Pub Date : 2026-02-02DOI: 10.1038/s44303-026-00137-y
I Jolanda M de Vries
{"title":"Imaging immune responses: visualizing immunity from molecules to medicine.","authors":"I Jolanda M de Vries","doi":"10.1038/s44303-026-00137-y","DOIUrl":"10.1038/s44303-026-00137-y","url":null,"abstract":"","PeriodicalId":501709,"journal":{"name":"npj Imaging","volume":"4 1","pages":"6"},"PeriodicalIF":0.0,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12864914/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146109363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-02DOI: 10.1038/s44303-026-00138-x
Chunfang A Xia, Hsiu-Ming Tsai, Sandra Diaz Garcia, Shuanglong Liu, Alessandra Matzeu, Mani Salarian, Wouter Bruinzeel, Anna K Szardenings
Parkinson's disease (PD) is characterized by alpha-synuclein (α-syn) aggregation, dopaminergic (DA) neuron loss, and neuroinflammation. Synucleinopathy, the α-syn-related pathology, is the central to the pathogenetic processes observed in the brains of patients with PD, dementia with Lewy bodies (DLB), and multiple system atrophy (MSA). We are seeking an animal model with synucleinopathy that can comprehensively replicate these pathologies and adhere to suitable timeframes for preclinical research for positron emission tomography (PET) imaging studies. Adeno-associated virus (AAV) carrying the mutated human α-syn gene and S87N α-syn preformed fibrils (PFF) were co-injected into the left substantia nigra (SN) of mouse brains. Immunohistochemistry (IHC) and PET/CT imaging were performed at different time points to detect the key pathologies in the brain. This model resulted in accelerated α-syn pathology, detectable as early as two weeks post-injection, alongside DA neuron loss, microglial activation, reduced synaptic density, and impaired mitochondrial function within five weeks. Pathology remained spatially localized. In summary, this AAV/PFF hybrid model offers a rapid, region-specific platform for studying synucleinopathies such as PD, as well as for evaluating PET ligands for disease diagnosis and monitoring.
{"title":"Accelerated and localized synucleinopathy in a hybrid mouse model: implications for positron emission tomography studies.","authors":"Chunfang A Xia, Hsiu-Ming Tsai, Sandra Diaz Garcia, Shuanglong Liu, Alessandra Matzeu, Mani Salarian, Wouter Bruinzeel, Anna K Szardenings","doi":"10.1038/s44303-026-00138-x","DOIUrl":"10.1038/s44303-026-00138-x","url":null,"abstract":"<p><p>Parkinson's disease (PD) is characterized by alpha-synuclein (α-syn) aggregation, dopaminergic (DA) neuron loss, and neuroinflammation. Synucleinopathy, the α-syn-related pathology, is the central to the pathogenetic processes observed in the brains of patients with PD, dementia with Lewy bodies (DLB), and multiple system atrophy (MSA). We are seeking an animal model with synucleinopathy that can comprehensively replicate these pathologies and adhere to suitable timeframes for preclinical research for positron emission tomography (PET) imaging studies. Adeno-associated virus (AAV) carrying the mutated human α-syn gene and S87N α-syn preformed fibrils (PFF) were co-injected into the left substantia nigra (SN) of mouse brains. Immunohistochemistry (IHC) and PET/CT imaging were performed at different time points to detect the key pathologies in the brain. This model resulted in accelerated α-syn pathology, detectable as early as two weeks post-injection, alongside DA neuron loss, microglial activation, reduced synaptic density, and impaired mitochondrial function within five weeks. Pathology remained spatially localized. In summary, this AAV/PFF hybrid model offers a rapid, region-specific platform for studying synucleinopathies such as PD, as well as for evaluating PET ligands for disease diagnosis and monitoring.</p>","PeriodicalId":501709,"journal":{"name":"npj Imaging","volume":"4 1","pages":"7"},"PeriodicalIF":0.0,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12864980/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146109424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-28DOI: 10.1038/s44303-025-00134-7
Eva Remlova, Alexander Jessernig, Marcus Bammel, Daniil Nozdriukhin, Yi Chen, Oscar Cipolato, Xosé Luís Deán-Ben, Inge K Herrmann, Daniel Razansky
Gold nanoparticles (AuNPs) absorbing light in the near-infrared (NIR) range offer unparalleled benefits for both optoacoustic (OA) imaging and photothermal therapy (PTT), stemming from their ability to transform optical energy into heat. These unique theranostic capabilities are further complemented by the high sensitivity of OA signals to temperature variations. However, AuNPs typically experience rapid photodegradation when exposed to high laser intensities, which hinders their efficient monitoring with OA. To address this critical limitation, we synthesized silica-coated gold nanorods (AuNRs) featuring enhanced photostability and an absorption peak in the second NIR window (NIR-II, 1064 nm) for optimal tissue penetration. Their comprehensive evaluation under exposure to nanosecond-pulsed and continuous-wave (CW) radiation revealed that the synthesized AuNRs are photostable under laser energy densities required for efficient therapy under OA imaging guidance, which was confirmed with electron microscopy images. Real-time volumetric OA mapping of PTT-induced temperature variations was verified using simultaneous thermal camera readings, whilst post-mortem experiments in mice corroborated the viability of this theranostic approach in deep biological tissues.
