Manual 3D Research Articles

Improved ground truth annotation by multimodal image registration from 3D ultrasound to histopathology for resected tongue carcinoma.

This study's objectives are (1) to investigate the registration accuracy from intraoperative ultrasound (US) to histopathological images, (2) to assess the agreement and correlation between measurements in registered 3D US and histopathology, and (3) to train a nnUNet model for automatic segmentation of 3D US volumes of resected tongue specimens. Ten 3D US volumes were acquired, including the corresponding digitalized histopathological images (n = 29). Based on corresponding landmarks, the registrations between 3D US and histopathology images were calculated and evaluated using the target registration error (TRE). Tumor thickness and resection margins were measured based on three annotations: (1) manual histopathological tumor annotation (HTA), manual 3D US tumor annotation, and (2) the HTA registered in the 3D US. The agreement and correlation were computed between the measurements based on the HTA and those based on the manual US and registered HTA in US. A deep-learning model with nnUNet was trained on 151 3D US volumes. Segmentation metrics quantified the model's performance. The median TRE was 0.42mm. The smallest mean difference was between registered HTA in US and histopathology with 2.16mm (95% CI - 1.31; 5.63) and a correlation of 0.924 (p < 0.001). The nnUNet predicted the tumor with a Dice similarity coefficient of 0.621, an average surface distance of 1.15mm, and a Hausdorff distance of 3.70mm. Multimodal image registration enabled the HTA's registration in the US images and improved the agreement and correlation between the modalities. In the future, this could be used to annotate ground truth labels accurately.

Comparison of automated with manual 3D qEASL assessment based on MR imaging in hepatocellular carcinoma treated with conventional TACE

Comparison of automated with manual 3D qEASL assessment based on MR imaging in hepatocellular carcinoma treated with conventional TACE

Automated monitoring of tooth wear progression using AI on intraoral scans

ObjectivesThis study aimed to develop and evaluate a fully automated method for visualizing and measuring tooth wear progression using pairs of intraoral scans (IOSs) in comparison with a manual protocol. MethodsEight patients with severe tooth wear progression were retrospectively included, with IOSs taken at baseline and 1-year, 3-year, and 5-year follow-ups. For alignment, the automated method segmented the arch into separate teeth in the IOSs. Tooth pair registration selected tooth surfaces that were likely unaffected by tooth wear and performed point set registration on the selected surfaces. Maximum tooth profile losses from baseline to each follow-up were determined based on signed distances using the manual 3D Wear Analysis (3DWA) protocol and the automated method. The automated method was evaluated against the 3DWA protocol by comparing tooth segmentations with the Dice-Sørensen coefficient (DSC) and intersection over union (IoU). The tooth profile loss measurements were compared with regression and Bland-Altman plots. Additionally, the relationship between the time interval and the measurement differences between the two methods was shown. ResultsThe automated method completed within two minutes. It was very effective for tooth instance segmentation (826 teeth, DSC = 0.947, IoU = 0.907), and a correlation of 0.932 was observed for agreement on tooth profile loss measurements (516 tooth pairs, mean difference = 0.021mm, 95% confidence interval = [-0.085, 0.138]). The variability in measurement differences increased for larger time intervals. ConclusionsThe proposed automated method for monitoring tooth wear progression was faster and not clinically significantly different in accuracy compared to a manual protocol for full-arch IOSs. Clinical significanceGeneral practitioners and patients can benefit from the visualization of tooth wear, allowing quantifiable and standardized decisions concerning therapy requirements of worn teeth. The proposed method for tooth wear monitoring decreased the time required to less than two minutes compared with the manual approach, which took at least two hours.

Evaluation of automatic cochlear dimension measurement using ALPACA: a comparative study

Background Cochlear dimension measurements are critical in diagnosing and managing congenital sensorineural hearing loss. Objectives To evaluate the feasibility and reliability of an automated landmark approach for measuring cochlear dimensions (A-, B- and H-values). Material and Methods Cochlear parameters from 100 patients were measured by MPR, manual three-dimensional and ALPACA. We assessed intra- and inter-observer reliability as well as inter-method reliability. Statistical analyses were conducted to detect differences between the right and left ears, as well as to assess the relevance of the values obtained using ALPACA. Results All A-, B-, and H-values measured by the various methods showed a high intra-observer reliability with intra-class correlation coefficients (ICC) ranging from 0.70 to 0.99, and values gained by ALPACA reaching the highest ICC. Inter-method reliability was at a good level with ICC ranging from 0.51 to 0.86. There were no significant differences between the right and left ears’ measured values. Obvious positive correlations existed among cochlear dimensions measured by ALPACA. Conclusions and Significance The ALPACA method can be used to measure cochlear dimensions. Values obtained by the method demonstrate high reliability and consistency with a significant reduction in intra-observer variability compared to results from conventional MPR and manual 3D measurements.

