Positron Emission Tomography (PET) in Oncology

PET imaging of sodium-glucose cotransporters (SGLTs): Unveiling metabolic dynamics in diabetes and oncology

The advent of positron emission tomography (PET) imaging utilizing sodium-glucose cotransporter (SGLT) substrates has opened a new frontier in understanding metabolic alterations in various disease states. SGLT isoforms, notably SGLT2, play critical roles in glucose regulation and have been therapeutic targets in diabetes management. SGLT-specific radiotracers, such as alpha-methyl-4-deoxy-4-18F-fluoro-d-glucopyranoside (Me-4FDG), offer opportunities beyond conventional 18F-2-fluoro-2-deoxy-d-glucose (2-FDG) imaging, permitting targeted evaluation of SGLT activity. This review summarizes recent advances in PET imaging for SGLT, highlighting its impact on assessing the pharmacodynamics of SGLT inhibitors, exploring metabolism in diabetics, and staging various cancers. The clinical implications of these findings suggest potential shifts in therapeutic approaches and diagnostic accuracy, providing a comprehensive understanding of the physiological and pathological relevance of SGLTs.

Joint segmentation of tumors in 3D PET-CT images with a network fusing multi-view and multi-modal information

Objective. Joint segmentation of tumors in positron emission tomography-computed tomography (PET-CT) images is crucial for precise treatment planning. However, current segmentation methods often use addition or concatenation to fuse PET and CT images, which potentially overlooks the nuanced interplay between these modalities. Additionally, these methods often neglect multi-view information that is helpful for more accurately locating and segmenting the target structure. This study aims to address these disadvantages and develop a deep learning-based algorithm for joint segmentation of tumors in PET-CT images.Approach. To address these limitations, we propose the Multi-view Information Enhancement and Multi-modal Feature Fusion Network (MIEMFF-Net) for joint tumor segmentation in three-dimensional PET-CT images. Our model incorporates a dynamic multi-modal fusion strategy to effectively exploit the metabolic and anatomical information from PET and CT images and a multi-view information enhancement strategy to effectively recover the lost information during upsamping. A Multi-scale Spatial Perception Block is proposed to effectively extract information from different views and reduce redundancy interference in the multi-view feature extraction process.Main results. The proposed MIEMFF-Net achieved a Dice score of 83.93%, a Precision of 81.49%, a Sensitivity of 87.89% and an IOU of 69.27% on the Soft Tissue Sarcomas dataset and a Dice score of 76.83%, a Precision of 86.21%, a Sensitivity of 80.73% and an IOU of 65.15% on the AutoPET dataset.Significance. Experimental results demonstrate that MIEMFF-Net outperforms existing state-of-the-art models which implies potential applications of the proposed method in clinical practice.

Baseline and interim 18F-FDG PET/CT metabolic parameters predict the efficacy and survival in patients with diffuse large B-cell lymphoma

Introduction

The prognostic value of 18F-FDG PET/CT metabolic parameters, such as metabolic tumor volume (MTV) and total lesion glycolysis (TLG), in diffuse large B-cell lymphoma (DLBCL) remains inadequately explored. This study aims to assess the correlation between these parameters and patient outcomes.

Methods

A cohort of 156 DLBCL patients underwent 18F-FDG PET/CT imaging at baseline and after 3-4 cycles of R-CHOP or CHOP-like regimen. The third quartiles of liver uptake values were used as thresholds for calculating MTV and TLG. Patient outcomes were analyzed based on Ann Arbor staging and the 5-PS score. A nomogram was developed to predict overall survival (OS).