金纳米颗粒(AuNPs)吸收近红外(NIR)范围内的光,由于其将光能转化为热能的能力,为光声(OA)成像和光热治疗(PTT)提供了无与伦比的好处。这些独特的治疗能力进一步补充了OA信号对温度变化的高灵敏度。然而,当暴露在高激光强度下时,aunp通常会经历快速的光降解,这阻碍了OA对其的有效监测。为了解决这一关键限制,我们合成了硅包覆金纳米棒(aunr),具有增强的光稳定性和在第二个近红外窗口(NIR- ii, 1064 nm)的吸收峰,以实现最佳的组织穿透。在纳秒脉冲和连续波(CW)辐射下的综合评价表明,在OA成像引导下,合成的aunr在有效治疗所需的激光能量密度下具有光稳定性,这一点得到了电镜图像的证实。同时使用热像仪读数验证了ptt诱导的温度变化的实时体积OA映射,而小鼠的死后实验证实了这种治疗方法在深部生物组织中的可行性。
{"title":"Deep tissue optoacoustic monitoring of photothermal treatments in the NIR-II assisted with silica-coated gold nanorods.","authors":"Eva Remlova, Alexander Jessernig, Marcus Bammel, Daniil Nozdriukhin, Yi Chen, Oscar Cipolato, Xosé Luís Deán-Ben, Inge K Herrmann, Daniel Razansky","doi":"10.1038/s44303-025-00134-7","DOIUrl":"https://doi.org/10.1038/s44303-025-00134-7","url":null,"abstract":"<p><p>Gold nanoparticles (AuNPs) absorbing light in the near-infrared (NIR) range offer unparalleled benefits for both optoacoustic (OA) imaging and photothermal therapy (PTT), stemming from their ability to transform optical energy into heat. These unique theranostic capabilities are further complemented by the high sensitivity of OA signals to temperature variations. However, AuNPs typically experience rapid photodegradation when exposed to high laser intensities, which hinders their efficient monitoring with OA. To address this critical limitation, we synthesized silica-coated gold nanorods (AuNRs) featuring enhanced photostability and an absorption peak in the second NIR window (NIR-II, 1064 nm) for optimal tissue penetration. Their comprehensive evaluation under exposure to nanosecond-pulsed and continuous-wave (CW) radiation revealed that the synthesized AuNRs are photostable under laser energy densities required for efficient therapy under OA imaging guidance, which was confirmed with electron microscopy images. Real-time volumetric OA mapping of PTT-induced temperature variations was verified using simultaneous thermal camera readings, whilst post-mortem experiments in mice corroborated the viability of this theranostic approach in deep biological tissues.</p>","PeriodicalId":501709,"journal":{"name":"npj Imaging","volume":"4 1","pages":"4"},"PeriodicalIF":0.0,"publicationDate":"2026-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12852917/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146095447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-28DOI: 10.1038/s44303-025-00136-5
Amir Reza Sadri, Sepideh Azarianpour, Prathyush Chirra, Sneha Singh, Thomas DeSilvio, Anant Madabhushi, Satish E Viswanath
Computerized features derived from medical imaging have shown great potential in building machine learning models for predicting and prognosticating disease outcomes. However, the performance of such models depends on the robustness of extracted features to institutional and acquisition variability inherent in clinical imaging. To address this challenge, we propose Variability Regularized Feature Selection (VaRFS), a framework that integrates feature variability as a regularization term to identify features that are both discriminable between outcome groups and generalizable across imaging differences. VaRFS employs a novel sparse regularization strategy within the within the Least Absolute Shrinkage and Selection Operator (LASSO) framework, for which we analytically confirm convergence guarantees as well as present an accelerated proximal variant for computational efficiency. We evaluated VaRFS across five clinical applications using over 700 multi-institutional imaging datasets, including disease detection, treatment response characterization, and risk stratification. Compared to three conventional feature selection methods, VaRFS yielded consistently higher classifier AUCs in hold-out validation; balancing reproducibility, sparsity, and discriminability in medical imaging feature selection.
