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Purpose: With diaphanoscopic illumination of the eye, the intensity of light entering its interior depends on the transmission properties of the eyewall. Light that passes through the eyewall can cause damage to the retina. Therefore, in this study, the intraocular irradiances are determined at different positions on the retina, directly behind the illuminated eyewall, the opposite eyewall and near the macula of ex-vivo porcine eyes. These irradiances are examined for their dependence on the pressure applied on the eyewall with the illuminating fiber and for the influence of the pigmentation of the eye. Methods: In total 221 ex-vivo porcine eyes were investigated. For transscleral illumination an illumination fiber with a diffusing adapter cap is pressed against the equatorial eyewall. The illumination fiber is pressed onto the eye and the pressure is measured in the anterior chamber. Three different pressures are applied, 23, 78 and 132 mmHg. A detection fiber with diffusing fiber tip is inserted into the eye at the desired position. The eyes were divided in groups with high and less pigmentation to investigate the influence of the pigmentation on the intraocular irradiance. Results: The intraocular irradiances Eintra increases for various increasing applied pressures with the illumination fiber on the eyewall and for various positions inside the eye. With this the irradiances weighted with the photochemical and thermal hazard weighting function, EA-R and EVIR-R, also increases. Differences in Eintra, EA-R and EVIR-R could be found for different pigmented eyes as these values are higher for less pigmented eyes than for strong pigmented ones. Conclusion: The hazard to the retina during diaphanoscopic illumination of the eye depends on how strong the surgeon presses the illumination fiber on the eyewall. Depending on the applied pressure and the measuring position in the eye, the specified limit for the photochemical hazard to the retina is partly exceeded. The pigmentation of the eye also plays a role. The irradiance in less pigmented eyes appears to be higher than in strongly pigmented eyes. Because of this, the surgeon should be able to adjust the intensity of the light source to the color of the patient’s eye.

Background: In recent years, some lens manufacturers have committed to providing lens shape data for some of their lens models. The purpose of this study is to present a strategy for prediction of intraocular lens power and residual refraction based on a pseudophakic model eye containing 5 refractive surfaces and to show its applicability using worked examples. Methods: A pseudophakic model eye with a thin spectacle correction, a thick cornea (radius of curvatures for both surfaces and central thickness) and a thick IOL (either radius of curvatures RLa and RLp for front and back surface or equivalent power PL and Coddington factor CL; and either central thickness LT or edge thickness and optic diameter) was set up. Calculations were performed based on linear Gaussian optics (vergence formulae). Formulae were provided to derive the lens power/shape and the residual equivalent spectacle refraction SEQ. From the lens shape the location of the haptic plane HP, the image sided principal plane of the lens HL, and the ocular magnification OM were extracted. Results: The calculation of a thick intraocular lens and the prediction of residual refraction is presented with reference to 3 working examples: A) lens varied in PL and shifted with its haptic plane keeping the CL constant, B) lens varied in CL and shifted with its haptic plane keeping PL constant, and C) CL and PL of the lens varied keeping its haptic plane position in the eye constant. For each combination of parameters (PL, CL, or haptic plane shift) the parameters influencing SEQ, OM and HL-HP were analysed. Conclusion: Some modern optical biometers currently on the market provide the radii of curvature of both corneal surface and all relevant distances in the eye. With additional data on the lens shape, it would be possible to improve lens power calculations by switching from thin to thick lens models for the cornea and for the lens. This would overcome one of the major drawbacks of current lens power calculation methods.

Precise instrument placement plays a critical role in all interventional procedures, especially percutaneous procedures such as needle biopsies, to achieve successful tumor targeting and increased diagnostic accuracy. C-arm cone beam computed tomography (CBCT) has the potential to precisely visualize the anatomy in direct vicinity of the needle and evaluate the adequacy of needle placement during the intervention, allowing for instantaneous adjustment in case of misplacement. However, even with the most advanced C-arm CBCT devices, it can be difficult to identify the exact needle position on CBCT images due to the strong metal artifacts around the needle. In this study, we proposed a framework for customized trajectory design in CBCT imaging based on Prior Image Constrained Compressed Sensing (PICCS) reconstruction with the goal of reducing metal artifacts in needle-based procedures. We proposed to optimize out-of-plane rotations in three-dimensional (3D) space and minimize projection views while reducing metal artifacts at specific volume of interests (VOIs). An anthropomorphic thorax phantom with a needle inserted inside and two tumor models as the imaging targets were used to validate the proposed approach. The performance of the proposed approach was also evaluated for CBCT imaging under kinematic constraints by simulating some collision areas on the geometry of the C-arm. We compared the result of optimized 3D trajectories using the PICCS algorithm and 20 projections with the result of a circular trajectory with sparse view using PICCS and Feldkamp, Davis, and Kress (FDK), both using 20 projections, and the circular FDK method with 313 projections. For imaging targets 1 and 2, the highest values of structural similarity index measure (SSIM) and universal quality index (UQI) between the reconstructed image from the optimized trajectories and the initial CBCT image at the VOI was calculated 0.7521, 0.7308 and 0.7308, 0.7248 respectively. These results significantly outperformed the FDK method (with 20 and 313 projections) and the PICCS method (20 projections) both using the circular trajectory. Our results showed that the proposed optimized trajectories not only significantly reduce metal artifacts but also suggest a dose reduction for needle-based CBCT interventions, considering the small number of projections used. Furthermore, our results showed that the optimized trajectories are compatible with spatially constrained situations and enable CBCT imaging under kinematic constraints when the standard circular trajectory is not feasible.

Purpose: To test intra-arterial spin labeling (iASL) using active guiding catheters for myocardial perfusion measurements during magnetic resonance (MR)-guided interventions in a pig study. Methods: In this work, a single-loop radiofrequency (RF) coil at the tip of a 6F active coronary catheter was used as a transmit coil for local spin labeling. The transmit magnetic RF field (B1) of the coil and the labeling efficiency were determined, and iASL was tested in two pigs after the catheter was engaged in the aortic root, the ostium of the left coronary artery (LCA) under MR-guidance. The iASL effect was assessed by the signal difference between spin-labeling On and control (spin-labeling OFF) images, and in a cross-correlation between ON/Off states of spin-labeling a binary labeling paradigm. In addition, quantitative myocardial perfusion was calculated from the iASL experiments. Results: The maximum B1 in the vicinity of the catheter coil was 2.1 µT. A strong local labeling effect with a labeling efficiency of 0.45 was achieved with iASL both in vitro and in vivo. In both pigs, the proximal myocardial segments supplied by the LCA showed significant labelling effect up to distances of 60 mm from the aortic root with a relative signal difference of (3.14 ± 2.89)% in the first and (3.50 ± 1.25)% in the second animal. The mean correlation coefficients were R = 0.63 ± 0.22 and 0.42 ± 0.16, respectively. The corresponding computed myocardial perfusion values in this region of the myocardium were similar to those obtained with contrast perfusion methods ((1.2 ± 1.1) mL/min/g and (0.8 ± 0.6) mL/min/g). Conclusion: The proposed iASL method demonstrates the feasibility of selective myocardial perfusion measurements during MR-guided coronary interventions, which with further technical improvements may provide an alternative to exogenous contrast-based perfusion. Due to the invasive nature of the iASL method, it can potentially be used in concert with MRI-guided coronary angioplasty.

Purpose: To implement a fully data driven strategy for identifying outliers in clinical datasets used for formula constant optimisation, in order to achieve proper formula predicted refraction after cataract surgery, and to assess the capabilities of this outlier detection method. Methods: 2 clinical datasets (DS1/DS2: N = 888/403) of eyes treated with a monofocal aspherical intraocular lens (Hoya XY1/Johnson&Johnson Vision Z9003) containing preoperative biometric data, power of the lens implant and postoperative spherical equivalent (SEQ) were transferred to us for formula constant optimisation. Original datasets were used to generate baseline formula constants. A random forest quantile regression algorithm was set up using bootstrap resampling with replacement. Quantile regression trees were grown and the 25% and 75% quantile, and the interquartile range were extracted from SEQ and formula predicted refraction REF for the SRKT, Haigis and Castrop formulae. Fences were defined from the quantiles and data points outside the fences were marked and removed as outliers before recalculating the formula constants. Results: NB = 1000 bootstrap samples were derived from both datasets, and random forest quantile regression trees were grown to model SEQ versus REF and to estimate the median and 25% and 75% quantiles. The fence boundaries were defined as being from 25% quantile - 1.5·IQR to 75% quantile + 1.5·IQR, with data points outside the fence being marked as outliers. In total, for DS1 and DS2, 25/27/32 and 4/5/4 data points were identified as outliers for the SRKT/Haigis/Castrop formulae respectively. The respective root mean squared formula prediction errors for the three formulae were slightly reduced from: 0.4370 dpt;0.4449 dpt/0.3625 dpt;0.4056 dpt/and 0.3376 dpt;0.3532 dpt to: 0.4271 dpt;0.4348 dpt/0.3528 dpt;0.3952 dpt/0.3277 dpt;0.3432 dpt for DS1;DS2. Conclusion: We were able to prove that with random forest quantile regression trees a fully data driven outlier identification strategy acting in the response space is achievable. In a real life scenario this strategy has to be complemented by an outlier identification method acting in the parameter space for a proper qualification of datasets prior to formula constant optimisation.