3D Echocardiographic Assesment of Left Ventricle Size and Function with Automated Adaptive Software in Patients with Right Heart Dominant

Introduction : Echocardiography is a fundamental tool for assessing cardiac chamber size and function, with evolving technologies like real-time three-dimensional echocardiography (3DE) and automated quantification software offering new possibilities. This study aims to validate left ventricular (LV) measurements obtained through automated quantification software against manual 3DE and 2D measurements, explore the relationship between these measurement techniques, and compare their reproducibility and analysis time. Methods : A total of 60 patients with uncorrected severe mitral stenosis (MS) and atrial septal defect (ASD) underwent echocardiography. Automated and manual 3DE measurements were compared, with subgroup analysis for software performance. Analysis times were also assessed. Results : The automated quantification software did not work in 16 patients, with notable differences in tricuspid regurgitation parameters. Automated 3DE measurements yielded larger LV volumes than manual 3DE measurements, while LV ejection fraction (LVEF) measurements were smaller. Good correlations were observed, but agreement analysis revealed significant differences between the two methods. The use of automated software significantly reduced analysis time. Conclusions : Automated quantification software can effectively measure LV parameters in patients with MS and ASD, significantly reducing analysis time. However, manual methods may still be necessary in cases with structural changes or unique anatomical conditions, emphasizing the importance of selecting the appropriate measurement technique for specific patient populations. Keywords: 3D Echocardiography, Automated Adaptive Software, Cardiac Imaging

Current Issues Related to Anthropometry in Engineering

Anthropos and Metrikos both mean "human" in Greek, which is where the term anthropometry comes from. Anthropometry is employed in a variety of fields, including apparel and textile design. For anthropometric evaluations, a current, thorough, and community-specific anthropometric normative-reference standard is necessary. In health care, ergonomic design is utilised to reduce pain and illness. Misalignments between humans and machines result in pain, accidents, biomechanical stress, tiredness, and musculoskeletal injuries. Designing for the anthropometrics of end users improves long-term viability. The human body comes in a wide range of sizes and shapes. Manual measurement and 3D scanning procedures, on the other hand, are inefficient and expensive, making precise body measurements difficult. This is especially true for head-worn medical devices. Manual measurement and 3D scanning are inefficient and expensive, making precise body measurements difficult. Grip strength and force were determined using hand measurements. Anthropometric parameter estimate is more precise when a 3D model is used to boost pinnae features. While numerous anatomical features have been gathered to aid in the ergonomic design of wearable devices, there is still a lot more work to be done. In three dimensions, the segment masses and torso Centre of Mass (COM) may be calculated. Researchers tracking mobility would benefit greatly from the ability to locate the body COM using a weighted sum of segment masses. Design features such as comfort and usefulness are crucial. Ergonomic characteristics like taller seats with front slopes and saddle chairs encourage good posture, movement, and alternation. In the creation of wearable technologies, using outdated anthropometric reference standards may be insufficient. This review discuses common issues related to anthropometry in engineering which includes the human body, anthropometric parameters, anthropometric measurements, the force plate method, ergonomic design, and body dimension. The goal is to give a broad overview of the subject.

Evidence for Simultaneous Muscle Atrophy and Hypertrophy in Response to Resistance Training in Humans.

Human skeletal muscle has the profound ability to hypertrophy in response to resistance training (RT). However, this has a high energy and protein cost and is presumably mainly restricted to recruited muscles. It remains largely unknown what happens with nonrecruited muscles during RT. This study investigated the volume changes of 17 recruited and 13 nonrecruited muscles during a 10-wk single-joint RT program targeting upper arm and upper leg musculature. Muscle volume changes were measured by manual or automatic 3D segmentation in 21 RT novices. Subjects ate ad libitum during the study and energy and protein intake were assessed by self-reported diaries. Posttraining, all recruited muscles increased in volume (range: +2.2% to +17.7%, P < 0.05), whereas the nonrecruited adductor magnus (mean: -1.5% ± 3.1%, P = 0.038) and soleus (-2.4% ± 2.3%, P = 0.0004) decreased in volume. Net muscle growth ( r = 0.453, P = 0.045) and changes in adductor magnus volume ( r = 0.450, P = 0.047) were positively associated with protein intake. Changes in total nonrecruited muscle volume ( r = 0.469, P = 0.037), adductor magnus ( r = 0.640, P = 0.002), adductor longus ( r = 0.465, P = 0.039), and soleus muscle volume ( r = 0.481, P = 0.032) were positively related to energy intake. When subjects were divided into a HIGH or LOW energy intake group, overall nonrecruited muscle volume (-1.7% ± 2.0%), adductor longus (-5.6% ± 3.7%), adductor magnus (-2.8% ± 2.4%), and soleus volume (-3.7% ± 1.8%) decreased significantly ( P < 0.05) in the LOW but not the HIGH group. To our knowledge, this is the first study documenting that some nonrecruited muscles significantly atrophy during a period of RT. Our data therefore suggest muscle mass reallocation, that is, that hypertrophy in recruited muscles takes place at the expense of atrophy in nonrecruited muscles, especially when energy and protein availability are limited.