{"title":"Variability Regularized Feature Selection (VaRFS) for optimal identification of robust and discriminable features from medical imaging.","authors":"Amir Reza Sadri, Sepideh Azarianpour, Prathyush Chirra, Sneha Singh, Thomas DeSilvio, Anant Madabhushi, Satish E Viswanath","doi":"10.1038/s44303-025-00136-5","DOIUrl":"10.1038/s44303-025-00136-5","url":null,"abstract":"<p><p>Computerized features derived from medical imaging have shown great potential in building machine learning models for predicting and prognosticating disease outcomes. However, the performance of such models depends on the robustness of extracted features to institutional and acquisition variability inherent in clinical imaging. To address this challenge, we propose Variability Regularized Feature Selection (VaRFS), a framework that integrates feature variability as a regularization term to identify features that are both discriminable between outcome groups and generalizable across imaging differences. VaRFS employs a novel sparse regularization strategy within the within the Least Absolute Shrinkage and Selection Operator (LASSO) framework, for which we analytically confirm convergence guarantees as well as present an accelerated proximal variant for computational efficiency. We evaluated VaRFS across five clinical applications using over 700 multi-institutional imaging datasets, including disease detection, treatment response characterization, and risk stratification. Compared to three conventional feature selection methods, VaRFS yielded consistently higher classifier AUCs in hold-out validation; balancing reproducibility, sparsity, and discriminability in medical imaging feature selection.</p>","PeriodicalId":501709,"journal":{"name":"npj Imaging","volume":"4 1","pages":"5"},"PeriodicalIF":0.0,"publicationDate":"2026-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12852897/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146095446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-07DOI: 10.1038/s44303-025-00132-9
Daniel R Woldring, Theodore Belecciu, Logan R Garland, Andrea Amalfitano, Erik M Shapiro
Organic anion transporting polypeptides (OATPs) are hepatic membrane transporters responsible for the uptake of numerous endogenous compounds and drugs. Among these, OATP1B1 and OATP1B3 in humans, and their orthologs in other species, mediate the cellular uptake of clinically approved hepatospecific MRI contrast agents, rendering them suitable candidates for use as MRI reporter proteins. This review examines the structural biology, evolutionary divergence, and transport mechanisms of hepatic OATPs, with a focus on their capacity to serve as genetically encoded imaging reporters. We survey the uptake and imaging characteristics of clinically available and experimental contrast agents in species-specific contexts and detail how hepatic OATPs have been leveraged in preclinical models for tracking engineered cells in oncology, regenerative medicine, and immunotherapy. Special attention is given to the pioneering studies that established OATP1A1 and OATP1B3 as MRI reporter proteins, the challenges related to contrast dose and imaging timing, and the emerging solutions such as dual-reporter systems and dynamic imaging protocols. Compared to traditional labeling strategies like iron oxide nanoparticles, OATP-based reporters enable positive contrast on T1-weighted MRI, avoid signal ambiguity, and permit multimodal imaging using clinically approved probes. The integration of hepatic OATPs as MRI reporter proteins offers a translationally feasible platform for non-invasive, longitudinal imaging of therapeutic cells in clinical trials and medicine. This technology has the potential to improve safety, efficacy, and mechanistic understanding across a wide array of biomedical applications.