Absorbed dose heterogeneity in kidney tissues is an important issue in radiopharmaceutical therapy. The effect of absorbed dose heterogeneity in nephrotoxicity is, however, not fully understood yet, which hampers the implementation of treatment optimization by obscuring the interpretation of clinical response data and the selection of optimal treatment options. Although some dosimetry methods have been developed for kidney dosimetry to the level of microscopic renal substructures, the clinical assessment of the microscopic distribution of radiopharmaceuticals in kidney tissues currently remains a challenge. This restricts the anatomical resolution of clinical dosimetry, which hinders a thorough clinical investigation of the impact of absorbed dose heterogeneity. The potential of absorbed dose–response modelling to support individual treatment optimization in radiopharmaceutical therapy is recognized and gaining attraction. However, biophysical modelling is currently underexplored for the kidney, where particular modelling challenges arise from the convolution of a complex functional organization of renal tissues with the function-mediated dose distribution of radiopharmaceuticals. This article reviews and discusses the heterogeneity of absorbed dose distribution in kidney tissues and the absorbed dose–response modelling of nephrotoxicity in radiopharmaceutical therapy. The review focuses mainly on the peptide receptor radionuclide therapy with beta-particle emitting somatostatin analogues, for which the scientific literature reflects over two decades of clinical experience. Additionally, detailed research perspectives are proposed to address various identified challenges to progress in this field.

Introduction: The shape of the energy spectrum is an essential component of any electron beam Monte Carlo model. Due to specialized equipment and the long measurement time for the direct methods for determining the energy spectrum, attractive alternatives are backward spectrum reconstructions from the measured data. One such approach is solving the first-degree Fredholm integral equation with appropriate regularization. It makes it possible to calculate the depth distribution as the sum of the distributions from monoenergetic beams. This study aims to determine the optimal value of the regularization parameter for the problem of determining the spectrum of the electron beam produced by a mobile accelerator used during intraoperative radiotherapy. Material and methods: The Geant4 package was used to generate the distributions of deep doses for monoenergetic beams for two models with different degrees of complexity, i.e. simple (theoretical) and full (for the mobile accelerator). The dose distributions for four different shapes of energy spectrum (for each model) were obtained similarly. They were established as the reference data for further calculations. The Dual Annealing optimization method was used to obtain the reconstructed spectrum. The multiple optimizations that differ by the regularization parameter (ranging from 0 to 1) were performed. For each reconstruction, similarity indicators of the energy spectrum and the dose distribution to the referenced data were calculated to determine the optimal regularization parameters. Results: Optimal regularization parameters determined by similarity indicators for the spectrum and the dose distribution differ for geometry models considered in the study. The regularization parameter for the simple geometry ranged from 0.03 to 0.05, while for full geometry, they were from 0.05 to 0.06. The results for conventional linear accelerators found in the literature range from 0.5 to 1.1. Conclusion: The Dual Annealing optimization method can be effectively used to solve the Fredholm equation with Tikhonov regularization to reconstruct an electron beam's energy spectrum. The regularization parameter value depends on the beam-forming system. Its value for the mobile accelerator considered in the study ranges from 0.05 to 0.06, depending on the nominal beam energy value.

Introduction: Image guided radiotherapy allows for particularly conformal tumour irradiation through precise patient positioning. Becoming the standard for radiotherapy, this increases imaging doses to the patient. The Halcyon 3.0 linear accelerator (Varian Medical Systems, Palo Alto, CA) requires daily imaging due to its geometry. For this reason, the accelerator is equipped with on-line kV and MV imaging. However, daily CBCT images required for irradiation apply additional radiation, which increases the dose to normal tissue and therefore can affect the patient's secondary cancer risk. In this study, actual organ doses were measured for the kV system, and a comparison of normal tissue doses for all available kV CBCT protocols was presented to demonstrate differences in imaging doses across entities and protocols. In addition, effective dose and secondary cancer risk from imaging are evaluated. Material and methods: Measurements were performed with thermoluminescent dosimeters in an anthropomorphic phantom positioned according to each entity (brain, head and neck, breast, lung, pelvis). CBCT images were obtained, using all available pre-set protocols without further adjustment of the parameters. Measured doses for each position and each protocol were then compared and secondary cancer risk of relevant and specifically radiosensitive organs was calculated. Results: It was found that imaging doses for protocols such as Pelvis and Head could be reduced by up to half using the corresponding Fast and Low Dose modes, respectively. On the other hand, larger field sizes or the Large mode yielded higher doses than their initial protocols. Image Gently was found to spare normal tissue best, however it is not suitable for certain entities due to low image quality or insufficient projection data. Discussion: By using appropriate kV-CBCT protocols, it is possible to reduce imaging doses to a significant extent and therefore spare healthy tissue. Combined with studies of image quality, the results of this study could lead to adjustments in workflow regarding the choice of protocols used in daily routine. This could prevent unnecessary radiation exposure and reduce secondary cancer risk.

Purpose: Volumetric modulated arc therapy (VMAT) is a widespread technique for the delivery of normo-fractionated radiation therapy (NFRT) and stereotactic body radiation therapy (SBRT). It is associated with a significant hardware burden requiring dose rate modulation, collimator movement and gantry rotation synchronisation. Patient specific quality assurance (PSQA) guarantees that the linacs can precisely and accurately deliver the planned dose. However, PSQA requires a significant time allocation and class solutions to reduce this while guaranteeing the deliverability of the plans should be investigated. Methods: In this study, an in-house developed Eclipse Scripting API (ESAPI) script was used to extract five independent plan complexity metrics from N = 667 VMAT treatment fields. The correlation between metrics and portal dosimetry measurements was investigated with Pearson correlation, box plot analysis and receiver operating characteristic curves, which were used to defined the best performing metric and its threshold. Results: The incidence of fields failing the clinical PSQA criteria of 3%/2mm (NFRT) and 3%/1.5mm (SBRT) was low (N = 1). The mean MLC opening was the metric with the highest correlation with the portal dosimetry data and among the best in discriminating the requirement of PSQA. The thresholds of 16.12 mm (NFRT) and 7.96 mm (SBRT) corresponded to true positive rates higher than 90%. Conclusions: This work presents a quantitative approach to reduce the time allocation for PSQA by identifying the most complex plans demanding a dedicated measurement. The proposed method requires PSQA for approximately 10% of the plans. The ESAPI script is distributed open-source to ease the investigation and implementation at other institutions.

Purpose: To determine 10 MV IMRT and VMAT based protocols with a daily bolus targeting a skin dose of 45 Gy in order to replace the 6 MV tangential fields with a 5 mm thick bolus on alternate days method for post-mastectomy radiotherapy. Method: We measured the mean surface dose along the chest wall PTV as a function of different bolus thicknesses for sliding window IMRT and VMAT plans. We analyzed surface dose profiles and dose homogeneities and compared them to our standard 6 MV strategy. All measurements were performed on a thorax phantom with Gafchromic films while dosimetric plans were computed using the Acuros XB algorithm (Varian). Results: We obtained the best compromise between measured surface dose (mean dose and homogeneity) and skin toxicity threshold obtained from the literature using a daily 3 mm thick bolus. Mean surface doses were 91.4 ± 2.8% [85.7% – 95.4%] and 92.2 ± 2.3% [85.6% – 95.2%] of the prescribed dose with IMRT and VMAT techniques, respectively. Our standard 6 MV alternate days 5 mm thick bolus leads to 89.0 ± 3.7% [83.6% – 95.5%]. Mean dose differences between measured and TPS results were < 3.2% for depths as low as 2 mm depth. Conclusion: 10 MV IMRT-based protocols with a daily 3 mm thick bolus produce a surface dose comparable to the standard 6 MV 5 mm thick bolus on alternate days method but with an improved surface dose homogeneity. This allows for a better control of skin toxicity and target volume coverage.

We present a multi-stage and multi-resolution deformable image registration framework for image-guidance at a small animal proton irradiation platform. The framework is based on list-mode proton radiographies acquired at different angles, which are used to deform a 3D treatment planning CT relying on normalized mutual information (NMI) or root mean square error (RMSE) in the projection domain.We utilized a mouse X-ray micro-CT expressed in relative stopping power (RSP), and obtained Monte Carlo simulations of proton images in list-mode for three different treatment sites (brain, head and neck, lung). Rigid transformations and controlled artificial deformation were applied to mimic position misalignments, weight loss and breathing changes. Results were evaluated based on the residual RMSE of RSP in the image domain including the comparison of extracted local features, i.e. between the reference micro-CT and the one transformed taking into account the calculated deformation.The residual RMSE of the RSP showed that the accuracy of the registration framework is promising for compensating rigid (>97% accuracy) and non-rigid (∼95% accuracy) transformations with respect to a conventional 3D-3D registration. Results showed that the registration accuracy is degraded when considering the realistic detector performance and NMI as a metric, whereas the RMSE in projection domain is rather insensitive.This work demonstrates the pre-clinical feasibility of the registration framework on different treatment sites and its use for small animal imaging with a realistic detector. Further computational optimization of the framework is required to enable the use of this tool for online estimation of the deformation.

In human radiotherapy a safety margin (PTV margin) is essential for successful irradiation and is usually part of clinical treatment planning. In preclinical radiotherapy research with small animals, most uncertainties and inaccuracies are present as well, but according to the literature a margin is used only scarcely. In addition, there is only little experience about the appropriate size of the margin, which should carefully be investigated and considered, since sparing of organs at risk or normal tissue is affected.Here we estimate the needed margin for preclinical irradiation by adapting a well-known human margin recipe from van Herck et al. to the dimensions and requirements of the specimen on a small animal radiation research platform (SARRP). We adjusted the factors of the described formula to the specific challenges in an orthotopic pancreatic tumor mouse model to establish an appropriate margin concept. The SARRP was used with its image-guidance irradiation possibility for arc irradiation with a field size of 10 × 10 mm2 for 5 fractions. Our goal was to irradiate the clinical target volume (CTV) of at least 90% of our mice with at least 95% of the prescribed dose. By carefully analyzing all relevant factors we gain a CTV to planning target volume (PTV) margin of 1.5 mm for our preclinical setup.The stated safety margin is strongly dependent on the exact setting of the experiment and has to be adjusted for other experimental settings. The few stated values in literature correspond well to our result. Even if using margins in the preclinical setting might be an additional challenge, we think it is crucial to use them to produce reliable results and improve the efficacy of radiotherapy.