Multiparametric prenatal imaging characterization of fetal brain edema in Chiari II malformation might help to select candidates for fetal surgery

ObjectiveTo identify brain edema in fetuses with Chiari II malformation using a multiparametric approach including structural T2-weighted, diffusion tensor imaging (DTI) metrics, and MRI-based radiomics.MethodsA single-center retrospective review of MRI scans obtained in fetuses with Chiari II was performed. Brain edema cases were radiologically identified using the following MR criteria: brain parenchymal T2 prolongation, blurring of lamination, and effacement of external CSF spaces. Fractional anisotropy (FA) values were calculated from regions of interest (ROI), including hemispheric parenchyma, internal capsule, and corticospinal tract, and compared group-wise. After 1:1 age matching and manual single-slice 2D segmentation of the fetal brain parenchyma using ITK-Snap, radiomics features were extracted using pyradiomics. Areas under the curve (AUCs) of the features regarding discriminating subgroups were calculated.ResultsNinety-one fetuses with Chiari II underwent a total of 101 MRI scans at a median gestational age of 24.4 weeks and were included. Fifty scans were visually classified as Chiari II with brain edema group and showed significantly reduced external CSF spaces compared to the nonedema group (9.8 vs. 18.3 mm, p < 0.001). FA values of all used ROIs were elevated in the edema group (p < 0.001 for all ROIs). The 10 most important radiomics features showed an AUC of 0.81 (95%CI: 0.71, 0.91) for discriminating between Chiari II fetuses with and without edema.ConclusionsBrain edema in fetuses with Chiari II is common and radiologically detectable on T2-weighted fetal MRI sequences, and DTI-based FA values and radiomics features provide further evidence of microstructure differences between subgroups with and without edema.Clinical relevance statementA more severe phenotype of fetuses with Chiari II malformation is characterized by prenatal brain edema and more postnatal clinical morbidity and disability. Fetal brain edema is a promising prenatal MR imaging biomarker candidate for optimizing the risk-benefit evaluation of selection for fetal surgery.Key PointsBrain edema of fetuses prenatally diagnosed with Chiari II malformation is a common, so far unknown, association.DTI metrics and radiomics confirm microstructural differences between the brains of Chiari II fetuses with and without edema.Fetal brain edema may explain worse motor outcomes in this Chiari II subgroup, who may substantially benefit from fetal surgery.Graphical

Classification, registration and segmentation of ear canal impressions using convolutional neural networks

Today, fitting bespoke hearing aids involves injecting silicone into patients’ ears to produce ear canal molds. These are subsequently 3D scanned to create digital ear canal impressions. However, before digital impressions can be used they require a substantial amount of effort in manual 3D editing. In this article, we present computational methods to pre-process ear canal impressions. The aim is to create automation tools to assist the hearing aid design, manufacturing and fitting processes as well as normalizing anatomical data to assist the study of the outer ear canal’s morphology. The methods include classifying the handedness of the impression into left and right ear types, orienting the geometries onto the same coordinate system sense, and removing extraneous artifacts introduced by the silicone mold. We investigate the use of convolutional neural networks for performing these semantic tasks and evaluate their accuracy using a dataset of 3000 ear canal impressions. The neural networks proved highly effective at performing these tasks with 95.8% adjusted accuracy in classification, 92.3% within 20° angular error in registration and 93.4% intersection over union in segmentation.

Automatic Vertebral Rotation Angle Measurement of 3D Vertebrae Based on an Improved Transformer Network.

The measurement of vertebral rotation angles serves as a crucial parameter in spinal assessments, particularly in understanding conditions such as idiopathic scoliosis. Historically, these angles were calculated from 2D CT images. However, such 2D techniques fail to comprehensively capture the intricate three-dimensional deformities inherent in spinal curvatures. To overcome the limitations of manual measurements and 2D imaging, we introduce an entirely automated approach for quantifying vertebral rotation angles using a three-dimensional vertebral model. Our method involves refining a point cloud segmentation network based on a transformer architecture. This enhanced network segments the three-dimensional vertebral point cloud, allowing for accurate measurement of vertebral rotation angles. In contrast to conventional network methodologies, our approach exhibits notable improvements in segmenting vertebral datasets. To validate our approach, we compare our automated measurements with angles derived from prevalent manual labeling techniques. The analysis, conducted through Bland-Altman plots and the corresponding intraclass correlation coefficient results, indicates significant agreement between our automated measurement method and manual measurements. The observed high intraclass correlation coefficients (ranging from 0.980 to 0.993) further underscore the reliability of our automated measurement process. Consequently, our proposed method demonstrates substantial potential for clinical applications, showcasing its capacity to provide accurate and efficient vertebral rotation angle measurements.

