Nanoparticle Delivery to Tumours: From EPR and ATR Mechanisms to Clinical Impact.

New insights into active versus passive nanoparticle tumour entry and exit mechanisms are enriching the understanding of tumour-targeted drug delivery. Here, we align the principles of the enhanced permeability and retention (EPR) and active transport and retention (ATR), and outline how their mechanistic features may be employed to improve the performance and clinical impact of cancer nanomedicines.

Aminolysis-mediated single-step surface functionalization of poly (butyl cyanoacrylate) microbubbles for ultrasound molecular imaging.

Molecular ultrasound imaging with actively targeted microbubbles (MB) proved promising in preclinical studies but its clinical translation is limited. To achieve this, it is essential that the actively targeted MB can be produced with high batch-to-batch reproducibility with a controllable and defined number of binding ligands on the surface. In this regard, poly (n-butyl cyanoacrylate) (PBCA)-based polymeric MB have been used for US molecular imaging, however, ligand coupling was mostly done via hydrolysis and carbodiimide chemistry, which is a multi-step procedure with poor reproducibility and low MB yield. Herein, we developed a single-step coupling procedure resulting in high MB yields with minimal batch-to-batch variation. Actively targeted PBCA-MB were generated using an aminolysis protocol, wherein amine-containing cRGD was added to the MB using lithium methoxide as a catalyst. We confirmed the successful conjugation of cRGD on the MB surface, while preserving their structure and acoustic signal. Compared to the conventional hydrolysis protocol, aminolysis resulted in higher MB yields and better reproducibility of coupling efficiency. Optical imaging revealed that under flow conditions, cRGD- and rhodamine-labelled MB, generated by aminolysis, specifically bind to tumor necrosis factor-alpha (TNF-α) activated endothelial cells in vitro. Furthermore, US molecular imaging demonstrated a markedly higher binding of the cRGD-MB than of control MB in TNF-α activated mouse aortas and 4T1 tumors in mice. Thus, using the aminolysis based conjugation approach, important refinements on the production of cRGD-MB could be achieved that will facilitate the production of clinical-scale formulations with excellent binding and ultrasound imaging performance.

Polymeric antibubbles with strong ultrasound imaging capabilities.

Antibubbles are liquid droplets encapsulated by a gas film that have recently been explored for on-demand ultrasound-triggered drug release. However, their ultrasound imaging capabilities are limited by their stiff shells stabilized with silica nanoparticles. Here, we develop polymeric antibubbles that generate greater ultrasound contrast than silica-based antibubbles, while showing better stability than conventional polymeric microbubbles.

Ultrasonic Control of Protein Splicing by Split Inteins.

Utilizing ultrasound as an external stimulus to remotely modulate the activity of proteins is an important aspect of sonopharmacology and establishes the basis for the emerging field of sonogenetics. Here, we describe an ultrasound-responsive protein splicing system that enables spatiotemporal control of split-intein-mediated protein ligation. The system utilizes engineered split inteins that are caged and can be activated by thrombin released from a high molar mass DNA-based carrier under focused ultrasound sonication. This approach represents a general method for controlling the functions of proteins of interest by ultrasound, as demonstrated here by the controlled synthesis of the superfolder green fluorescence protein (GFP) and calcitonin. Furthermore, calcitonin receptor-mediated signal transduction in cells was triggered by this system in vitro without harming cell viability. By expanding the sonogenetic toolbox with protein splicing technologies, this study provides a possible pathway to deploy ultrasound for remotely controlling a variety of protein functions in deep tissue in the future.

Microfluidic formulation, cryoprotection and long-term stability of paclitaxel-loaded π electron-stabilized polymeric micelles.

Controlled manufacturing and long-term stability are key challenges in the development and translation of nanomedicines. This is exemplified by the mRNA-nanoparticle vaccines against COVID-19, which require (ultra-)cold temperatures for storage and shipment. Various cryogenic protocols have been explored to prolong nanomedicine shelf-life. However, freezing typically induces high mechanical stress on nanoparticles, resulting in aggregation or destabilization, thereby limiting their performance and application. Hence, evaluating the impact of freezing and storing on nanoparticle properties already early-on during preclinical development is crucial. In the present study, we used prototypic π electron-stabilized polymeric micelles based on mPEG-b-p(HPMAm-Bz) block copolymers to macro- and microscopically study the effect of different cryoprotective excipients on nanoformulation properties like size and size distribution, as well as on freezing-induced aggregation phenomena via in-situ freezing microscopy. We show that sucrose, unlike trehalose, efficiently cryoprotected paclitaxel-loaded micelles, and we exemplify the impact of formulation composition for efficient cryoprotection. We finally establish microfluidic mixing to formulate paclitaxel-loaded micelles with sucrose as a cryoprotective excipient in a single production step and demonstrate their stability for 6 months at -20 °C. The pharmaceutical properties and preclinical performance (in terms of tolerability and tumor growth inhibition in a patient-derived triple-negative breast cancer xenograft mouse model) of paclitaxel-loaded micelles were successfully cryopreserved. Together, our efforts promote future pharmaceutical development and translation of π electron-stabilized polymeric micelles, and they illustrate the importance of considering manufacturing and storage stability issues early-on during nanomedicine development.