Abstract Background To investigate the artifact sizes of four common breast clip-markers on a standard breast magnetic resonance imaging (MRI) protocol in an in vitro phantom model. Methods Using 1.5-T and 3-T whole-body scanners with an 18-channel breast coil, artifact dimensions of four breast biopsy markers in an agarose-gel phantom were measured by two readers on images obtained with the following sequences: T2-weighted fast spin-echo short inversion time fat-suppressed inversion-recovery with magnitude reconstruction (T2-TIRM); T1-weighted spoiled gradient-echo with fat suppression (T1_FL3D), routinely used for dynamic contrast-enhanced imaging; diffusion-weighted imaging (DWI), including a readout segmented echo-planar imaging (RESOLVE-DWI) and echo-planar imaging sequence (EPI-DWI). After outlining the artifacts by freehand regions of interest, sagittal and lateral diameters in axial images were measured. Results Interreader agreement for artifact size quantification was high, depending on the sequence (80.4–94.8%). Overall, the size, shape, and appearance of artifacts depended on clip type and MRI sequence. The artifact size ranged from 5.7 × 8.5 mm2 to 13.4 × 17.7 mm2 at 1.5 T and from 6.6 × 8.2 mm2 to 17.7 × 20.7 mm2 at 3 T. Clip artifacts were largest on EPI-DWI and RESOLVE-DWI (p ≤ 0.016). In three out of four clips, T2-TIRM showed the smallest artifact (p ≤ 0.002), while in one clip the artifact was smallest on T1_FL3D (p = 0.026). With the exception of one clip in the RESOLVE sequence, all clips showed a decrease in the artifact area from DWI to ADC images (p ≤ 0.037). Conclusion Breast clip-marker MRI artifact appearances depend on clip type, field strength, and sequence and may reach a significant size, potentially obscuring smaller lesions and hindering accurate assessment of breast tumors. Relevance statement Considerable variations in artifact size and characteristics across different breast clips, MRI sequences, and field strengths exist. Awareness of these artifacts and their characteristics is essential to ensure accurate interpretation of scans and appropriate treatment planning. Key Points Awareness of breast clip artifacts is essential for accurate interpretation of MRI. The appearance of artifacts depends on breast clip type, field strength, and sequence. Clip-related artifacts might hinder the visibility of small lesions. Graphical Abstract

Abstract Background Patient-specific three-dimensional (3D) printed anatomic models are valuable clinical tools that facilitate enhanced visualization of pertinent anatomic structures and have demonstrated benefits of reduced surgical times, increased surgeon confidence, and improved operative results and subsequent patient outcomes. Medical image-based 3D printed anatomic models are generally created from computed tomography (CT), however magnetic resonance imaging (MRI), which offers exquisite soft tissue characterization and flexible contrast avoiding the use of ionizing radiation, is an attractive alternative. Herein, the application of 3D printing incorporating both MR neurography and zero-echo time (ZTE) MRI for visualization of the brachial plexus anatomy in a subject with thoracic outlet syndrome (TOS) is described. Methods A 28-year-old man presented with chronic right upper limb discomfort and paresthesias extending from the shoulder region to the third and fourth digits. The subject underwent evaluation with a unilateral brachial plexus MR neurography protocol at 3.0 Tesla for suspicion of TOS. The protocol included T2-weighted, 3D fast spin echo short-tau inversion recovery (STIR-FSE) and 3D radial ZTE sequences for depiction of the nerves and bones, respectively. The first rib and its synostosis impinged upon the inferior aspect of the T1 nerve root (T1NR), with accompanying mild enlargement of the T1NR. A 3D printed anatomic model was created and included: (1) bone (spine, ribs, clavicle, scapula, and humerus), (2) brachial plexus, and (3) costal cartilage. Results The 3D printed model clearly demonstrated a T1NR impingement from the synostosis, confirming the diagnosis of neurologic thoracic outlet syndrome (TOS) and guided the treatment approach in prescribing TOS-specific physical therapy, which led to significant improvements in the patient’s condition. Conclusion To our knowledge, this is the first in-vivo human 3D printed case for TOS using MRI-only data. The 3D printed model allowed for improved visualization and understanding of the spatial relationships between the nerves of the brachial plexus and surrounding osseous structures responsible for the patient’s symptoms. Clinical trial number Not applicable.

Abstract Background Parathyroid cysts account for a small percentage of parathyroid lesions and are more prevalent in females. Cystic parathyroid hyperplasia is exceptionally rare, with only two cases reported thus far. This case report provides the readers with the first multimodality imaging in cystic parathyroid hyperplasia as well as the authors’ first experience in using a 4D computed tomography (CT) scan in our institution while the systematic review will comprehensively search and present similar cases. Main text The literature search started and ended on August 4, 2024. We searched five academic databases: MEDLINE, Cochrane Library, Pubmed, Science Direct, and Google Scholar. The studied population was all patients with cystic parathyroid gland hyperplasia, confirmed by histopathology. A total of 205 articles were initially identified, out of which 29 duplicates were promptly eliminated, leaving 176 unique articles for screening. Following the evaluation of titles and abstracts, ultimately only two studies were included in the systematic review. A 61-year-old male presented with recurrent abdominal pain and weight loss. Ultrasound revealed a left neck mass, cystic. The laryngeal CT scan agreed with the ultrasound while the Technetium-99 sestamibi scan suggested a thyroid lesion. A 4D CT scan confirmed a lobulated cystic lesion in the left parathyroid region. The patient underwent successful surgery, and histopathology confirmed parathyroid hyperplasia with a pseudocyst appearance. Conclusions This case report presents the first imaging multimodality in cystic parathyroid hyperplasia while highlighting the rarity of this case, with two cases worldwide. In addition, this article describes our institution’s first experience with a 4D CT scan.

Abstract Background The most popular technique for evaluating thyroid imaging is high-frequency ultrasonography; however, the TIRADS tool, intended to help with noninvasive risk assessment, has limitations in detecting thyroid cancerous nodules. The purpose of this article was to review the application of TIRADS in ultrasound radiomics and discuss its advantages and limitations. Main text A novel approach to medical picture processing called radiomics can help identify these nodules more precisely. Radiomics involves obtaining high-quality imaging for planning or diagnostic reasons, identifying a macroscopic tumor, extracting quantitative imaging features, and ranking the most informative findings according to prominence, independence, and reproducibility. Conclusions Radiomics combined with TIRADS has demonstrated strong potential in enhancing the accuracy of thyroid nodule malignancy predictions, though challenges such as the need for larger, diverse datasets, and thorough validation persist. Incorporating clinical data, using deep learning models, and standardized imaging protocols could improve diagnostic precision, and further research will, therefore, be essential for its implementation in routine clinical practice.

Abstract Background Primary breast carcinoma is far more common than breast metastases. Common breast metastases usually come from lymphoma, leukemia, melanoma, and ovarian cancers. Breast metastases from neuroendocrine carcinomas are considered an exceeding rare entity. It has been reported in the literature that the pathological presentation of this particular metastatic tumor is very challenging as it shares many morphological characteristics with primary breast carcinoma. Case presentation We report a case of a patient with large cell neuroendocrine carcinoma of the lung metastasizes to both breasts. The patient was initially presented with brain metastasis of unknown origin. Further radiological imaging workup showed multiple bilateral breast masses and bilateral lymphadenopathy, which raised concern for secondary lymphoma of the breast. The histopathology of this case was challenging, particularly when triple negative invasive ductal carcinoma diagnosis had been made. Multidisciplinary meetings between medical oncologists, radiologists, and pathologists profoundly helped confirming the diagnosis of metastatic large cell neuroendocrine tumor to the breast. Conclusion Large cell neuroendocrine carcinoma of the lung is a relatively uncommon diagnosis with generally poor prognosis. Large cell neuroendocrine carcinoma that metastasizes to the breast is even scarcer. Correlation between clinical assessment, radiological imaging, and pathological evaluation is the key in making such an unusual and complex diagnosis. Additionally, radiologists should be aware of metastatic presentations of the breast and avoid confusion with mimicking benign entities or primary breast carcinomas.

Abstract Background Globally, the clinical understanding of prostatitis has been obscured mainly due non-specificity of clinical features, no uniform diagnostic criteria and its protracted treatment course. Conventional treatment of chronic prostatitis by oral or parenteral routes of drug administration remains a challenge basically because of the poor ability of drugs to penetrate prostate epithelium; the alternative of direct prostate injection has not been thoroughly studied in an African population. The aim of this retrospective study was to determine the effect of transrectal ultrasound (TRUS)-guided intraprostatic injection of a cocktail of antibiotics, antifungal and long-acting steroids on alleviating symptoms attributed to chronic prostatitis in Ugandan patients. Methods We conducted a retrospective review of records among patients who were referred with symptoms attributed to chronic prostatitis at the Radiology Department of Ernest Cook Ultrasound Research and Education Institute (ECUREI). Patients were treated using TRUS-guided intraprostatic injection of a cocktail of antibiotics, antifungal agents and long-acting steroids. Results At baseline, we found that out of the 131 patients, 90 had pain or burning during urination in the last week to seeking care and 89 had symptoms, which had kept them away from doing the kinds of things they would usually do. Additionally, 85 of the total number of patients felt terrible about their symptoms. Post intervention, after 1 year following completion of intraprostatic injection therapy (IPIT), we found that most patients had mild residual symptoms which were largely; mild pain and burning at urination. None of the patients had symptoms, which kept them away from doing the kind of things they would usually do. Furthermore, 62 patients felt delighted about their quality of life, whereas prior to treatment, none was delighted. Eighty-five patients had felt terrible about their quality of life prior to the IPIT, but post therapy, no patient felt terrible. Conclusion Transrectal ultrasound-guided intraprostatic injection therapy of a drug cocktail composed of antibiotics, antifungal agents, long-acting steroids and lidocaine for treatment of patients presenting with symptoms attributed to chronic prostatitis and refractory to conventional oral therapy has shown a good response in this study.

