18F-AlF-FAPI was barely detectable, highlighting the potential of 18F-AlF-FAPI probe-based PET/CT for visualization of quick response to CIRT radiotherapy within one month. Additionally, the tumor site in this case was around 1,4 times larger in 18F-AlF-FAPI PET imaging than in MRI and 18F-FDG PET/CT imaging. The physician finally expanded the target volume delineation for CIRT treatment based on the positive region and heterogeneity, indicating the potential of 18F-AlF-FAPI nanotracer in target volume delineation. Conclusions In PET/CT imaging, the novel 18F-AlF-FAPI nanotracer had a higher TBR and a lower background than 68Ga-FAPI due to its distinct formation. 18F-AlF-FAPI uptake was found to be favorably linked with tumor progression in tumor-xenografted mice and sarcoma patients. Compared to 18F-FDG, 68Ga-FAPI PET/CT imaging, and MRI imaging, 18F-AlF-FAPI PET/CT imaging revealed greater potential for identifying the rapid response of sarcoma to radiotherapy within one month. 18F-AlF-FAPI PET/CT imaging has also shown potential in radiotherapy target volume delineation.

Background: Apart from invasive pathological examination, there is no effective method to differentiate breast diffuse large B-cell lymphoma (DLBCL) from breast invasive ductal carcinoma (IDC). In this study, we aimed to develop and validate an effective deep learning radiomics model to discriminate between DLBCL and IDC. Methods: A total of 324 breast nodules from 236 patients with baseline18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) were retrospectively analyzed. After grouping breast DLBCL and breast IDC patients, external and internal datasets were divided according to the data collected by different centers. Preprocessing was then used to process the original PET/CT images and an attention-based aggregate convolutional neural network (AACNN) model was designed. The AACNN model was trained using patches of CT or PET tumor images and optimized with an improved loss function. The final ensemble predictive model was built using distance weight voting. Finally, the model performance was evaluated and statistically verified.Results: A total of 249 breast nodules from Fudan University Shanghai Cancer Center (FUSCC) and 75 breast nodules from Shanghai Proton and Heavy Ion Center (SPHIC) were selected as internal and external datasets, respectively. On the internal testing, our method yielded an area under the curve (AUC), accuracy (ACC), sensitivity (SEN), specificity (SPE), positive predictive value (PPV), negative predictive value (NPV), and harmonic mean of precision and sensitivity (F1) of 0.886, 83.0%, 80.9%, 85.0%, 84.8%, 81.2%, and 0.828, respectively. Meanwhile on the external testing, the results were 0.788, 71.6%, 61.4%, 84.7%, 84.0%, 62.6%, and 0.709, respectively.Conclusions: Our study outlines a deep learning radiomics method which can automatically, noninvasively, and accurately differentiate breast DLBCL from breast IDC, which will be more in line with the needs and strategies of precision medicine, individualized diagnosis, and treatment.

The bone microenvironment provides a "barrier" for bone tumors to resist clinical chemoradiotherapy, implying that molecules targeting tumor cells alone cannot effectively target bone tumor cells. One restriction of using nanosystems in the treatment of bone tumors is bone tumor cell-targeting. In this study, a novel chemophotothermal combined therapy (CPT) bone tumor cell-targeting nanosystem was designed. A bone tumor cell-targeting peptide (BTTP) was covalently attached to the surface of the nanosystem. The nanosystem was constructed by hybridization of a core Mn-Co metal-organic framework and polydopamine as the shell (TM@P). The TM@P/DOX nanosystem could be first targeted to the bone damage interface by the bone-targeting peptide octapolyaspartic acid (D8) of BTTP. Then the KCQGWI-GQPGCK polypeptide fragment of BTTP could be cut off by matrix metalloproteinases (MMPs) secreted by bone tumors, and finally guided specifically the nanosystem into bone tumor cells by cell penetrating peptides (R-8) of BTTP. Doxorubicin (DOX) was loaded onto the TM@P surface (TM@P/DOX). The nanosystem targeted bone tumor cells well in vivo and enhanced the contrast of bone tumor (MRI). Finally, the TM@P/DOX nanosystem-mediated CPT effectively inhibited bone tumor growth and osteolysis. This study provides an effective new approach for the treatment of malignant bone tumors.