Combining Radiomics and Autoencoders to Distinguish Benign and Malignant Breast Tumors on US Images.

Background US is clinically established for breast imaging, but its diagnostic performance depends on operator experience. Computer-assisted (real-time) image analysis may help in overcoming this limitation. Purpose To develop precise real-time-capable US-based breast tumor categorization by combining classic radiomics and autoencoder-based features from automatically localized lesions. Materials and Methods A total of 1619 B-mode US images of breast tumors were retrospectively analyzed between April 2018 and January 2024. nnU-Net was trained for lesion segmentation. Features were extracted from tumor segments, bounding boxes, and whole images using either classic radiomics, autoencoder, or both. Feature selection was performed to generate radiomics signatures, which were used to train machine learning algorithms for tumor categorization. Models were evaluated using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity and were statistically compared with histopathologically or follow-up-confirmed diagnosis. Results The model was developed on 1191 (mean age, 61 years ± 14 [SD]) female patients and externally validated on 50 (mean age, 55 years ± 15]). The development data set was divided into two parts: testing and training lesion segmentation (419 and 179 examinations) and lesion categorization (503 and 90 examinations). nnU-Net demonstrated precision and reproducibility in lesion segmentation in test set of data set 1 (median Dice score [DS]: 0.90 [IQR, 0.84-0.93]; P = .01) and data set 2 (median DS: 0.89 [IQR, 0.80-0.92]; P = .001). The best model, trained with 23 mixed features from tumor bounding boxes, achieved an AUC of 0.90 (95% CI: 0.83, 0.97), sensitivity of 81% (46 of 57; 95% CI: 70, 91), and specificity of 87% (39 of 45; 95% CI: 77, 87). No evidence of difference was found between model and human readers (AUC = 0.90 [95% CI: 0.83, 0.97] vs 0.83 [95% CI: 0.76, 0.90]; P = .55 and 0.90 vs 0.82 [95% CI: 0.75, 0.90]; P = .45) in tumor classification or between model and histopathologically or follow-up-confirmed diagnosis (AUC = 0.90 [95% CI: 0.83, 0.97] vs 1.00 [95% CI: 1.00,1.00]; P = .10). Conclusion Precise real-time US-based breast tumor categorization was developed by mixing classic radiomics and autoencoder-based features from tumor bounding boxes. ClinicalTrials.gov identifier: NCT04976257 Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Bahl in this issue.

Ultrasound Localization Microscopy Precision of Clinical 3D Ultrasound Systems.

Ultrasound localization microscopy is becoming well established in preclinical applications. For its translation into clinical practice, the localization precision achievable with commercial ultrasound scanners is crucial - especially with volume imaging, which is essential for dealing with out-of-plane motion. Here, we propose an easy-to-perform method to estimate the localization precision of 3D ultrasound scanners. With this method, we evaluated imaging sequences of the Philips Epiq 7 ultrasound device using the X5-1 and the XL14-3 matrix transducers, and also tested different localization methods. For the X5-1 transducer, the best lateral, elevational, and axial precision was 109 µm, 95 µm, and 55 µm for one contrast mode, and 29 µm, 22 µm, and 19 µm for the other. The higher frequency XL14-3 transducer yielded precisions of 17 µm, 38 µm, and 6 µm using the harmonic imaging mode. Although the center of mass was the most robust localization method also often providing the best precision, the localization method has only minor influence on the localization precision compared to the impact by the imaging sequence and transducer. The results show that with one of the imaging modes of the X5-1 transducer, precisions comparable to the XL14-3 transducer can be achieved. However, due to localization precisions worse than 10 µm, reconstruction of the microvasculature at the capillary level will not be possible. These results show the importance to evaluate the localization precision of imaging sequences from different ultrasound transducers or scanners in all directions before using them for in vivo measurements.