Abstract Purpose To assess the diagnostic performance of prostate MRI by estimating the proportion of clinically significant prostate cancer (csPCa) in patients without prostate pathology. Materials and methods This three-center retrospective study included prostate MRI examinations performed for clinical suspicion of csPCa (Grade group ≥ 2) between 2018 and 2022. Examinations were divided into two groups: pathological diagnosis within 1 year after the MRI (post-MRI pathology) is present and absent. Risk prediction models were developed using the extracted eleven common predictive variables from the patients with post-MRI pathology. Then, the csPCa proportion in the patients without post-MRI pathology was estimated by applying the model. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and positive and negative predictive values (PPV/NPV) of prostate MRI in diagnosing csPCa were subsequently calculated for patients with and without post-MRI prostate pathology (estimated statistics) with a positive threshold of PI-RADS ≥ 3. Results Of 12,191 examinations enrolled (mean age, 65.7 years ± 8.4 [standard deviation]), PI-RADS 1–2 was most frequently assigned (55.4%) with the lowest pathological confirmation rate of 14.0–18.2%. Post-MRI prostate pathology was found in 5670 (46.5%) examinations. The estimated csPCa proportions across facilities were 12.6–15.3%, 18.4–31.4%, 45.7–69.9%, and 75.4–88.3% in PI-RADS scores of 1–2, 3, 4, and 5, respectively. The estimated (observed) performance statistics were as follows: AUC, 0.78–0.81 (0.76–0.79); sensitivity, 76.6–77.3%; specificity, 67.5–78.6%; PPV, 49.8–66.6% (52.0–67.7%); and NPV, 84.4–87.2% (82.4–86.6%). Conclusion We proposed a method to estimate the probabilities harboring csPCa for patients who underwent prostate MRI examinations, which allows us to understand the PI-RADS diagnostic performance with several metrics. Clinical relevance statement The reported estimated performance metrics are expected to aid in understanding the true diagnostic value of PI-RADS in the entire prostate MRI population performed with clinical suspicion of prostate cancer. Key Points Calculating performance metrics only from patients who underwent prostate biopsy may be biased due to biopsy selection criteria, especially in PI-RADS 1–2. The estimated area under the receiver operating characteristic curve of PI-RADS in the entire prostate MRI population ranged from 0.78 to 0.81 at three facilities. The estimated statistics are expected to help us understand the true PI-RADS performance and serve as a reference for future studies. Graphical Abstract

Abstract Objectives To investigate the value of vascular morphology on high frame rate contrast-enhanced ultrasound (H-CEUS) and CEUS Li-RADS in predicting microvascular invasion (MVI), Ki-67 expression and recurrence of hepatocellular carcinoma (HCC). Methods This retrospective study enrolled 78 patients with single HCC diagnosed by postoperative pathology between January 1, 2021, and June 30, 2022. All patients underwent ultrasound and H-CEUS examination before operation. H-CEUS image features and CEUS Li-RADS were compared in different MVI status and Ki-67 level. Multiple logistic regression analysis was performed to select independent variables for MVI. Differences in recurrence among different H-CEUS image features, MVI status and Ki-67 level were further analyzed. Results Tumor shape, vascular morphology, LR-M category, necrosis and AFP level were different between the MVI-positive group and MVI-negative group (p

Abstract Over the past decades, numerous large-scale neuroimaging projects that involved the collection and release of multimodal data have been conducted globally. Distinguished initiatives such as the Human Connectome Project, UK Biobank, and Alzheimer’s Disease Neuroimaging Initiative, among others, stand as remarkable international collaborations that have significantly advanced our understanding of the brain. With the advancement of big data technology, changes in healthcare models, and continuous development in biomedical research, various types of large-scale projects are being established and promoted worldwide. For project leaders, there is a need to refer to common principles in project construction and management. Users must also adhere strictly to rules and guidelines, ensuring data safety and privacy protection. Organizations must maintain data integrity, protect individual privacy, and foster stakeholders’ trust. Regular updates to legislation and policies are necessary to keep pace with evolving technologies and emerging data-related challenges. Critical relevance statement By reviewing global large-scale neuroimaging projects, we have summarized the standards and norms for establishing and utilizing their data, and provided suggestions and opinions on some ethical issues, aiming to promote higher-quality neuroimaging data development. Key Points Global neuroimaging projects are increasingly advancing but still face challenges. Constructing and utilizing neuroimaging projects should follow set rules and guidelines. Effective data management and governance should be developed to support neuroimaging projects. Graphical Abstract

Abstract Background To evaluate the utility of glucose chemical exchange saturation transfer (glucoCEST) MRI with non-contrast injection in predicting the histological grade of rectal cancer. Methods This prospective analysis included 60 patients with preoperative rectal cancer who underwent pelvic glucoCEST, amide proton transfer-weighted imaging (APTWI), and diffusion-weighted imaging (DWI). In total, 21 low-grade and 39 high-grade cases were confirmed by postoperative pathology. The MTRasym (1.2 ppm), MTRasym (3.5 ppm), and apparent diffusion coefficient (ADC) values of lesions between the low-grade and high-grade groups were compared. The area under the receiver operating characteristic curve (AUC) was generated to evaluate the diagnostic performance of each technique. Logistic regression (LR) analysis was applied to determine independent predictors and for multi-parameter combined diagnosis. Results Elevated MTRasym (1.2 ppm), MTRasym (3.5 ppm) values and lower ADC values were observed in the high-grade group compared with low-grade cases (all p

Abstract Developments in the multidisciplinary treatment of rectal cancer with advances in preoperative magnetic resonance imaging (MRI), surgical techniques, neoadjuvant chemoradiotherapy, and adjuvant chemotherapy have had a significant impact on patient outcomes, increasing the rates of curative surgeries and reducing pelvic recurrence. Patients with pelvic recurrence have worse prognoses, with an impact on morbidity and mortality. Although local recurrence is more frequent within 2 years of surgical resection of the primary tumor, late recurrence may occur. Clinical manifestations can vary from asymptomatic, nonspecific symptoms, to pelvic pain, bleeding, and fistulas. Synchronous metastatic disease occurs in approximately 50% of patients diagnosed with local recurrence. MRI plays a crucial role in posttreatment follow-up, whether by identifying viable neoplastic tissues or acting as a tool for therapeutic planning and assessing the resectability of these lesions. Locally recurrent tissues usually have a higher signal intensity than muscle on T2-weighted imaging. Thus, attention is required for focal heterogeneous lesions, marked contrast enhancement, early invasive behavior, and asymmetric appearance, which are suspicious for local recurrence. However, postsurgical inflammatory changes related to radiotherapy and fibrosis make it difficult to detect initial lesions. This study therefore aimed to review the main imaging patterns of pelvic recurrence and their implications for the surgical decision-making process. Critical relevance statement MRI plays a crucial role in the posttreatment follow-up of rectal cancer, whether by identifying viable neoplastic tissues or by acting as a tool for therapeutic planning. This study reviewed the main imaging patterns of pelvic recurrence. Key Points MRI aids in surgical planning and the detection of pelvic recurrence and postoperative complications. Being familiar with surgical techniques enables radiologists to identify expected MRI findings. Patterns of rectal cancer recurrence have been categorized by pelvic compartments. Neoplastic tissue may mimic postsurgical and postradiotherapy changes. Resectability of pelvic recurrence is highly related to lesion location. Graphical Abstract

Abstract Objectives Chest computed tomography (CT) can diagnose and assess the severity of pulmonary contusions. However, in cases of severe lung contusion, the total lung volume ratio may not accurately predict severity. This study investigated the association between life-threatening hemoptysis and chest CT imaging data on arrival at the emergency department in patients with pulmonary contusions or lacerations due to blunt chest injury. Methods The records of 277 patients with lung contusions or lacerations treated at a trauma center between 2018 and 2022 were retrospectively reviewed. The ratio of the local lung contusion volume to lobe volume in each lobe was calculated from chest CT images. The maximal ratio in the Hounsfield unit (HU) range was defined as the highest ratio value within the HU range among five lobes. Results The median patient age was 41 years, and 68.6% were male. Life-threatening hemoptysis occurred in 39 patients. The area under the receiver operating characteristic curve for the maximal ratio at −500 HU to 100 HU was 96.52%. The cutoff value was 45.49%. Multivariate analysis showed a high maximal chest CT ratio ≥ 45.49% at −500 HU to 100 HU (adjusted odds ratio [aOR]: 104.66, 95% confidence interval [CI]: 21.81–502.16, p

Abstract Background With the next generation of Human Epidermal Growth Factor Receptor 2 (HER2) -targeting therapies, such as antibody–drug conjugates, showing benefit in “HER2 low” and even “HER2 ultralow” patients, the need for novel methods to quantify HER2 expression accurately becomes even more important for clinical decision making. A HER2 PET/CT imaging assessment could evaluate HER2 positive disease locations while improving patient care, reducing the need for invasive biopsies. A single-domain antibody (sdAb)-based PET tracer could combine the high specificity of sdAbs with short-lived radionuclides such as fluorine-18 (18F) and gallium-68 (68Ga). SdAb-based PET tracers have clinically been used via a 68Ga-chelator approach. However, the distribution of 68Ga-labelled pharmaceuticals to peripheral PET centres is more challenging to organize due to the short half-life of 68Ga, most certainly when the available activity is limited by a generator. Cyclotron produced 68Ga has removed this limitation. Distribution of 18F-labelled pharmaceuticals remains less challenging due to its slightly longer half-life, and radiofluorination of sdAbs via N-succinimidyl-4-[18F]fluorobenzoate ([18F]SFB) has shown to be a promising strategy for developing sdAb-based PET tracers. Although [18F]SFB automation has been reported, automating protein conjugation proves challenging. Herein we report the fully automated, cartridge-based production of [18F]FB-HER2 sdAb on a single synthesis module. Results [18F]FB-HER2 sdAb (> 6 GBq) was obtained after a fully automated production (95 min), with a RCP > 95%, apparent molar activity > 20 GBq/µmol and decay-corrected radiochemical yield (RCY d.c.) of 14 ± 2% (n = 4). Further upscaling amounted to production batches of 16 GBq with an apparent molar activity > 40 GBq/µmol and RCY d.c. of 8 ± 1% (n = 4). Ex vivo biodistribution and PET imaging showed specific HER2-positive tumour targeting and low kidney retention. Conclusion The [18F]FB-HER2 sdAb tracer was produced with clinically relevant activities using a fully automated production method. The automated production method was designed to ease the translation to the clinic and has the potential to be used not only in mono-centre but also multi-centre clinical trials with one central production site. [18F]FB-HER2 sdAb showed a favourable biodistribution pattern and could be a valuable alternative to 68Ga-labelled sdAb-based PET tracers in the clinic.