Calculation of the Forearm and Hand Three-Dimensional Anthropometry Based on Two-Dimensional Image Feature Extraction: An Approach for Cock-up Splint Design.

An alternative to both the time-consuming traditional and the expensive three-dimensional (3D) methods for splint design is to use two-dimensional (2D) images. The present study utilized image processing to achieve an automatic and practical method of anthropometry measurement to design and build a personalized and remote cock-up splint. This method is applicable for patients unable to personally attend clinic appointments. The defined landmarks of the cock-up splint of 100 adult participants were measured manually. Each individual had a 2D image taken of their upper limb using a customized imaging device. The 2D image portions that corresponded to the manual measurements were then identified, and their sizes were retrieved in pixels using MATLAB software. To find equations between manual 3D measurements and 2D image processing ones, multiple linear regression analysis was performed on landmark variables. We were able to determine equations to estimate manual dimensions based on 2D image data. In the men's group, we could predict the third finger length, forearm circumference at three levels, and the largest forearm circumference. In the women's group, in addition to variables predicted for men, hand circumference at the distal palmar crease and first web levels, as well as arm circumference, could be predicted using the identified equations. Based on the findings, 2D image processing could be an appropriate method for designing personalized cock-up splints.

Application of Texture and Volume Model Analysis to Dedicated Axillary High-resolution 3D T2-weighted MR Imaging: A Novel Method for Diagnosing Lymph Node Metastasis in Patients with Clinically Node-negative Breast Cancer.

To evaluate the effectiveness of the texture analysis of axillary high-resolution 3D T2-weighted imaging (T2WI) in distinguishing positive and negative lymph node (LN) metastasis in patients with clinically node-negative breast cancer. Between December 2017 and May 2021, 242 consecutive patients underwent high-resolution 3D T2WI and were classified into the training (n = 160) and validation cohorts (n = 82). We performed manual 3D segmentation of all visible LNs in axillary level I to extract the texture features. As the additional parameters, the number of the LNs and the total volume of all LNs for each case were calculated. The least absolute shrinkage and selection operator algorithm and Random Forest were used to construct the models. We constructed the texture model using the features from the LN with the largest least axis length in the training cohort. Furthermore, we constructed the 3 models combining the selected texture features of the LN with the largest least axis length, the number of LNs, and the total volume of all LNs: texture-number model, texture-volume model, and texture-number-volume model. As a conventional method, we manually measured the largest cortical diameter. Moreover, we performed the receiver operating curve analysis in the validation cohort and compared area under the curves (AUCs) of the models. The AUCs of the texture model, texture-number model, texture-volume model, texture-number-volume model, and conventional method in the validation cohort were 0.7677, 0.7403, 0.8129, 0.7448, and 0.6851, respectively. The AUC of the texture-volume model was higher than those of other models and conventional method. The sensitivity, specificity, positive predictive value, and negative predictive value of the texture-volume model were 90%, 69%, 49%, and 96%, respectively. The texture-volume model of high-resolution 3D T2WI effectively distinguished positive and negative LN metastasis for patients with clinically node-negative breast cancer.

Skeletal facial asymmetry: reliability of manual and artificial intelligence-driven analysis.

To compare artificial intelligence (AI)-driven web-based platform and manual measurements for analysing facial asymmetry in craniofacial CT examinations. The study included 95 craniofacial CT scans from patients aged 18-30 years. The degree of asymmetry was measured based on AI platform-predefined anatomical landmarks: sella (S), condylion (Co), anterior nasal spine (ANS), and menton (Me). The concordance between the results of automatic asymmetry reports and manual linear 3D measurements was calculated. The asymmetry rate (AR) indicator was determined for both automatic and manual measurements, and the concordance between them was calculated. The repeatability of manual measurements in 20 randomly selected subjects was assessed. The concordance of measurements of quantitative variables was assessed with interclass correlation coefficient (ICC) according to the Shrout and Fleiss classification. Erroneous AI tracings were found in 16.8% of cases, reducing the analysed cases to 79. The agreement between automatic and manual asymmetry measurements was very low (ICC < 0.3). A lack of agreement between AI and manual AR analysis (ICC type 3 = 0) was found. The repeatability of manual measurements and AR calculations showed excellent correlation (ICC type 2 > 0.947). The results indicate that the rate of tracing errors and lack of agreement with manual AR analysis make it impossible to use the tested AI platform to assess the degree of facial asymmetry.

First-in-human real-time AI-assisted instrument deocclusion during augmented reality robotic surgery.