{"title":"Hepatic organic anion transporting polypeptides (OATPs) as MRI reporter proteins.","authors":"Daniel R Woldring, Theodore Belecciu, Logan R Garland, Andrea Amalfitano, Erik M Shapiro","doi":"10.1038/s44303-025-00132-9","DOIUrl":"10.1038/s44303-025-00132-9","url":null,"abstract":"<p><p>Organic anion transporting polypeptides (OATPs) are hepatic membrane transporters responsible for the uptake of numerous endogenous compounds and drugs. Among these, OATP1B1 and OATP1B3 in humans, and their orthologs in other species, mediate the cellular uptake of clinically approved hepatospecific MRI contrast agents, rendering them suitable candidates for use as MRI reporter proteins. This review examines the structural biology, evolutionary divergence, and transport mechanisms of hepatic OATPs, with a focus on their capacity to serve as genetically encoded imaging reporters. We survey the uptake and imaging characteristics of clinically available and experimental contrast agents in species-specific contexts and detail how hepatic OATPs have been leveraged in preclinical models for tracking engineered cells in oncology, regenerative medicine, and immunotherapy. Special attention is given to the pioneering studies that established OATP1A1 and OATP1B3 as MRI reporter proteins, the challenges related to contrast dose and imaging timing, and the emerging solutions such as dual-reporter systems and dynamic imaging protocols. Compared to traditional labeling strategies like iron oxide nanoparticles, OATP-based reporters enable positive contrast on T1-weighted MRI, avoid signal ambiguity, and permit multimodal imaging using clinically approved probes. The integration of hepatic OATPs as MRI reporter proteins offers a translationally feasible platform for non-invasive, longitudinal imaging of therapeutic cells in clinical trials and medicine. This technology has the potential to improve safety, efficacy, and mechanistic understanding across a wide array of biomedical applications.</p>","PeriodicalId":501709,"journal":{"name":"npj Imaging","volume":"4 1","pages":"3"},"PeriodicalIF":0.0,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12780193/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145919677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-06DOI: 10.1038/s44303-025-00133-8
Cécile Philippe, Jonathan Cotton, Gregory D Bowden, Simone Pöschel, Philipp Knopf, Barbara Schörg, Irene Gonzalez-Menendez, Dominik Sonanini, Lukas Flatz, Martin Allen-Auerbach, Caius G Radu, Johannes Czernin, Leticia Quintanilla-Martinez, Marcus Hacker, Bernd J Pichler, Andreas Maurer, Manfred Kneilling
Efficient application of immunotherapy necessitates advanced whole-body imaging techniques to monitor sites of immune cell activation. Deoxycytidine kinase (dCK), a key enzyme in the deoxynucleotide salvage pathway, is upregulated in proliferating immune cells and can be targeted by the radiotracers [18F]FAC (preclinical) and [18F]CFA (clinical), allowing for noninvasive monitoring of immune activation in lymphatic organs via positron emission tomography (PET). In this study, we aimed to assess the efficacy of [18F]FAC in detecting immune activation upon immune checkpoint inhibitor therapy (CIT). In vitro, activated T cells and macrophages exhibited significantly higher [18F]FAC uptake compared to their naïve counterparts. In vivo, preclinical [18F]FAC-PET/MRI revealed a CIT-induced significant increase in [18F]FAC uptake in tumor-draining lymph nodes (TDLNs) compared to contralateral lymph nodes, independent of tumor responsiveness. This phenomenon was absent in TDLNs of sham-treated experimental mice. Ex vivo cell sorting further confirmed elevated [18F]FAC uptake in T cells from TDLNs following CIT. Consistently, [18F]CFA-PET/CT imaging in metastatic melanoma patients demonstrated CIT-induced enhanced regional LN uptake. Together, these findings establish a strong correlation between CIT-induced immune activation and [18F]FAC/[18F]CFA uptake, underscoring the critical role of TDLNs in cancer immuotherapy. The radiotracers [18F]FAC and [18F]CFA provide valuable tools for noninvasive monitoring of immune cell activation, potentially unveiling tumor-microenvironment-related resistance mechanisms and advancing the utility of PET imaging in immunotherapy monitoring and patient stratification.