Abstract Background Pretargeted radioimmunotherapy of cancer has the potential to increase tumor specific uptake of activity when compared with conventional radioimmunotherapy. This is especially true in radioimmunotherapy with nuclides that exhibit a relatively short half-life. When administering antibody-based pretargeting molecules systemically, the antibodies often show a relatively slow clearance from the blood. Therefore, the use of a clearing agent is advantageous to remove unbound pretargeting molecules from the circulation, facilitating a reduction in the nonspecific radiation exposure to normal tissue while maximizing the dose delivered to the tumors. Results In the current study, two types of poly-L-lysine based clearing agents were produced for two different pretargeting systems: (strept)avidin/biotin and Tetrazine/Transcyclooctene. Poly-L-lysine was used as scaffold for production of clearing agents. The polymer is available in multiple sizes and can readily be modified with several functional groups, allowing different pretargeting strategies to be used. In vivo evaluation of the biotin-functionalized poly-L-lysine clearing agent, 110 repeating units, resulted in a decrease in blood concentration of the Iodine-125 labeled pretargeting agent of 50%, circa 23 h after injection, compared to controls. Two sizes, 68 and 143 repeating units, of the tetrazine-functionalized poly-L-lysine clearing agent were also evaluated, which at 23 h after injection decreased the blood concentration of the Iodine-125 labeled pretargeting agent to 58 and 38% respectively. Conclusion The straightforward synthesis of poly-L-lysine based clearing agents makes kit preparation possible and these agents show good potential for further evaluation, especially within the Tetrazine/Transcyclooctene pretargeting system where no liver or kidney accumulation was observed.

Abstract Objectives This study aimed to develop and validate a deep-learning radiomics model using CT, T2, and DWI images for predicting pathological complete response (pCR) in patients with esophageal squamous cell carcinoma (ESCC) undergoing neoadjuvant chemoradiotherapy (nCRT). Materials and methods Patients with ESCC undergoing nCRT followed by surgery were retrospectively enrolled from three institutions and divided into training and testing cohorts. Both traditional and deep-learning radiomics features were extracted from pre-treatment CT, T2, and DWI. Multiple radiomics models were developed, both single modality and integrated, using machine learning algorithms. The models’ performance was assessed using receiver operating characteristic curve analysis, with the area under the curve (AUC) as a primary metric, alongside sensitivity and specificity from the cut-off analysis. Results The study involved 151 patients, among whom 63 achieved pCR. The training cohort consisted of 89 patients from Institution 1 (median age 62, 73 males) and the testing cohort included 52 patients from Institution 2 (median age 62, 41 males), and 10 in a clinical trial from Institution 3 (median age 69, 9 males). The integrated model, combining traditional and deep learning radiomics features from CT, T2, and DWI, demonstrated the best performance with an AUC of 0.868 (95% CI: 0.766–0.959), sensitivity of 88% (95% CI: 73.9–100), and specificity of 78.4% (95% CI: 63.6–90.2) in the testing cohort. This model outperformed single-modality models and the clinical model. Conclusion A multimodality deep learning radiomics model, utilizing CT, T2, and DWI images, was developed and validated for accurately predicting pCR of ESCC following nCRT. Critical relevance statement Our research demonstrates the satisfactory predictive value of multimodality deep learning radiomics for the response of nCRT in ESCC and provides a potentially helpful tool for personalized treatment including organ preservation strategy. Key Points After neoadjuvant chemoradiotherapy, patients with ESCC have pCR rates of about 40%. The multimodality deep learning radiomics model, could predict pCR after nCRT with high accuracy. The multimodality radiomics can be helpful in personalized treatment of esophageal cancer. Graphical Abstract

Abstract Objectives To investigate whether the signal intensity (SI) ratio of residual fibroid (RF) to myometrium using Contrast-Enhanced Magnetic Resonance Imaging (CE-MRI) could predict fibroid regrowth after high-intensity focused ultrasound (HIFU) treatment. Materials and methods A retrospective analysis was conducted among 164 patients with uterine fibroids who underwent HIFU. To predict the RF regrowth, the SI perfusion parameters were quantified using the RF-myometrium SI ratio on CE-MRI on day 1 post-HIFU and then compared with the fibroid-myometrium SI ratio on the T2-weighted image (T2WI) and Funaki classification 1 year later. Thirty cases from another center were used as an external validation set to evaluate the performance of RF-myometrium SI ratio. Results The predictive performance of the RF-myometrium SI ratio on CE-MRI on day 1 post-HIFU (Area Under Curve, AUC: 0.869) was superior to that of the preoperative and postoperative fibroid-myometrium SI ratios on the T2WI (AUC: 0.724, 0.696) and Funaki classification (AUC: 0.663, 0.623). Multivariate analysis showed that the RF- myometrium SI ratio and RF thickness were independent factors. The RF-myometrium SI ratio reflects the long-term rate of re-intervention (r = 0.455, p

Abstract Objectives This study developed a deep learning radiomics (DLR) model utilizing baseline computed tomography enterography (CTE) to non-invasively predict stratified healing in Crohn’s disease (CD) patients following infliximab (IFX) treatment. Methods The study included 246 CD patients diagnosed at three hospitals. From the first two hospitals, 202 patients were randomly divided into a training cohort (n = 141) and a testing cohort (n = 61) in a 7:3 ratio. The remaining 44 patients from the third hospital served as the validation cohort. Radiomics and deep learning features were extracted from both the active lesion wall and mesenteric adipose tissue. The most valuable features were selected using univariate analysis and least absolute shrinkage and selection operator (LASSO) regression. Multivariate logistic regression was then employed to construct the radiomics, deep learning, and DLR models. Model performance was evaluated using receiver operating characteristic (ROC) curves. Results The DLR model achieved an area under the ROC curve (AUC) of 0.948 (95% CI: 0.916–0.980), 0.889 (95% CI: 0.803–0.975), and 0.938 (95% CI: 0.868–1.000) in the training, testing, and validation cohorts, respectively in predicting mucosal healing (MH). Furthermore, the diagnostic performance of DLR model in predicting transmural healing (TH) was 0.856 (95% CI: 0.776–0.935). Conclusions We have developed a DLR model based on the radiomics and deep learning features of baseline CTE to predict stratified healing (MH and TH) in CD patients following IFX treatment with high accuracies in both testing and external cohorts. Critical relevance statement The deep learning radiomics model developed in our study, along with the nomogram, can intuitively, accurately, and non-invasively predict stratified healing at baseline CT enterography. Key Points Early prediction of mucosal and transmural healing in Crohn’s Disease patients is beneficial for treatment planning. This model demonstrated excellent performance in predicting mucosal healing and had a diagnostic performance in predicting transmural healing of 0.856. CT enterography images of active lesion walls and mesenteric adipose tissue exhibit an association with stratified healing in Crohn’s disease patients. Graphical Abstract

Abstract Purposes To evaluate the impact of prophylactic cranial irradiation (PCI) on the prognosis of patients with limited-stage small cell lung cancer (SCLC) in the era of MRI surveillance. Methods Limited-stage SCLC patients with complete remission (CR) or partial remission (PR) of tumor after definitive chemo-radiotherapy (CRT) were retrospectively analyzed. Survival data were calculated by Kaplan-Meier methods, Cox proportional hazards model was applied for multivariate prognostic analysis. Results Between June 2002 and January 2017, 620 patients with limited-stage SCLC were accrued in our study. After CRT, 228 (36.8%) patients achieved CR, of whom, 29 patients did not receive PCI, among the rest 199 patients, 172 (86.4%) received brain MRI to exclude brain metastasis (BM) before PCI. With a median follow-up time of 25.6 months, the cumulative BM rate was 17.1% and 37.9% in patients who received or did not receive PCI (P = 0.011). The median survival time was 30.2 months and 30.5 months, respectively and the 1 -, 3 -, 5-year survival rates were 93.7%, 42.9%, 35.8% and 83.4%, 46.5%, 41.9%, respectively (P = 0.98). Multivariate analysis indicated that baseline KPS ≥ 90 was a favorable independent prognostic factor for OS in CR patients (HR: 0.33, 95% CI: 0.23–0.46, P = 0.000). After CRT, 392 (63.2%) patients achieved PR, 53 cases did not receive PCI and 310 (91.4%) of the remaining 339 patients received brain MRI before PCI. With a median follow-up time of 15.5 months, the cumulative brain metastasis rate was 12.7% and 46.2% respectively (P = 0.000). The median survival time was 25.7 months and 18.6 months, respectively. The 1 -, 3 -, and 5-year survival rates were 87.6%, 40.2%, 29.2% and 75.7%, 16.7%, 10.3% (P = 0.000). Baseline KPS ≥ 90 (HR: 0.32, 95% CI: 0.25–0.41, P = 0.000) and PCI (HR: 0.57, 95% CI: 0.41–0.79, P = 0.001) were favorable prognostic factors for OS in PR patients. Conclusions In this study, PCI significantly reduced the incidence of BM in patients with limited-stage SCLC who were evaluated as CR and PR after CRT, but it has no significantly positive impact on overall survival in CR patients. Further prospective randomized studies were warranted.