The integration of Augmented Reality (AR) into daily surgical practice is withheld by the correct registration of pre-operative data. This includes intelligent 3D model superposition whilst simultaneously handling real and virtual occlusions caused by the AR overlay. Occlusions can negatively impact surgical safety and as such deteriorate rather than improve surgical care. Robotic surgery is particularly suited to tackle these integration challenges in a stepwise approach as the robotic console allows for different inputs to be displayed in parallel to the surgeon. Nevertheless, real-time de-occlusion requires extensive computational resources which further complicates clinical integration. This work tackles the problem of instrument occlusion and presents, to the authors' best knowledge, the first-in-human on edge deployment of a real-time binary segmentation pipeline during three robot-assisted surgeries: partial nephrectomy, migrated endovascular stent removal, and liver metastasectomy. To this end, a state-of-the-art real-time segmentation and 3D model pipeline was implemented and presented to the surgeon during live surgery. The pipeline allows real-time binary segmentation of 37 non-organic surgical items, which are never occluded during AR. The application features real-time manual 3D model manipulation for correct soft tissue alignment. The proposed pipeline can contribute towards surgical safety, ergonomics, and acceptance of AR in minimally invasive surgery.

Longitudinal PET/CT Imaging with Iodine ( 124I) Evuzamitide Reveals Organ Response to Plasma Cell Immunotherapy in a Patient with AL Amyloidosis

Background:Iodine-124-evuzamitide is a novel amyloidophilic peptide (p5+14), labeled with iodine-124, for detecting amyloid by positron emission/x-ray computed tomographic (PET/CT) imaging ( Pharmaceuticals 2023 Apr 21;16(4):629). PET is an inherently quantitative modality and thus 124I-evuzamitide may be useful for monitoring disease progression and response to therapy. Amyloid deposits can impact any organ in patients with light chain-associated amyloidosis (AL); thus, tissue-specific changes in amyloid load, based on PET/CT imaging, may be informative. Currently, response to therapy is assessed by anatomic imaging and measurement of serum or urinary biomarkers. However, the correlation between these metrics and concomitant changes in amyloid load remains enigmatic. Here, we report a case of a patient with AL amyloidosis, on long-term daratumumab therapy, who underwent longitudinal 124I-evuzamitide PET/CT imaging over 4 years (NCT03678259 and NCT05968846). Patient and Methods: A 70-year-old male presented with abnormal liver function tests, notably an elevated serum alkaline phosphatase (ALK) of 465 IU/L. Biopsies of both the liver and celiac nodes revealed the characteristic apple-green birefringence of Congo red stain, indicating the presence of amyloid. The patient began daratumumab immunotherapy 14 months prior to his enrollment in the 124I-evuzamitide imaging study and over the 4-year course of serial imaging. During this time, regular serial serum biomarkers were evaluated as standard of care. PET/CT images were acquired at 0, 23, and 45 months. For each imaging session, the patient received 2 mCi iodine-124-labeled tracer via intravenous injection and was imaged at 5 h post injection. Image data were assessed for visual uptake of radiotracer and quantified by manual 2D region-of-interest analysis where the semi-quantitative mean standard uptake value ratio (SUVR mean) was calculated using blood pool as the reference tissue. Results: Over the 45 months of evaluation, there was a 59% and 73% reduction in 124I-evuzamitide SUVR in the liver and spleen. This was accompanied by decreases in the weight-scaled organ volume (cc/kg) for both the liver (15.2%) and spleen (30.0%) based on segmentation of the organ volume from CT images. This reduction in radiotracer uptake coincided with a sustained decrease in serum FLC, from 38.3 mg/L to 19.1 mg/L, and a positive liver response, where ALK levels dropped from ~200 IU/L to ~120 IU/L. In contrast, renal radiotracer uptake increased slightly in the context of stable creatinine levels, and a modest decline in eGFR. Cardiac uptake of 124I-evuzamitide remained positive and relatively stable, concordant with serum NT-proBNP levels. These data suggest that organ-specific amyloid response, in the context of a sustained hematologic response, may occur independently and at different rates. Conclusion: Previous reports have demonstrated the resolution of AL amyloid. However, this is the first report using an amyloid-binding radiotracer, capable of visualizing all major organs including the heart, demonstrating the complex pattern of organ response and regression of AL amyloid in the context of concurrent biomarker improvement and changes in organ volume. PET/CT imaging using 124I-evuzamitide may, therefore, play a valuable role in both diagnosing amyloidosis and monitoring changes in organ-specific amyloid load. Additional longitudinal imaging studies are needed to support this clinical application.