免疫治疗的有效应用需要先进的全身成像技术来监测免疫细胞活化的部位。脱氧胞苷激酶(dCK)是脱氧核苷酸挽救途径中的关键酶,在增殖的免疫细胞中表达上调,可以被放射性示踪剂[18F]FAC(临床前)和[18F]CFA(临床)靶向,从而通过正电子发射断层扫描(PET)对淋巴器官的免疫激活进行无创监测。在本研究中,我们旨在评估[18F]FAC在检测免疫检查点抑制剂治疗(CIT)免疫激活方面的功效。在体外,活化的T细胞和巨噬细胞与naïve细胞相比,表现出明显更高的[18F]FAC摄取。在体内,临床前[18F]FAC- pet /MRI显示,与对侧淋巴结相比,ctc诱导的肿瘤引流淋巴结(tdln)中[18F]FAC摄取显著增加,与肿瘤反应性无关。这种现象在假药小鼠的tdln中不存在。离体细胞分选进一步证实了[18F] CIT后TDLNs T细胞中FAC摄取升高。与此一致的是,[18F]转移性黑色素瘤患者的CFA-PET/CT成像显示CIT诱导的局部LN摄取增强。总之,这些发现建立了ctc诱导的免疫激活与[18F]FAC/[18F]CFA摄取之间的强相关性,强调了tdln在癌症免疫治疗中的关键作用。放射性示踪剂[18F]FAC和[18F]CFA为无创监测免疫细胞活化提供了有价值的工具,有可能揭示肿瘤微环境相关的耐药机制,并推进PET成像在免疫治疗监测和患者分层中的应用。
{"title":"Noninvasive in vivo deoxycytidine kinase (dCK)-PET identifies tumor-draining lymph nodes upon immune checkpoint inhibitor therapy.","authors":"Cécile Philippe, Jonathan Cotton, Gregory D Bowden, Simone Pöschel, Philipp Knopf, Barbara Schörg, Irene Gonzalez-Menendez, Dominik Sonanini, Lukas Flatz, Martin Allen-Auerbach, Caius G Radu, Johannes Czernin, Leticia Quintanilla-Martinez, Marcus Hacker, Bernd J Pichler, Andreas Maurer, Manfred Kneilling","doi":"10.1038/s44303-025-00133-8","DOIUrl":"10.1038/s44303-025-00133-8","url":null,"abstract":"<p><p>Efficient application of immunotherapy necessitates advanced whole-body imaging techniques to monitor sites of immune cell activation. Deoxycytidine kinase (dCK), a key enzyme in the deoxynucleotide salvage pathway, is upregulated in proliferating immune cells and can be targeted by the radiotracers [<sup>18</sup>F]FAC (preclinical) and [<sup>18</sup>F]CFA (clinical), allowing for noninvasive monitoring of immune activation in lymphatic organs via positron emission tomography (PET). In this study, we aimed to assess the efficacy of [<sup>18</sup>F]FAC in detecting immune activation upon immune checkpoint inhibitor therapy (CIT). In vitro, activated T cells and macrophages exhibited significantly higher [<sup>18</sup>F]FAC uptake compared to their naïve counterparts. In vivo, preclinical [<sup>18</sup>F]FAC-PET/MRI revealed a CIT-induced significant increase in [<sup>18</sup>F]FAC uptake in tumor-draining lymph nodes (TDLNs) compared to contralateral lymph nodes, independent of tumor responsiveness. This phenomenon was absent in TDLNs of sham-treated experimental mice. Ex vivo cell sorting further confirmed elevated [<sup>18</sup>F]FAC uptake in T cells from TDLNs following CIT. Consistently, [<sup>18</sup>F]CFA-PET/CT imaging in metastatic melanoma patients demonstrated CIT-induced enhanced regional LN uptake. Together, these findings establish a strong correlation between CIT-induced immune activation and [<sup>18</sup>F]FAC/[<sup>18</sup>F]CFA uptake, underscoring the critical role of TDLNs in cancer immuotherapy. The radiotracers [<sup>18</sup>F]FAC and [<sup>18</sup>F]CFA provide valuable tools for noninvasive monitoring of immune cell activation, potentially unveiling tumor-microenvironment-related resistance mechanisms and advancing the utility of PET imaging in immunotherapy monitoring and patient stratification.</p>","PeriodicalId":501709,"journal":{"name":"npj Imaging","volume":"4 1","pages":"1"},"PeriodicalIF":0.0,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12775488/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145914523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-06DOI: 10.1038/s44303-025-00135-6