Polymeric Microbubble Shell Engineering: Microporosity as a Key Factor to Enhance Ultrasound Imaging and Drug Delivery Performance.

Microbubbles (MB) are widely used as contrast agents for ultrasound (US) imaging and US-enhanced drug delivery. Polymeric MB are highly suitable for these applications because of their acoustic responsiveness, high drug loading capability, and ease of surface functionalization. While many studies have focused on using polymeric MB for diagnostic and therapeutic purposes, relatively little attention has thus far been paid to improving their inherent imaging and drug delivery features. This study here shows that manipulating the polymer chemistry of poly(butyl cyanoacrylate) (PBCA) MB via temporarily mixing the monomer with the monomer-mimetic butyl cyanoacetate (BCC) during the polymerization process improves the drug loading capacity of PBCA MB by more than twofold, and the in vitro and in vivo acoustic responses of PBCA MB by more than tenfold. Computer simulations and physisorption experiments show that BCC manipulates the growth of PBCA polymer chains and creates nanocavities in the MB shell, endowing PBCA MB with greater drug entrapment capability and stronger acoustic properties. Notably, because BCC can be readily and completely removed during MB purification, the resulting formulation does not include any residual reagent beyond the ones already present in current PBCA-based MB products, facilitating the potential translation of next-generation PBCA MB.

Improving MPI and hyperthermia performance of superparamagnetic iron oxide nanoparticles through fractional factorial design of experiments.

Superparamagnetic iron oxide nanoparticles (SPIONs) are widely used for biomedical applications, including magnetic particle imaging (MPI) and magnetic hyperthermia. The co-precipitation method is one of the most common synthetic routes to obtain SPIONs, since it is simple and does not require extreme conditions, such as high temperatures. Despite its prevalence, however, the co-precipitation synthesis presents some challenges, most notably the high batch-to-batch variability, as multiple factors can influence nanoparticle growth. In this study, we utilized a fractional factorial design of experiments to identify key factors influencing SPION growth, properties, and performance in MPI and magnetic hyperthermia, namely Fe3+ content, pH, temperature, stirring, and atmosphere. Notably, our study unveiled secondary interactions, particularly between temperature and Fe3+ content, as well as pH and Fe3+ content, for which simultaneous changes of both parameters promoted greater effects than the sum of each factor effect alone, emphasizing the impact of synergistic effects on SPION growth and performance. These findings provide a deeper understanding of the growth mechanism of SPIONs, reconcile discrepancies in the existing literature, and underscore the importance of characterizing secondary interactions to improve the performance of SPIONs for biomedical applications.

Motivation and success factors in radiological research in Germany - results of a survey by the Methodology and Research Working Group of the German Radiological Society. / Motivation und Erfolgsfaktoren in der radiologischen Forschung in Deutschland ­ Ergebnisse einer Umfrage der AG Methodik und Forschung.

Investigation of motivation and identification of success factors in radiology research in Germany.Using a German online survey (54 questions, period: 3.5 months), demographic aspects, intrinsic and extrinsic success characteristics, as well as personal and organizational success factors were surveyed based on a career success model. The survey results were reported descriptively. The correlations between success factors and success characteristics were examined using linear, binary-logistic, and multinomial regression models.176 people (164 academically active, 10 not academically active) answered the survey. Most participants (80%, 139/174) worked at a university hospital. 32% had privatdozent or professor as their highest academic title (56/173). The researchers' main motivation was intrinsic interest in research (55%, 89/163), followed by a desire to increase their own career opportunities (25%, 41/163). The following were identified as factors for intrinsic success: i) support from department management (estimate=ß=0.26, p<0.001), ii) good work-life balance (ß=0.37, p<0.001), and iii) the willingness to pursue science even after reaching the career goal (ß=0.16, p<0.016). Relevant factors for extrinsic scientific success were mentoring, protected research time, and activities in professional societies.Researchers in German radiology are mainly intrinsically motivated. Factors known from the literature that determine intrinsic and extrinsic scientific success were confirmed in this study. Knowledge of these factors allows targeted systematic support and could thus increase scientific success in German radiology. · Main motivation for German radiology research is intrinsic interest, followed by career opportunities.. · Factors for intrinsic scientific success are good work-life balance and support by department management.. · Factors for extrinsic scientific success are mentoring, activities in professional societies, and protected research time.. · Wegner F, Heinrichs H, Stahlmann K et al. Motivation and success factors in radiological research in Germany - results of a survey by the Methodology and Research Working Group of the German Radiological Society. Fortschr Röntgenstr 2024; DOI 10.1055/a-2350-0023.