Abstract Background Intrahepatic cholangiocarcinoma (ICC) is a challenging primary liver cancer with a poor prognosis, especially in unresectable cases. Traditional palliative irradiation is limited in reducing liver doses. This study aimed to evaluate the efficacy and toxicity of respiratory-gated proton beam therapy without fiducial markers for intrahepatic cholangiocarcinoma. Methods Between October 2011 and February 2022, 24 patients (median [range] age, 71 [41–88] years) were evaluated at our institution. Twelve patients were pathologically diagnosed with ICC. All patients underwent respiratory-gated proton beam therapy at a dose of 48–83.6 (relative biological effectiveness) in 20–38 fractions with four-dimensional computed tomography planning. The median follow-up period was 18.5 (range, 2.0–74.0) months. The median tumor size was 41 (range, 10–134) mm. Twenty-one patients were classified as having Child–Pugh class A, and three patients were classified as having Child–Pugh class B. Local progression was defined as any growth of the irradiated tumor. Results The median survival time was 28 months for all patients. The Kaplan–Meier estimates of the 2-year overall survival, progression-free survival, and local tumor control rates were 51%, 26%, and 73%, respectively. Local tumor control rates were non-inferior to those reported in previous studies using fiducial markers. One patient had grade 4 pleural effusion; however, whether this was an adverse event due to the proton beam therapy was unclear. Conclusions Respiratory-gated proton beam therapy without fiducial markers is an effective and less invasive treatment option for ICC, showing potential for improved local control and tolerable adverse effects.

Abstract Background Recent research has demonstrated that the use of artificial intelligence (AI) in radiotherapy (RT) has significantly streamlined the process for physicians to treat patients with tumors; however, bibliometric studies examining the correlation between AI and RT are not available. Providing a thorough overview of the knowledge structure and research hotspots between AI and RT was the main goal of the current study. Method A search was conducted on the Web of Science Core Collection (WoSCC) database for publications pertaining to AI and RT between 2003 and 2023. VOSviewers, CiteSpace, and the R program “bibliometrix” were used to do the bibliometric analysis. Results The analysis comprised 615 publications from 64 countries, with USA and China leading the pack. Since 2017, there have been more and more publications about RT and AI every year. The research center that made the biggest contribution to this topic was Maastricht University. The most articles published journal in this field was Frontiers in Oncology, while Medical Physics received the greatest number of citations. Dekker Andre is the author with the greatest number of published articles, while Philippe Lambin was the most often co-cited author. In the newly identified research hotspots, “autocontouring algorithm”, “deep learning”, and “machine learning” stand out as the main terms. Conclusion In fact, our bibliometric analysis offers insightful information on current research directions and advancements pertaining to the use of AI in RT. For academics looking to understand the connection between AI and RT, this study is a great resource because it highlights current research frontiers and hot trends.

Abstract Background Craniopharyngioma is a rare and slow-growing benign sellar or parasellar epithelial tumor. The number of patients receiving proton beam therapy (PBT) has increased. This study aimed to systematically evaluate and analyze the comprehensive evidence regarding the safety and efficacy of PBT for craniopharyngioma. Methods We searched four databases: the Cochrane Library, PubMed, Embase, and Web of Science. The period was from their inception to February 16, 2024. Two researchers independently screened the literature and extracted data. Results Among 486 candidate articles, eight studies were included in our study. Exactly 393 patients with craniopharyngioma underwent PBT in these studies. These studies reported data on survival and toxicity. The median sample size was 42.5 patients. The median age was 9.1–37 years; the female proportion was 48.9%, and the median follow-up time was 29–91.4 months. All patients were treated once daily, five times a week, with a fraction of 1.8 Gy (RBE) per session. The median total dose was 54.0 Gy (RBE). The local control rates at 3 and 5 years in these studies were 99% and 93%, respectively. The overall survival rates at 3 and 5 years in these studies were both 100%. The incidence of acute and late toxicities was mainly grade 1–2. The main late toxicities included vascular and visual toxicities, hypothalamic obesity, endocrinopathy, and panhypopituitarism. Conclusions PBT for craniopharyngioma, especially in children and adolescents, has shown impressive local control and acceptable acute and late toxicities.

Abstract Background The aim of this study was to evaluate the inter-fraction reproducibility and intra-fraction stability of breast radiotherapy using voluntary deep-inspiration breath hold (DIBH) and free breathing (FB) based on an optical surface imaging system (OSIS). Methods Seventeen patients (510 breath-hold sessions) treated using a field-in-field (FiF) technique and twenty patients (600 breath-free sessions) treated with a volume-modulated arc therapy (VMAT) technique were included in this retrospective study. All the patients were positioned with the guidance of CBCT and OSIS, and also monitored with OSIS throughout the whole treatment session. Eight setup variations in three directions were extracted from the treatment reports of OSIS for all sessions and were subsequently manually introduced to treatment plans, resulting in a total of 296 perturbed plans. All perturbed plans were recalculated, and the dose volume histograms (DVH) for the target and organs at risk (OAR) were analyzed. Results The OSIS and CBCT for both DIBH and FB treatments showed a good agreement of less than 0.30 cm in each direction. The intra-fraction respiratory motion data during DIBH were −0.06 ± 0.07 cm, 0.12 ± 0.15 cm, and 0.12 ± 0.12 cm in the lateral, longitudinal, and vertical directions, respectively; for FB, the respiratory motion data were −0.02 ± 0.12 cm, 0.08 ± 0.18 cm, and 0.14 ± 0.20 cm, respectively. For the target, DIBH plans were more sensitive to setup errors; the mean deviations in D95 for CTV were 39.78 Gy–40.17 Gy for DIBH and 38.46 Gy–40.52 Gy for FB, respectively. For the OARs, the mean deviations of V10, V20, and Dmean to the heart; V5, V20, and Dmean to the ipsilateral lung; and Dmean to the breast were lower for the FB plan compared with the DIBH plan. Conclusion Based on OSIS, our results indicate that both DIBH and FB can provide good reproducibility in the inter-fractions and stability in the intra-fractions. When the patient respiratory motion is large, the FB technology has greater possibility for the undercoverage of the target volume, while DIBH technology is more likely to result in increases in dose to OARs (the lung, heart, and contralateral breast).

Abstract Background Pulsed low dose rate radiotherapy (PLDR) is a new radiation delivery method, in which the fractional dose is divided into sub-fractional doses with periodical time breaks in between. The goal of our study is to assess the toxicity on healthy tissues resulting from PLDR as compared to conventional radiotherapy (CRT) using the same physical X-ray dose. Methods We analyzed the weight and survival time for CRT and PLDR groups and studied the inflammatory cytokine transforming Growth Factor-β (TGF-β), usually released following irradiation. Histopathological and immunohistochemical analyses were conducted for intestinal and bone marrow tissues from rats subjected to 8 Gy whole- body irradiation using CRT and PLDR techniques. We investigated genotoxicity by performing a comet assay (CA) in splenic tissues. Results Our findings showed an improvement in survival time with PLDR versus CRT by 82%.The mean survival time for CRT rats’ group was 6.3 days, while it was 35.9 days for PLDR group.The weight of CRT group decreased gradually by 3.7%, while weight of PLDR group increased gradually by 2.4%.CRT resulted in more cellular atrophy in bone marrow and intestinal tissues than in PLDR treatments as shown by hematoxylin and eosin staining analysis. In addition, the transforming growth factor-β (TGF-β) expression in bone marrow and intestinal tissues of CRT was higher than those expressed in tissues from PLDR as demonstrated by the Immuno reactive score (IRS). It was10(0.53) and 9.8(0.55) for BM and intestinal tissues, respectively from CRT group and 5.8(0.63) for PLDR for both tissues. The measured CA parameters were larger with CRT compared to PLDR, where the Tail Length (TL), Tail DNA % (TD%) and Tail Moment (TM) measurements were 25.4(3.4), 56.5(7.6) % and 20.5(3.5) for CRT, 7.3(1.9), 30.0(7.2) % and 5.7(1.8) for PLDR, with P value 0.000064, 0.0004 and 0.00017, respectively. Conclusion This study indicates that PLDR can reduce the toxicity on normal tissues compared to CRT.

Abstract The discovery of fibroblast activation protein inhibitor positron emission tomography (FAPI-PET) has paved the way for a new class of PET tracers that target the tumor microenvironment (TME) rather than the tumor itself. Although 18F-fluorodeoxyglucose (FDG) is the most common PET tracer used in clinical imaging of cancer, multiple studies have now shown that the family of FAP ligands commonly outperform FDG in detecting cancers, especially those known to have lower uptake on FDG-PET. Moreover, FAPI-PET will have applications in benign fibrotic or inflammatory conditions. Thus, even while new FAPI-PET tracers are in development and applications are yet to enter clinical guidelines, a significant body of literature has emerged on FAPI-PET, suggesting it will have important clinical roles. This article summarizes the current state of clinical FAPI-PET imaging as well as potential uses as a theranostic agent.