CT Attenuation of Hepatic Pancreatic Cancer Metastases Correlates with Prognostically Detrimental Metastatic Necrosis

Percutaneous CT-guided biopsy is a frequently performed procedure for the confirmation and molecular workup of hepatic metastases of pancreatic ductal adenocarcinoma (PDAC). Tumor necrosis of primary PDAC has shown a negative prognostic impact in recent studies. This study aims to examine predictability in CT scans and the prognostic impact of necrosis in hepatic metastases of PDAC. In this tertiary-center retrospective cohort study, we included 36 patients with hepatic metastases of PDAC who underwent CT-guided hepatic biopsies. Normalized attenuation of the biopsied metastasis was determined in venous phase contrast-enhanced planning scans obtained prior to biopsy by automatic, threshold-based 3D segmentation and manual, blinded 2D segmentation. A board-certified pathologist specialized in hepatic pathology histologically quantified the tumor necrosis and cellularity of the biopsy cylinders. We found a significant inverse-linear correlation between normalized attenuation and the fraction of necrosis (Pearson’s r = 0.51, p &lt; 0.001 for automatic 3D segmentation or Pearson’s r = 0.52, p &lt; 0.001 for manual 2D segmentation), whereas no correlation was found with tumor cellularity. Additionally, we discovered that patients with a fraction of necrosis ≥ 20% in metastases had a significantly shorter overall survival (p &lt; 0.035). In summary, tumor necrosis of PDAC metastases can be estimated from contrast-enhanced CT scans, which could help to improve biopsy sample pattern planning. In addition, liver metastatic necrosis may serve as a prognostic biomarker in PDAC.

NIMG-52. CORRELATION OF BIDIMENSIONAL AND VOLUMETRIC TUMOR SIZING IN NEWLY DIAGNOSED AND RECURRENT GLIOBLASTOMA

Abstract BACKGROUND Glioblastoma (GBM) is the most common malignant primary nervous system tumor and remains incurable with a poor prognosis despite current therapy. The standard for monitoring response to treatment, as defined by the Response Assessment in Neuro-Oncology (RANO) criteria, relies on a bidimensional (2D) measurement product of T1-gadolinium enhancing disease. However, due to the variability of bidimensional tumor characterization, there is considerable interest in volumetric segmentation to assess tumor burden, which could be implemented using machine learning models offering workflow automatization. METHODS In this study, we evaluate a commercially available automated tumor segmentation tool and correlate its volumetric output to the manual assessment of bidimensional 2D enhancing tumor burden by experts. MRI examinations during systemic treatment for two retrospective cohorts of patients with either newly diagnosed (nGBM) or recurrent GBM (rGBM) were assessed. The 2D diameter product in cm^2 of enhancing tumor was determined by blinded readers and volumetric segmentations in cm^3 were automatically generated. Spearman's correlation between the manual 2D and automated volume measurements was calculated for each cohort. RESULTS 315 patients with nGBM, and 482 with rGBM were evaluated, comprising 3073 total brain MRIs in the nGBM cohort and 2439 MRIs in the rGBM cohort. Spearman's correlation between the manual 2D and automated volumetric measurements was 0.7463 (0.730, 0.762) in the nGBM cohort and 0.8598 (0.849, 0.870) in the rGBM cohort. CONCLUSION Automated segmentation tools have the potential to revolutionize radiology workflows and increase sensitivity to subtle changes on imaging. However, the differential performance of this volumetric assessment confirms the need for further refinement and customization of such automated tools to account for tumor- and patient-specific factors.

Longitudinal evaluation of cardiac and extracardiac amyloid load in patients with AL and ATTR amyloidosis, measured by 124I-AT-01 PET/CT imaging

Abstract Background The amyloid imaging agent, 124I-AT-01 (124I-p5+14), is being developed for the diagnosis and monitoring of amyloidosis, of any type, by PET/CT imaging (1,2). PET/CT is an intrinsically quantitative imaging modality, and this reagent could provide a facile, first-line method for the diagnosis of amyloidosis as well as permit quantitative longitudinal imaging for monitoring progression or regression of disease, notably in the heart, of all amyloid patients. Here we describe an interim analysis of a case series of AL and ATTR patients who have been imaged at least twice with 124I-AT-01 with a minimum of 12 months between imaging (NCT designation pending). Radiotracer uptake has been quantified for the heart, liver, spleen and kidneys and changes in uptake reported. Purpose The goal was to quantitatively assess changes in organ-specific radiotracer uptake in AL and ATTR patients with previous cardiac uptake using manual region-of-interest methods. Methods The study will enroll patients with AL (n=10) and ATTR (n=10) who were previously imaged more than 12 months prior and who had positive uptake of 124I-AT-01 in the heart. To date, six patients have been imaged twice and one has had three evaluations since 2019. Patients received 37 or 74 MBq 124I-AT-01 and PET/CT imaging was performed at ∼5 h post injection. A fully manual 2D region of interest analysis was performed on three representative image views of the heart in the transaxial plane as well as the liver, spleen and kidneys. The blood pool was used as a reference tissue to determine standard uptake value ratios (SUVRmean). Changes in cardiac uptake of radiotracer were compared with contemporaneous NTproBNP measurements. Results The PET images were of high quality and readily interpretable and quantifiable (Figure 1A). In this early analysis of the data, both AL (n=2) and ATTR (n=4) have been evaluated. The mean time between first and second imaging was 30.3 ± 8.9 months. In the patients with ATTR amyloidosis, there was an average of a 7.9 ± 10% decrease in cardiac uptake of 124I-AT-01 after an average of 32.5 months from the first scan, in patients on silencers or stabilizers. In the AL patients, one had a 10% decrease and the other a 12% decrease in heart uptake. In some, these changes correlated with serum NTproBNP levels. A notable decrease in 124I-AT-01 binding in both AL patients was observed in the liver (45% and 59%) and spleen (75% and 73%) with one example shown in Figure 1B. No cases of increased radiotracer uptake were observed in the heart, consistent with these patients being stabilised with standard of care therapy. Conclusion Changes in cardiac amyloid load, based on differential uptake of radiotracer, can be seen by longitudinal imaging and quantified using 124I-AT-01 PET/CT imaging. This technique may play a valuable role not only in the early and accurate diagnosis of amyloidosis but also for monitoring changes in organ-specific amyloid load.