Overcoming data scarcity in biomedical imaging with a foundational multi-task model.

Foundational models, pretrained on a large scale, have demonstrated substantial success across non-medical domains. However, training these models typically requires large, comprehensive datasets, which contrasts with the smaller and more specialized datasets common in biomedical imaging. Here we propose a multi-task learning strategy that decouples the number of training tasks from memory requirements. We trained a universal biomedical pretrained model (UMedPT) on a multi-task database including tomographic, microscopic and X-ray images, with various labeling strategies such as classification, segmentation and object detection. The UMedPT foundational model outperformed ImageNet pretraining and previous state-of-the-art models. For classification tasks related to the pretraining database, it maintained its performance with only 1% of the original training data and without fine-tuning. For out-of-domain tasks it required only 50% of the original training data. In an external independent validation, imaging features extracted using UMedPT proved to set a new standard for cross-center transferability.

In vitro and in vivo evaluation of biohybrid tissue-engineered vascular grafts with transformative 1H/19F MRI traceable scaffolds.

Biohybrid tissue-engineered vascular grafts (TEVGs) promise long-term durability due to their ability to adapt to hosts' needs. However, the latter calls for sensitive non-invasive imaging approaches to longitudinally monitor their functionality, integrity, and positioning. Here, we present an imaging approach comprising the labeling of non-degradable and degradable TEVGs' components for their in vitro and in vivo monitoring by hybrid 1H/19F MRI. TEVGs (inner diameter 1.5 mm) consisted of biodegradable poly(lactic-co-glycolic acid) (PLGA) fibers passively incorporating superparamagnetic iron oxide nanoparticles (SPIONs), non-degradable polyvinylidene fluoride scaffolds labeled with highly fluorinated thermoplastic polyurethane (19F-TPU) fibers, a smooth muscle cells containing fibrin blend, and endothelial cells. 1H/19F MRI of TEVGs in bioreactors, and after subcutaneous and infrarenal implantation in rats, revealed that PLGA degradation could be faithfully monitored by the decreasing SPIONs signal. The 19F signal of 19F-TPU remained constant over weeks. PLGA degradation was compensated by cells' collagen and α-smooth-muscle-actin deposition. Interestingly, only TEVGs implanted on the abdominal aorta contained elastin. XTT and histology proved that our imaging markers did not influence extracellular matrix deposition and host immune reaction. This concept of non-invasive longitudinal assessment of cardiovascular implants using 1H/19F MRI might be applicable to various biohybrid tissue-engineered implants, facilitating their clinical translation.

Microbubble-encapsulated Cobalt Nitrato Complexes for Ultrasound-triggerable Nitric Oxide Delivery.

Cobalt complexes exhibit versatile reactivity with nitric oxide (NO), enabling their utilization in applications ranging from homogeneous catalysis to NO-based modulation of biological processes. However, the coordination geometry around the cobalt center is complex, the therapeutic window of NO is narrow, and controlled NO delivery is difficult. To better understand the complexation of cobalt with NO, we prepared four cobalt nitrato complexes and present a structure-property relationship for ultrasound-triggerable NO release. We hypothesized that modulation of the coordination geometry by ligand-modification would improve responsiveness to mechanical stimuli, like ultrasound. To enable eventual therapeutic testing, we here first demonstrate the in vitro tolerability of [Co(ethylenediamine)2(NO)(NO3)](NO3) in A431 epidermoid carcinoma cells and J774A.1 murine macrophages, and we subsequently show successful encapsulation of the complex in poly(butyl cyanoacrylate) microbubbles. These hybrid Co-NO-containing microbubbles may in the future aid in ultrasound imaging-guided treatment of NO-responsive vascular pathologies.

Ultrasound-induced immune responses in tumors: A systematic review and meta-analysis.