Snigdha Sen, Lorna Smith, Lucy Caselton, Joey Clemente, Maxine Tran, Shonit Punwani, David Atkinson, Richard L Hesketh, Eleftheria Panagiotaki
Renal cell carcinomas (RCCs) have multiple subtypes that are difficult to distinguish using imaging alone. This study characterises renal tumour microstructure using diffusion MRI (dMRI) and the Vascular, Extracellular and Restricted Diffusion for Cytometry in Tumours (VERDICT)-MRI framework. Patients were prospectively recruited from the RIM trial (ClinicalTrials.gov: NCT07173140, 20/11/2024). Fourteen patients with 17 renal tumours (including benign and various RCC subtypes) underwent dMRI using nine b-values (0-2500 s/mm²). A three-compartment VERDICT model was fitted with a self-supervised neural network. Compared to simpler dMRI models, VERDICT more accurately captured the diffusion data in tumour and healthy tissue. VERDICT revealed significant differences in intracellular volume fraction between cancerous and normal tissue, and in vascular volume fraction between vascular and non-vascular regions. A feature selection method identified a reduced 4 b-value protocol (b = [70, 150, 1000, 2000]), cutting scan time by over 30 min, enabling more efficient imaging in larger cohorts.
{"title":"Dual deep learning approach for non-invasive renal tumour subtyping with VERDICT-MRI.","authors":"Snigdha Sen, Lorna Smith, Lucy Caselton, Joey Clemente, Maxine Tran, Shonit Punwani, David Atkinson, Richard L Hesketh, Eleftheria Panagiotaki","doi":"10.1038/s44303-025-00135-6","DOIUrl":"10.1038/s44303-025-00135-6","url":null,"abstract":"<p><p>Renal cell carcinomas (RCCs) have multiple subtypes that are difficult to distinguish using imaging alone. This study characterises renal tumour microstructure using diffusion MRI (dMRI) and the Vascular, Extracellular and Restricted Diffusion for Cytometry in Tumours (VERDICT)-MRI framework. Patients were prospectively recruited from the RIM trial (ClinicalTrials.gov: NCT07173140, 20/11/2024). Fourteen patients with 17 renal tumours (including benign and various RCC subtypes) underwent dMRI using nine b-values (0-2500 s/mm²). A three-compartment VERDICT model was fitted with a self-supervised neural network. Compared to simpler dMRI models, VERDICT more accurately captured the diffusion data in tumour and healthy tissue. VERDICT revealed significant differences in intracellular volume fraction between cancerous and normal tissue, and in vascular volume fraction between vascular and non-vascular regions. A feature selection method identified a reduced 4 b-value protocol (b = [70, 150, 1000, 2000]), cutting scan time by over 30 min, enabling more efficient imaging in larger cohorts.</p>","PeriodicalId":501709,"journal":{"name":"npj Imaging","volume":"4 1","pages":"2"},"PeriodicalIF":0.0,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12774943/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145914497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-24DOI: 10.1038/s44303-025-00131-w
Jishizhan Chen
Current biomedical imaging focuses on spatial detail but overlooks time, limiting our understanding of disease progression. There is an unmet need for temporal atlases that align multiscale and multimodal data across defined timepoints, enabling dynamic mapping of pathophysiology. This framework will pave the way for more personalised, time-aware diagnostics and interventions.