Abstract Objective The aim of this study was to establish an ensemble learning model based on clinicopathological parameter and ultrasound radomics for assessing the risk of lateral cervical lymph node with short diameter less than 8 mm (small lymph nodes were used instead) metastasis in patients with papillary thyroid cancer (PTC), thereby guiding the selection of surgical methods. Methods This retrospective analysis was conducted on 454 patients diagnosed with papillary thyroid carcinoma who underwent total thyroidectomy and lateral neck lymph node dissection or lymph node intraoperative frozen section biopsy at the First Hospital of China Medical University between January 2015 and April 2022. In a ratio of 8:2, 362(80%) patients were assigned to the training set and 92(20%) patients were assigned to the test set. Clinical pathological features and radomics features related to ultrasound imaging were extracted, followed by feature selection using recursive feature elimination (RFE). Based on distinct feature sets, we constructed ensemble learning models comprising random forest (RF), extreme gradient boosting (XGBoost), categorical boosting (CatBoost), gradient boosting decision tree (GBDT), and light gradient boosting machine (Lightgbm) to develop clinical models, radiomics models, and clinical-radiomic models. Through the comparison of performance metrics such as area under curve (AUC), accuracy (ACC), specificity (SPE), precision (PRE), recall rate, F1 score, mean squared error (MSE) etc., we identified the optimal model and visualized its results using shapley additive exPlanations (SHAP). Results In this study, a total of 454 patients were included, among whom 342 PTC patients had small lymph node metastasis in the lateral neck region, while 112 did not have any metastasis. A total of 1035 features were initially considered for inclusion in this study, which were then narrowed down to 10 clinical features, 8 radiomics features, and 17 combined clinical-omics features. Based on these three feature sets, a total of fifteen ensemble learning models were established. In the test set, RF model in the clinical model is outperforms other models (AUC = 0.72, F1 = 0.75, Jaccard = 0.60 and Recall = 0.84), while CatBoost model in the radiomics model is superior to other models (AUC = 0.91, BA = 0.83 and SPE = 0.76). Among the clinical-radiomic models, Catboost exhibits optimal performance (AUC = 0.93, ACC = 0.88, BA = 0.87, F1 = 0.91, SPE = 0.83, PRE = 0.88, Jaccard = 0.83 and Recall = 0.92). Using the SHAP algorithm to visualize the operation process of the clinical-omics CatBoost model, we found that clinical omics features such as central lymph node metastasis (CLNM), Origin_Shape_Sphericity (o_shap_sphericity), LoG-sigma3_first order_ Skewness (log-3_fo_skewness), wavelet-HH_first order_Skewness (w-HH_fo_skewness) and wavelet-HH_first order_Skewness (sqr_gldm_DNUN) had the greatest impact on predicting the presence of lateral cervical small lymph node metastasis in PTC patients. Conclusions (1) In this study, among the ensemble learning models established based on clinicopathological features and radiomics features for predicting PTC lateral small lymph node metastasis, the clinical-radiomic CatBoost model has the best performance. (2) SHAP can visualize how the clinical and radiomics features affect the results and realize the interpretation of the model. (3) The combined CatBoost model can improve the diagnostic accuracy of suspicious lymph nodes with short diameter

Abstract Background This study aims to construct predicting models using radiomic and clinical features in predicting first-line vascular endothelial growth factor receptor-tyrosine kinase inhibitor (VEGFR-TKI) early resistance in metastatic clear cell renal cell carcinoma (mccRCC) patients. We also aim to explore the correlation of predicting models with short and long-term survival of mccRCC patients. Materials and methods In this retrospective study, 110 mccRCC patients from 2009 to 2019 were included and assigned into training and test sets. Radiomic features were extracted from tumor 3D-ROI of baseline enhanced CT images. Radiomic features were selected by Lasso method to construct a radiomic score. A combined nomogram was established using the combination of radiomic score and clinical factors. The discriminative abilities of the radiomic, clinical and combined nomogram were quantified using ROC curve. Cox regression analysis was used to test the correlation of nomogram score with progression-free survival (PFS) and overall survival (OS). PFS and OS were compared between different risk groups by log-rank test. Results The radiomic, clinical and combined nomogram demonstrated AUCs of 0.81, 0.75, and 0.83 in training set; 0.79, 0.77, and 0.88 in test set. Nomogram score ≥ 1.18 was an independent prognostic factor of PFS (HR 0.22 (0.10, 0.47), p

Abstract Background To develop an artificial intelligence (AI)-based model using Radiomics, deep learning (DL) features extracted from 18F-fluorodeoxyglucose (18F-FDG) Positron emission tomography/Computed Tomography (PET/CT) images of tumor and cervical lymph node with clinical feature for predicting cervical lymph node metastasis (CLNM) in patients with esophageal squamous cell carcinoma (ESCC). Methods The study included 300 ESCC patients from the First Affiliated Hospital of Zhengzhou University who were divided into a training cohort and an internal testing cohort with an 8:2 ratio. Another 111 patients from Shanghai Chest Hospital were included as the external cohort. For each sample, we extracted 428 PET/CT-based Radiomics features from the gross tumor volume (GTV) and cervical lymph node (CLN) delineated layer by layer and 256 PET/CT-based DL features from the maximum cross-section of GTV and CLN images We input these features into seven different machine learning algorithms and ultimately selected logistic regression (LR) as the model classifier. Subsequently, we evaluated seven models (Clinical, Radiomics, Radiomics-Clinical, DL-Clinical, DL-Radiomics, DL-Radiomics-Clinical) using Radiomics features, DL features and clinical feature. Results The DL-Radiomics-Clinical (DRC) model demonstrated higher AUC of 0.955 and 0.916 compared to the other six models in both internal and external testing cohorts respectively. The DRC model achieved the highest accuracy among the seven models in both the internal and external test sets, with scores of 0.951 and 0.892, respectively. Conclusions Through the combination of Radiomics features and DL features from PET/CT imaging and clinical feature, we developed a predictive model exhibiting exceptional classification capabilities. This model can be considered as a non-invasive method for predication of CLNM in patients with ESCC. It might facilitate decision-making regarding to the extend of lymph node dissection, and to select candidates for postoperative adjuvant therapy.

Abstract Background The metabolic response of primary central nervous system lymphoma (PCNSL) patients has yet to be evaluated. This study aimed to assess the prognostic value of a novel scoring scale, the intracranial metabolic score (IMS), in PCNSL patients receiving end-of-therapy 18F-FDG PET/CT (EOT-PCT) and PET/MR (EOT-PMR). Methods The IMS was determined based on the metabolism of normal intracranial structures, including gray matter, white matter, and cerebrospinal fluid. The EOT-PCT cohort was evaluated using the IMS and commonly used Deauville score (DS). Another cohort of patients who underwent the EOT-PMR was used to validate the accuracy of the IMS. Results In total, 83 patients were included in the study (38 in PET/CT cohort, and 45 in PET/MR cohort). The area under the curve (AUC) values of the IMS for predicting PFS and OS were superior to those of the DS. When patients in the PET/CT cohort were stratified into five groups (respectively labeled IMS 1–5), three groups (IMS1-2, IMS 3–4, and IMS 5), or two groups (IMS1-3 and IMS4-5; IMS 1–4 and IMS 5), a higher IMS score was significantly correlated with poorer PFS and OS (p

Abstract The Response Evaluation in Solid Tumors (RECIST) 1.1 provides key guidance for performing imaging response assessment and defines image-based outcome metrics in oncology clinical trials, including progression free survival. In this framework, tumors identified on imaging are designated as either target lesions, non-target disease or new lesions and a structured categorical response is assigned at each imaging time point. While RECIST provides definitions for these categories, it specifically and objectively defines only the target disease. Predefined thresholds of size change provide unbiased metrics for determining objective response and disease progression of the target lesions. However, worsening of non-target disease or emergence of new lesions is given the same importance in determining disease progression despite these being qualitatively assessed and less rigorously defined. The subjective assessment of non-target and new disease contributes to reader variability, which can impact the quality of image interpretation and even the determination of progression free survival. The RECIST Working Group has made significant efforts in developing RECIST 1.1 beyond its initial publication, particularly in its application to targeted agents and immunotherapy. A review of the literature highlights that the Working Group has occasionally employed or adopted objective measures for assessing non-target and new lesions in their evaluation of RECIST-based outcome measures. Perhaps a prospective evaluation of these more objective definitions for non-target and new lesions within the framework of RECIST 1.1 might improve reader interpretation. Ideally, these changes could also better align with clinically meaningful outcome measures of patient survival or quality of life.

Abstract Background Primary mesenchymal tumors of the prostate are very rare, and there is no systematic report on fluorine-18-fluorodeoxyglucose positron emission tomography (18F-FDG PET/CT). The aim of this research was to characterize mesenchymal tumors of the prostate on 18F-FDG PET/CT. Results We included 13 patients with pathologically confirmed mesenchymal neoplasms of the prostate. The location, size, maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), total glycolysis of the lesion (TLG), pathologic findings, and available imaging study of the tumors were reviewed. Of the 13 patients (median age, 38 years; ranged from 13 to 74 years), the mean size of the tumors was 8.8 cm in diameter ranged from 5 to 16.1 cm. SUVmax ranged from 3.1 to 17.6 (mean 9.5), MTV ranged from 4.9 to 398 cm3 (mean 109 cm3) and TLG ranged from 21.3 to 1216 g (mean 96 g). The seminal vesicles, rectum, and bladder are the most commonly affected sites of invasion, while metastasis typically occurs in the bones, lungs, and lymph nodes. Conclusions Mesenchymal tumors of the prostate revealed large sizes and high SUVmax, MTV and TLG levels on 18F-FDG PET/CT. 18F-FDG PET/CT may be useful for accurate diagnosis, staging, and restaging, which plays an important role in the management of subsequent plans.