Ultrasound is widely used in the diagnosis and therapy of cancer. Tumors can be treated by thermal or mechanical tissue ablation. Furthermore, tumors can be manipulated by hyperthermia, sonodynamic therapy and sonoporation, e.g., by increasing tumor perfusion or the permeability of biological barriers to enhance drug delivery. These treatments induce various immune responses in tumors. However, conflicting data and high heterogeneity between experimental settings make it difficult to generalize the effects of ultrasound on tumor immunity. Therefore, we performed a systematic review to answer the question: "Does ultrasound alter the immune reaction of peripheral solid tumors in humans and animals compared to control conditions without ultrasound?" A systematic literature search was performed in PubMed, EMBASE, and Web of Science and 24,401 potentially relevant publications were identified. Of these, 96 publications were eligible for inclusion in the systematic review. Experiments were performed in humans, rats, and mice and focused on different tumor types, primarily breast and melanoma. We collected data on thermal and non-thermal ultrasound settings, the use of sono-sensitizers or sono-enhancers, and anti-tumor therapies. Six meta-analyses were performed to quantify the effect of ultrasound on tumor infiltration by T cells (cytotoxic, helper, and regulatory T cells) and on blood cytokines (interleukin-6, interferon-γ, tumor necrosis factor-α). We provide robust scientific evidence that ultrasound alters T cell infiltration into tumors and increases blood cytokine concentrations. Furthermore, we identified significant differences in immune cell infiltration based on tumor type, ultrasound settings, and mouse age. Stronger effects were observed using hyperthermia in combination with sono-sensitizers and in young mice. The latter may impair the translational impact of study results as most cancer patients are older. Thus, our results may help refining ultrasound parameters to enhance anti-tumor immune responses for therapeutic use and to minimize immune effects in diagnostic applications.

Riboflavin-targeted polymers improve tolerance of paclitaxel while maintaining therapeutic efficacy.

Active targeting can enhance precision and efficacy of drug delivery systems (DDS) against cancers. Riboflavin (RF) is a promising ligand for active targeting due to its biocompatibility and high riboflavin-receptor expression in cancers. In this study, RF-targeted 4-arm polyethylene glycol (PEG) stars conjugated with Paclitaxel (PTX), named PEG PTX RF, were evaluated as a targeted DDS. In vitro, PEG PTX RF exhibited higher toxicity against tumor cells compared to the non-targeted counterpart (PEG PTX), while free PTX displayed the highest acute toxicity. In vivo, all treatments were similarly effective, but PEG PTX RF-treated tumors showed fewer proliferating cells, pointing to sustained therapy effects. Moreover, PTX-treated animals' body and liver weights were significantly reduced, whereas both remained stable in PEG PTX and PEG PTX RF-treated animals. Overall, our targeted and non-targeted DDS reduced PTX's adverse effects, with RF targeting promoted drug uptake in cancer cells for sustained therapeutic effect.

Histopathological biomarkers for predicting the tumour accumulation of nanomedicines.

The clinical prospects of cancer nanomedicines depend on effective patient stratification. Here we report the identification of predictive biomarkers of the accumulation of nanomedicines in tumour tissue. By using supervised machine learning on data of the accumulation of nanomedicines in tumour models in mice, we identified the densities of blood vessels and of tumour-associated macrophages as key predictive features. On the basis of these two features, we derived a biomarker score correlating with the concentration of liposomal doxorubicin in tumours and validated it in three syngeneic tumour models in immunocompetent mice and in four cell-line-derived and six patient-derived tumour xenografts in mice. The score effectively discriminated tumours according to the accumulation of nanomedicines (high versus low), with an area under the receiver operating characteristic curve of 0.91. Histopathological assessment of 30 tumour specimens from patients and of 28 corresponding primary tumour biopsies confirmed the score's effectiveness in predicting the tumour accumulation of liposomal doxorubicin. Biomarkers of the tumour accumulation of nanomedicines may aid the stratification of patients in clinical trials of cancer nanomedicines.

Pathophysiologic Mapping of Chronic Liver Diseases With Longitudinal Multiparametric MRI in Animal Models.