{"title":"Towards time-resolved multiscale and multimodal imaging.","authors":"Jishizhan Chen","doi":"10.1038/s44303-025-00131-w","DOIUrl":"10.1038/s44303-025-00131-w","url":null,"abstract":"<p><p>Current biomedical imaging focuses on spatial detail but overlooks time, limiting our understanding of disease progression. There is an unmet need for temporal atlases that align multiscale and multimodal data across defined timepoints, enabling dynamic mapping of pathophysiology. This framework will pave the way for more personalised, time-aware diagnostics and interventions.</p>","PeriodicalId":501709,"journal":{"name":"npj Imaging","volume":"3 1","pages":"67"},"PeriodicalIF":0.0,"publicationDate":"2025-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12739114/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145829477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-22DOI: 10.1038/s44303-025-00130-x
Hagar Shmuely, Michal Rivlin, Or Perlman
Parkinson's disease (PD) diagnosis remains a substantial clinical challenge due to its heterogeneous symptomatology and the absence of reliable early-stage biomarkers. While molecular imaging offers promise, current methods are lengthy or have limited specificity. Here, we combined a rapid molecular MRI acquisition paradigm with deep learning based reconstruction for multi-metabolite quantification of glutamate, mobile proteins, semisolid, and mobile macromolecules in an acute MPTP (1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine) mouse model. The resulting quantitative parameter maps align well with histology and magnetic resonance spectroscopy (MRS) findings. Notably, the semisolid magnetization transfer (MT), amide, and aliphatic relayed nuclear Overhauser effect (rNOE) proton volume fractions emerged as promising PD biomarkers.
{"title":"Quantitative multi-metabolite imaging of Parkinson's disease using AI boosted molecular MRI.","authors":"Hagar Shmuely, Michal Rivlin, Or Perlman","doi":"10.1038/s44303-025-00130-x","DOIUrl":"10.1038/s44303-025-00130-x","url":null,"abstract":"<p><p>Parkinson's disease (PD) diagnosis remains a substantial clinical challenge due to its heterogeneous symptomatology and the absence of reliable early-stage biomarkers. While molecular imaging offers promise, current methods are lengthy or have limited specificity. Here, we combined a rapid molecular MRI acquisition paradigm with deep learning based reconstruction for multi-metabolite quantification of glutamate, mobile proteins, semisolid, and mobile macromolecules in an acute MPTP (1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine) mouse model. The resulting quantitative parameter maps align well with histology and magnetic resonance spectroscopy (MRS) findings. Notably, the semisolid magnetization transfer (MT), amide, and aliphatic relayed nuclear Overhauser effect (rNOE) proton volume fractions emerged as promising PD biomarkers.</p>","PeriodicalId":501709,"journal":{"name":"npj Imaging","volume":"3 1","pages":"66"},"PeriodicalIF":0.0,"publicationDate":"2025-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12722214/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145812604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-10DOI: 10.1038/s44303-025-00128-5
Elizabeth A Germino, Kirstin A Zettlitz, Tyler Watkins, Bao Ying Chen, Deirdre La Placa, Felix B Salazar, Jennifer Chean, Shichang Li, Heather M McGee, Terence M Williams, Anna M Wu
Anti-CD8 immunoPET facilitates non-invasive, whole-body visualization of immune responses, and syngeneic preclinical models are a crucial tool for studying tumor infiltration of T cells in response to cancer therapies. This study characterized longitudinal CD8+ T cell responses in an orthotopic mouse model of breast cancer treated with radiation and anti-CTLA4 by immunohistochemistry and anti-CD8 immunoPET, confirming an early but heterogeneous response induced by combination treatment that is detectable by imaging.
{"title":"<sup>89</sup>Zr-anti-CD8 immunoPET visualizes heterogeneous intratumoral CD8<sup>+</sup> immune responses to treatment with radiation and anti-CTLA4.","authors":"Elizabeth A Germino, Kirstin A Zettlitz, Tyler Watkins, Bao Ying Chen, Deirdre La Placa, Felix B Salazar, Jennifer Chean, Shichang Li, Heather M McGee, Terence M Williams, Anna M Wu","doi":"10.1038/s44303-025-00128-5","DOIUrl":"10.1038/s44303-025-00128-5","url":null,"abstract":"<p><p>Anti-CD8 immunoPET facilitates non-invasive, whole-body visualization of immune responses, and syngeneic preclinical models are a crucial tool for studying tumor infiltration of T cells in response to cancer therapies. This study characterized longitudinal CD8<sup>+</sup> T cell responses in an orthotopic mouse model of breast cancer treated with radiation and anti-CTLA4 by immunohistochemistry and anti-CD8 immunoPET, confirming an early but heterogeneous response induced by combination treatment that is detectable by imaging.</p>","PeriodicalId":501709,"journal":{"name":"npj Imaging","volume":"3 1","pages":"65"},"PeriodicalIF":0.0,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12695897/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145727925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}