Structural and Functional Cardiac Parameters in Patients with AL Amyloidosis Correlate with Uptake of the Amyloidophilic Radiotracer Iodine ( 124I) Evuzamitide

Background: The deposition of fibrillar aggregates of monoclonal free light chains in the heart is a characteristic feature of light chain associated (AL) amyloidosis. Cardiac amyloid is the major cause of morbidity and mortality in these patients. Structural and functional sequelae of cardiac amyloidosis can be appreciated clinically using echocardiography, cardiac magnetic resonance imaging, and measurement of serum NT-proBNP and troponins. These measures are not particularly amyloid-specific, and the correlation between parameters derived from these evaluations and amyloid burden remain enigmatic. The iodine-124 labeled peptide (p5+14), iodine ( 124I) evuzamitide, is a novel radiotracer that is being evaluated for the detection of systemic amyloidosis, of any type, by PET/CT imaging. As an amyloid binding peptide, this radiotracer has the potential to serve as a first line diagnostic agent capable of providing whole body semi-quantitative estimation of organ-specific amyloid load. Nascent studies of the relationship between 124I-evuzamitide uptake and established clinical parameters in patients with amyloidosis are underway. Here we report a single site, open label pilot study of 18 ( n=18) patients with AL ( n=8) and ATTR amyloidosis ( n=10) that evaluates the cardiac uptake of 124I-evuzamitide with contemporaneous echocardiographic and serum biomarkers (NCT05968846). Methods: The data described herein was collected as part of an open label single site repeat imaging study that plans to enroll up to 20 ( n=20) patients with AL ( n=10) and ATTR ( n=10) amyloidosis. To date, eight ( n=8) patients with AL and ten ( n=10) with ATTR amyloidosis have undergone 124I-evuzamitide PET/CT imaging with contemporaneous transthoracic echocardiography and assessment of serum NTproBNP within ~30 h of imaging. Patients received 37 or 74 MBq 124I-evuzamitide, and PET/CT imaging was performed at ~5 h post injection. Images were interpreted by a single reviewer, experienced in evaluating this tracer, for positive cardiac uptake. A fully manual 2D region of interest (ROI) analysis was performed encompassing the free left ventricular (LV) wall, LV lumen and interventricular septum (IVS). Blood pool was used as a reference tissue to determine standard uptake value ratios (SUVR mean) and to control for the rate of tracer clearance from the central compartment. Cardiac uptake of radiotracer was compared with free LV wall thickness (cm), IVS thickness (cm), global longitudinal strain (GLS, %), and serum NT-proBNP (pg/mL) measurements. Pearson and Spearman correlations were used to test for associations between variables. Results: Patients with AL amyloidosis were 2012 Mayo Stage I ( n=2/8) or Stage II ( n=6/8). The mean serum NTproBNP was 672.9±762.4 pg/mL (min=98, max=2327). With singular exception, all patients with AL amyloidosis had visually evident cardiac uptake of 124I-evuzamitide in the PET/CT images. In patients with AL amyloidosis ( n=8), the SUVR mean (encompassing the LV, lumen and IVS) correlated strongly with LV thickness (cm) (Pearson r=0.83, p=0.011) and GLS (%) (Pearson r=0.74, p=0.037), but not the IVS thickness (cm) (Pearson r=0.57, p=0.142). In contrast, in patients with ATTR ( n=10), there was no significant correlation of SUVR mean with GLS ( p=0.395), but a moderate significant correlation of SUVR mean with the LV ( p=0.037) and IVS ( p=0.017) thickness was observed. Similarly, in this pilot cohort, we observed a strong positive correlation between serum NTproBNP and cardiac SUVR mean (Pearson r=0.81, p=0.015), but not for patients with ATTR amyloidosis (Pearson r=0.58, p=0.079). Conclusion: Serum NTproBNP is a validated and qualified measure of overall survival for patients with AL amyloidosis (PMID: 27416985). Global longitudinal strain, with or without inclusion of other structural parameters such as left atrial volume, is a strong predictor of survival in patients with AL amyloidosis (PMID: 29111123, PMID: 37143609). PET/CT imaging using 124I-evuzamitide is a promising technique for diagnosing and monitoring AL and other types of amyloidosis. In light of these early results that demonstrate a strong relationship between validated metrics of all cause mortality in patients with AL, larger studies should seek to evaluate similar relationships with some metric of 124I-evuzamitide uptake in the heart, and indeed other organs.