OBJECTIVES: Chronic liver diseases (CLDs) have diverse etiologies. To better classify CLDs, we explored the ability of longitudinal multiparametric MRI (magnetic resonance imaging) in depicting alterations in liver morphology, inflammation, and hepatocyte and macrophage activity in murine high-fat diet (HFD)- and carbon tetrachloride (CCl 4 )-induced CLD models. MATERIALS AND METHODS: Mice were either untreated, fed an HFD for 24 weeks, or injected with CCl 4 for 8 weeks. Longitudinal multiparametric MRI was performed every 4 weeks using a 7 T MRI scanner, including T1/T2 relaxometry, morphological T1/T2-weighted imaging, and fat-selective imaging. Diffusion-weighted imaging was applied to assess fibrotic remodeling and T1-weighted and T2*-weighted dynamic contrast-enhanced MRI and dynamic susceptibility contrast MRI using gadoxetic acid and ferucarbotran to target hepatocytes and the mononuclear phagocyte system, respectively. Imaging data were associated with histopathological and serological analyses. Principal component analysis and clustering were used to reveal underlying disease patterns. RESULTS: The MRI parameters significantly correlated with histologically confirmed steatosis, fibrosis, and liver damage, with varying importance. No single MRI parameter exclusively correlated with 1 pathophysiological feature, underscoring the necessity for using parameter patterns. Clustering revealed early-stage, model-specific patterns. Although the HFD model exhibited pronounced liver fat content and fibrosis, the CCl 4 model indicated reduced liver fat content and impaired hepatocyte and macrophage function. In both models, MRI biomarkers of inflammation were elevated. CONCLUSIONS: Multiparametric MRI patterns can be assigned to pathophysiological processes and used for murine CLD classification and progression tracking. These MRI biomarker patterns can directly be explored clinically to improve early CLD detection and differentiation and to refine treatments.

A Biodegradable Tissue Adhesive for Post-Extraction Alveolar Bone Regeneration under Ongoing Anticoagulation-A Microstructural Volumetric Analysis in a Rodent Model.

In addition to post-extraction bleeding, pronounced alveolar bone resorption is a very common complication after tooth extraction in patients undergoing anticoagulation therapy. The novel, biodegenerative, polyurethane adhesive VIVO has shown a positive effect on soft tissue regeneration and hemostasis. However, the regenerative potential of VIVO in terms of bone regeneration has not yet been explored. The present rodent study compared the post-extraction bone healing of a collagen sponge (COSP) and VIVO in the context of ongoing anticoagulation therapy. According to a split-mouth design, a total of 178 extraction sockets were generated under rivaroxaban treatment, of which 89 extraction sockets were treated with VIVO and 89 with COSP. Post-extraction bone analysis was conducted via in vivo micro-computed tomography (µCT), scanning electron microscopy (SEM), and energy-dispersive X-ray spectroscopy (EDX) after 5, 10, and 90 days. During the observation time of 90 days, µCT analysis revealed that VIVO and COSP led to significant increases in both bone volume and bone density (p ≤ 0.001). SEM images of the extraction sockets treated with either VIVO or COSP showed bone regeneration in the form of lamellar bone mass. Ratios of Ca/C and Ca/P observed via EDX indicated newly formed bone matrixes in both treatments after 90 days. There were no statistical differences between treatment with VIVO or COSP. The hemostatic agents VIVO and COSP were both able to prevent pronounced bone loss, and both demonstrated a strong positive influence on the bone regeneration of the alveolar ridge post-extraction.

Nanoscale engineering of gold nanostars for enhanced photoacoustic imaging.

Photoacoustic (PA) imaging is a diagnostic modality that combines the high contrast resolution of optical imaging with the high tissue penetration of ultrasound. While certain endogenous chromophores can be visualized via PA imaging, many diagnostic assessments require the administration of external probes. Anisotropic gold nanoparticles are particularly valued as contrast agents, since they produce strong PA signals and do not photobleach. However, the synthesis of anisotropic nanoparticles typically requires cytotoxic reagents, which can hinder their biological application. In this work, we developed new PA probes based on nanostar cores and polymeric shells. These AuNS were obtained through one-pot synthesis with biocompatible Good's buffers, and were subsequently functionalized with polyethylene glycol, chitosan or melanin, three coatings widely used in (pre)clinical research. Notably, the structural features of the nanostar cores strongly affected the PA signal. For instance, despite displaying similar sizes (i.e. 45 nm), AuNS obtained with MOPS buffer generated between 2 and 3-fold greater signal intensities in the region between 700 and 800 nm than nanostars obtained with HEPES and EPPS buffers, and up to 25-fold stronger signals than spherical gold nanoparticles. A point source analytical model demonstrated that AuNS synthesized with MOPS displayed greater absorption coefficients than the other particles, corroborating the stronger PA responses. Furthermore, the AuNS shell not only improved the biocompatibility of the nanoconstructs but also affected their performance, with melanin coating enhancing the signal more than 4-fold, due to its own PA capacity, as demonstrated by both in vitro and ex vivo imaging. Taken together, these results highlight the strengths of gold nanoconstructs as PA probes and offer insights into the design rules for the nanoengineering of new nanodiagnostic agents.