Abstract Background Heart-type fatty acid binding proteins (FABP3) constitute a family of lipid chaperone proteins. They are found in the cytosol and enhance cellular fatty acid solubilisation, transport, and metabolism. FABP3 is highly expressed in the myocardium and is released from myocytes during myocardial damage. As FABP3 content in the myocardium is closely related to the metabolic state of fatty acids, we hypothesised that targeting of FABP3 with a radiolabelled small organic compound would visualise myocardium. Results The selective FABP3 inhibitor, 4-(4-fluoro-2-(1-phenyl-5-(2-(trifluoromethyl)phenyl)-1H-pyrazol-3-yl)phenoxy)butanoic acid (LUF), was radiolabelled via a two-step reaction comprising copper-mediated 18F-fluorination of an arylboronic precursor followed by alkaline hydrolysis of the ethoxy protecting group. [18F]LUF was successfully synthesised by automated synthesiser with sufficient activity yields (14.0 ± 1.8 GBq) and high quality (molar activity, > 250 GBq/µmol and radiochemical purity, > 99.6%). Biological assessment of [18F]LUF as an in vivo myocardial imaging agent included evaluations of biodistribution, metabolite analysis, and positron emission tomography (PET) imaging of small animals. [18F]LUF clearly visualised the myocardium with high contrast against background tissues such as the lung and liver. [18F]LUF also showed a high absolute myocardial uptake equivalent to that of the promising myocardial perfusion tracer [18F]flurpiridaz and excellent metabolic stability in the body. These properties are ideal for stable and noise-less imaging of the heart. PET imaging of rat surgical permanent myocardial infarction (MI) and experimental autoimmune myocarditis (EAM) was also performed. [18F]LUF successfully visualised lesions of permanent MI and EAM. Conclusion Our results showed for the first time that the 18F-labelled FABP3 selective small organic compound clearly visualised myocardium with good quality. To determine the clinical utility of [18F]LUF for cardiovascular disease in clinical practice, it will be necessary to evaluate a greater variety of cardiovascular disease models and elucidate the accumulation mechanism, particularly in relation to fatty acid metabolism in the myocardium.

Abstract Background Over the past decade, numerous treatment options have emerged for patients with locally advanced and metastatic neuroendocrine tumours (NETs). Nevertheless, the optimal timing of treatment interventions remains uncertain, given the highly variable disease course observed in these patients, even when patients have the same tumour stage and grade. The aim of the study was to evaluate the predictive role of standardized uptake values (SUVs) and volumetric parameters obtained from pretreatment [68Ga]Ga-DOTA-TATE for response to SSA therapy in patients with NET. In this retrospective study, we included 42 patients (21 women, 21 men; age range: 46–84 years) with histologically confirmed, metastatic, NET (G1 13, G2 28 cases); median Ki-67 index 5%, range 1–16) who received long acting SSA as a first line treatment and underwent [68Ga]Ga-DOTA-TATE PET/CT before SSA treatment. For all [68Ga]Ga-DOTA-TATE avid lesion SUVmax, SUVmean, somatostatin receptor expression tumour volume (STV), total lesion somatostatin receptor expression (TLD, STV multiplied by SUV mean) and Tmean/Smean (SUVmean of tumours/metastases divided by SUVmean of normal spleen) were measured. Finally, the sum of STV (total STV, TSTV) and TLD (total TLD, TTLD) was calculated for each patient and used in the analysis. Results During the study period, 14 patients had stable disease (33.3%) and 28 patients experienced progression (66.7%), among whom 12 patients died. The median progression-free survival (PFS) and overall survival (OS) were 26.5 and 46.5 months, respectively. In the univariate and multivariate analysis, in the whole population study, Tmean/Smean ratio (HR 1.88, 95% CI 1.06–3.35, p = 0.03), Ki-67 index (HR 1.14, CI 1.03–1.26, p = 0.01) and pre-treatment chromogranin A serum concentration (HR 1.01, CI 1.0–1.03, p = 0.01) were significantly associated with PFS. Among patients with small intestinal NETs, TSTV (

Abstract Background A considerable portion of patients with fever of unknown origin (FUO) present concomitant lymphadenopathy. Diseases within the spectrum of FUO accompanied by lymphadenopathy include lymphoma, infections, and rheumatic diseases. Particularly, lymphoma has emerged as the most prevalent etiology of FUO with associated lymphadenopathy. Distinguishing between benign and malignant lymph node lesions is a major challenge for physicians and an urgent clinical concern for patients. However, conventional imaging techniques, including PET/CT, often have difficulty accurately distinguishing between malignant and benign lymph node lesions. This study utilizes PET/CT radiomics to differentiate between lymphoma and benign lymph node lesions in patients with FUO, aiming to improve diagnostic accuracy. Results Data were collected from 204 patients who underwent 18F-FDG PET/CT examinations for FUO, including 114 lymphoma patients and 90 patients with benign lymph node lesions. Patients were randomly divided into training and testing groups at a ratio of 7:3. A total of 15 effective features were obtained by the least absolute shrinkage and selection operator (LASSO) algorithm. Machine learning models were constructed using logistic regression (LR), support vector machine (SVM), random forest (RF), and k-nearest neighbors (KNN) algorithms. In the training group, the area under the curve (AUC) values for predicting lymphoma and benign cases by LR, SVM, RF, and KNN models were 0.936, 0.930, 0.998, and 0.938, respectively. There were statistically significant differences in AUC between the RF and other models (all P 0.05). The decision curve analysis (DCA) curves of the RF model outperformed those of the other three models in both the training and testing groups. Conclusions PET/CT radiomics demonstrated promising performance in discriminating lymphoma from benign lymph node lesions in patients with FUO, with the RF model showing the best performance.

Abstract Background Early evaluation of radiation sensitivity in lung cancer patients can facilitate the transition to personalized treatment strategies. To this end, we assessed the capability of 89Zr-anti-γH2AX-TAT microPET imaging in determining the radiosensitivity of lung cancer xenograft models. We prepared and conducted quality control on 89Zr-anti-γH2AX-TAT. The radiosensitivity of human non-small cell lung cancer cells (H460) and adenocarcinoma cells (A549) was analyzed through clonogenic survival experiments. Additionally, the role of γH2AX as a biomarker for radiosensitivity was validated by quantifying γH2AX foci via fluorescence staining. Subsequently, the H460 and A549 xenograft mouse models were subjected to irradiation, followed by 89Zr-anti-γH2AX-TAT microPET imaging. Concurrently, we performed immunofluorescence staining for γH2AX in tumor tissues to establish a correlation between the uptake of 89Zr-anti-γH2AX-TAT and γH2AX expression. Results The surviving fraction 2 Gy (SF2) values of H460 and A549 indicating that A549 adenocarcinoma has higher radiosensitivity. The cell immunofluorescence experiment showed that the repair of γH2AX foci in H460 cells after irradiation was significantly higher than that in A549 cells, which also confirmed that A549 has higher radiosensitivity. The microPET imaging results showed the uptake of 89Zr-anti-γH2AX-TAT in the tumor of the A549 models after radiotherapy was higher than H460 models. The immunofluorescence staining of tumor tissue confirmed that the expression level of γH2AX was higher and the correlation with microPET imaging uptake was good. Conclusion 89Zr-anti-γH2AX-TAT allows PET imaging of radiosensitivity in lung cancer xenograft models, and is expected to become an early evaluation method for lung cancer radiosensitivity.

Abstract Background The radiation exposure of nuclear medicine personnel, especially concerning extremity doses, has been a significant focus over the past two decades. This study addresses the evolving practice of NM, particularly with the rise of radionuclide therapy and theranostic procedures, which involve a variety of radionuclides such as 68Ga, 177Lu, and 131I. Traditional studies have concentrated on common radioisotopes like 99mTc, 18F, and 90Y, but there is limited data on these radionuclides, which are more and more frequently used. This study, part of the European SINFONIA project, aims to fill this gap by providing new dosimetry data through a multicenter approach. The research monitors extremity doses to hands, eye lens doses, and whole-body doses in nuclear medicine staff handling 68Ga, 177Lu, and 131I. It examines the type of activities performed and the protective measures used. The study extrapolates measured doses to annual doses, comparing them with annual dose limits, and assesses the contribution of these specific procedures to the overall occupational dose of nuclear medicine personnel. Results Measurements were conducted from November 2020 to August 2023 across nine hospitals. The highest whole-body, eye lens and extremity doses were observed for 68Ga. Average maximum extremity doses, normalized per manipulated activity, were found of 6200 µSv/GBq, 30 µSv/GBq and 260 µSV/GBq for 68Ga, 177Lu and 131I, respectively. Average whole-body doses stayed below 60 µSv/GBq for all 3 isotopes and below 200 µSv/GBq for the eye lens dose. The variation in doses also depends on the task performed. For 68Ga there is a risk of reaching the annual dose limit for skin dose during synthesis and dispensing. Conclusions This study’s measurement campaigns across various European countries have provided new and extensive occupational dosimetry data for nuclear medicine staff handling 68Ga, 177Lu and 131I radiopharmaceuticals. The results indicate that 68Ga contributes significantly to the global occupational dose, despite its relatively low usage compared to other isotopes. Staff working in radiopharmacy hot labs, labeling and dispensing 177Lu contribute less to the finger dose compared to other isotopes.

Abstract Purpose This study aims to evaluate the accuracy of four kidney depth measurement methods—nuclear medicine tomography, nuclear medicine lateral scanning, ultrasound, and Tonnesen’s formula-based estimation—using CT measurements as the reference standard. Additionally, it investigates the feasibility of utilizing nuclear medicine tomography and lateral scanning for measuring kidney depth in 99mTc-DTPA renal dynamic imaging. Methods Hollow kidney phantoms mimicking the shape and volume of adult kidneys were 3D printed and filled with 99mTcO4 − solution. These phantoms were then subjected to lateral scanning and nuclear medicine tomography using CZT (cadmium-zinc-telluride) SPECT/CT to determine the optimal post-processing method. Forty patients who underwent renal dynamic imaging were recruited for the study. Renal depths were derived from ultrasound, lateral imaging, nuclear medicine tomography, formula-based estimation, and CT measurements. The renal depths obtained through these four methods were for correlation with CT-measured renal depths. Additionally, the absolute differences between renal depths obtained by each method and the CT standard were analyzed and compared across groups. Results Using kidney phantoms, nuclear medicine tomography images were processed with a Butterworth filter (cutoff frequency = 0.6), and renal outlines in lateral images was manually delineated. In the clinical validation phase, correlation coefficients indicated strong associations between renal depths measured by nuclear medicine tomography (left kidney: R = 0.885, P