Systemic Amyloid Response in Patients with AL Amyloidosis Assessed By Serial Iodine ( 124I) Evuzamitide PET/CT Imaging

Background: Immunoglobulin light chain (AL) amyloidosis is a systemic disorder. Fibrillar aggregates of monoclonal free light chains, or fragments thereof, can deposit in any organ or tissue. Invariably, more than one anatomic site is involved, including the heart, liver, spleen, kidneys, pancreas, nerves, gastrointestinal tract and vasculature. Cardiac and renal amyloidosis are clinically most ominous; however, amyloid in other sites significantly impacts quality of life and may cause other heretofore unappreciated clinical sequelae. This is also true of the other 17 types of systemic amyloidosis. The degree of amyloid distribution and the tissue-specific amyloid load can only be achieved by nuclear imaging. Moreover, monitoring changes in amyloid load in response to therapy would benefit from whole body quantitative molecular imaging techniques. Here we report a pilot study of eight ( n=8) patients with AL amyloidosis who underwent serial PET/CT imaging using a novel amyloid-binding, iodine-124-labelled peptide, designated iodine-124-evuzamitide. Data from a cohort of ten ( n=10) patients with transthyretin associated (ATTR) amyloidosis are also described for comparison (NCT05968846). Methods: The study plans to enroll 20 ( n=20) patients with AL ( n=10) and ATTR ( n=10) amyloidosis who were previously imaged more than 12 months prior and who had positive uptake of 124I-evuzamitide in the heart. To date, eight ( n=8) patients with AL and ten ( n=10) with ATTR amyloidosis have undergone repeat imaging since 2019. Between imaging sessions, patients with AL received immunotherapy ( n=2/8) or were untreated ( n=6/8). Patients were administered 37 or 74 MBq 124I-evuzamitide, and PET/CT imaging was performed at ~5 h post injection. Clinical chemistry parameters were collected contemporaneously. Images were interpreted by a single reviewer, experienced in evaluating this tracer, for positive uptake. A fully manual 2D region of interest (ROI) analysis was performed on three representative image views of the heart in the transaxial plane as well as the liver, spleen, and kidneys. The blood pool was used as a reference tissue to determine standard uptake value ratios (SUVR mean). Cardiac uptake of radiotracer was compared with serum NT-proBNP measurements. Pearson and Spearman correlations were used to test for associations. Results: The mean time between imaging sessions for patients with AL amyloidosis was 3.21±0.95 years and 2.96±0.87 years for the entire cohort. In the AL amyloid cohort, 88% ( n=7/8) had a reduction in cardiac radiotracer uptake. In one ( n=1) patient, a 92.9% increase in cardiac uptake was seen, which was readily visible in scaled maximum intensity PET images. In this patient, the liver, spleen, and kidney uptake also increased. In contrast to the heart, renal uptake of the radiotracer was increased in 62.5% ( n=5/8) of patients with AL, with three ( n=3) patients showing a &amp;gt;20% increase in the SUVR mean. A strongly positive, significant correlation between the change in the liver and spleen uptake was observed (Pearson r=0.88, p=0.004). The change in the cardiac radiotracer uptake correlated strongly with that of the spleen (Pearson r=0.74, p=0.04). For the entire cohort, AL and ATTR patients ( n=18), there was a significant moderate correlation between the change in cardiac SUVR mean and change in single point serum NTproBNP concentration (Spearman rho=0.57, p=0.01). Conclusion: AL amyloidosis, and indeed all types of systemic amyloid disease, is a complex systemic disorder. The amyloid response to treatment, or disease progression, remains enigmatic as compared to the hematologic and biomarker responses. Appreciating the changes in amyloid load may not only improve clinical management but may also illuminate aspects of pathogenesis. PET/CT imaging using 124I-evuzamitide may, therefore, play a valuable role in understanding, diagnosing, and monitoring changes in organ-specific amyloid load and amyloid response. Additional longitudinal imaging studies are needed to investigate these possibilities further.