Resistance to chemotherapy is a key factor affecting Non-small cell lung cancer spinal metastasis (NSCLC-SM) treatment efficiency. In this study, Osteopontin (OPN), an intracellular and a secreted glycoprotein, showed overexpression in NSCLC-SM. Further studies demonstrated that OPN promoted chemoresistance by activating mTORC2/AKT/NF-kappa B/MDR1 signaling via interaction with integrin alpha v beta 3. Subsequently, it was confirmed that a specific inhibitor of OPN/alpha v beta 3, the pentapeptide Gly-Arg-Gly-Asp-Ser (TFA), targeted NSCLC-SM and promoted chemosensitivity by competitively blocking the OPN/alpha v beta 3 interaction and by inhibiting the downstream signaling. Therefore, a TFA-modified and cisplatin (DDP)-loaded hollow MnO2 structure (H-MnO2/DDP(Cy)-TFA nanocapsules) was fabricated in the present study. The H-MnO2/DDP(Cy)-TFA targeted OPN, exhibited responses to the tumor microenvironment, and demonstrated high drug loading and controlled release. In a NSCLC-SM mouse model, H-MnO2/DDP(Cy)-TFA enhanced chemosensitivity and suppressed tumor progression via combination effect of targeted inhibition of OPN and controlled release of DDP. Collectively, the present study elucidated the mechanism underlying OPN-mediated NSCLC chemoresistance and a nano-drug delivery platform was developed as a new therapeutic strategy for precisely targeting NSCLC-SM and for enhancing chemosensitivity.

High myopia is a leading cause of blindness worldwide. Myopia progression may lead to pathological changes of lens and affect the outcome of lens surgery, but the underlying mechanism remains unclear. Here, we find an increased lens size in highly myopic eyes associated with up-regulation of β/γ-crystallin expressions. Similar findings are replicated in two independent mouse models of high myopia. Mechanistic studies show that the transcription factor MAF plays an essential role in up-regulating β/γ-crystallins in high myopia, by direct activation of the crystallin gene promoters and by activation of TGF-β1-Smad signaling. Our results establish lens morphological and molecular changes as a characteristic feature of high myopia, and point to the dysregulation of the MAF-TGF-β1-crystallin axis as an underlying mechanism, providing an insight for therapeutic interventions.

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@19 F-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@19 F-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.

BackgroundIn 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.MethodsBrain 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).FindingsThe 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 < 0.05) T1-weighted intensity enhancement in the ipsilateral hippocampus of chronic kainite models than the control probe without LRP1 specificity.InterpretationThe expression of LRP1 is up-regulated in vascular endothelium, activated glia in both DRE patients and kainate models. LRP1-targeted imaging strategy may provide an alternative strategy to define the "concealed" epileptic foci by overcoming the intact BBB.FundingThis work was supported by the National Natural Science Foundation, Shanghai Science and Technology Committee, Shanghai Municipal Science and Technology, Shanghai Municipal Health and Family Planning Commission and the National Postdoctoral Program for Innovative Talents.

19F MRI has been paid great attention because of its higher signal-to-noise ratio and larger chemical shift than 1H MRI. However, the low 19F content and sensitivity of environment limit its development in clinic. Herein, considering the large surface area and abundant metal active sites of metal organic framework (MOF) nanoparticles, we fabricated Zr-based MOF nanoparticles (UiO-66-F NPs) with an organic ligand of tetrafluoro-terephthalic acid (F4PTA) as a pH-sensitive 19F MRI contrast agent, which remained stable in a neutral condition, but could release free F4PTA in an acidic condition to enhance 19F MRI signal. As a proof of concept, UiO-66-F NPs-based contrast agent could turn on the 19F MRI signal in an acidic tumor micro-environment. The results provide an alternative strategy for the design of tumor micro-environment responsive 19F MRI contrast agents.

A pH- and GSH-responsive 1H/19F dual-mode magnetic resonance imaging contrast agent (MRI CA) was constructed by incorporating MnOx into Zr-based MOF nanoparticles (MnOx/UiO-66-F/PPEG NPs) with an organic ligand of tetrafluoro-terephthalic acid (F4PTA). Under a weak acidic tumor micro-environment, MnOx/UiO-66-F/PPEG NPs would collapse to release MnOx and free F4PTA. Due to the released free F4PTA, 19F MRI signal was enhanced. Meanwhile, GSH, which is overexpressed in a tumor micro-environment, reduced MnOx to divalent manganese ions and improved the T1-weighted MR imaging capability. As a proof of concept, MnOx/UiO-66-F/PPEG NPs was favorable for dual 1H/19F MRI with a high signal-to-noise ratio in vivo.

A biodegradable gadolinium-doped mesoporous bismuth-based nanomaterial is used to diagnose kidneys with dysfunction accurately via magnetic resonance imaging in vivo.