Results

Patients with low baseline TLG exhibited significantly better outcomes compared to those with high baseline TLG in both Ann Arbor stages I-II and III-IV (1-year PFS: 78.9% vs. 40%, p=0.016; OS: 94.7% vs. 40%, p=0.005 for stage I-II; 1-year PFS: 74.1% vs. 46.8%, p=0.014; OS: 85.4% vs. 71.8%, p=0.007 for stage III-IV). In interim PET/CT patients with a 5-PS score >3, the high ΔTLG group had superior prognosis (1-year PFS: 82.3% vs. 35.7%, p=0.003; OS: 88.2% vs. 85.7%, p=0.003). The nomogram achieved a C-index of 0.9 for OS prediction.

Discussion

The findings suggest that baseline TLG is a robust prognostic indicator for patients with DLBCL, particularly in early stages, while ΔTLG effectively distinguishes those with favorable outcomes in higher-risk groups. These metabolic parameters from 18F-FDG PET/CT could enhance treatment decision-making and patient management strategies.

Head-to-Head Comparison of the Diagnostic Performance of FDG PET/CT and FDG PET/MRI in Patients With Cancer: A Systematic Review and Meta-Analysis

BACKGROUND. The available evidence on the use of FDG PET/MRI performed using an integrated system in patients with cancer has grown substantially. OBJECTIVE. The purpose of this study was to perform a systematic review and meta-analysis comparing the diagnostic performance of FDG PET/CT and FDG PET/MRI in patients with cancer. EVIDENCE ACQUISITION. MEDLINE, Embase, and the Cochrane Database of Systematic Reviews were searched for studies reporting a head-to-head comparison of the diagnostic performance of FDG PET/CT and FDG PET/MRI in patients with cancer from July 1, 2015, to January 25, 2023. The two modalities' diagnostic performance was summarized, stratified by performance end point. For end points with sufficient data, a meta-analysis was performed using bivariate modeling to produce summary estimates of pooled sensitivity and specificity. For the remaining end points, reported performance in individual studies was recorded. EVIDENCE SYNTHESIS. The systematic review included 29 studies with a total of 1656 patients. For patient-level detection of regional nodal metastases (five studies), pooled sensitivity and specificity for PET/MRI were 88% (95% CI, 74-95%) and 92% (95% CI, 71-98%), respectively, and for PET/CT were 86% (95% CI, 70-94%) and 86% (95% CI, 68-95%). For lesion-level detection of recurrence and/or metastases (five studies), pooled sensitivity and specificity for PET/MRI were 94% (95% CI, 78-99%) and 83% (95% CI, 76-88%), respectively, and for PET/CT were 91% (95% CI, 77-96%) and 81% (95% CI, 72-88%). In individual studies not included in the meta-analysis, PET/MRI in comparison with PET/CT showed staging accuracy in breast cancer of 98.0% versus 74.5% and in colorectal cancer of 96.2% versus 69.2%; sensitivity for primary tumor detection in cervical cancer of 93.2% versus 66.2%; and sensitivity, specificity, and accuracy for lesion-level liver metastasis detection of 91.1-98.0% versus 42.3-71.1%, 100.0% versus 83.3-98.6%, and 96.5-98.2% versus 44.7-86.7%, respectively. In three studies, management was more commonly impacted by information from PET/MRI (5.2-11.1%) than PET/CT (0.0-2.6%). CONCLUSION. PET/MRI showed comparable or superior diagnostic performance versus PET/CT across a range of cancers and end points. CLINICAL IMPACT. The findings help to identify clinical settings where PET/MRI may provide clinical benefit for oncologic evaluation. TRIAL REGISTRATION. Prospective Register of Systematic Reviews CRD42023433857.

Tetrazine-trans-cyclooctene ligation: Unveiling the chemistry and applications within the human body

Bioorthogonal reactions have revolutionized chemical biology by enabling selective chemical transformations within living organisms and cells. This review comprehensively explores bioorthogonal chemistry, emphasizing inverse-electron-demand Diels-Alder (IEDDA) reactions between tetrazines and strained dienophiles and their crucial role in chemical biology and various applications within the human body. This highly reactive and selective reaction finds diverse applications, including cleaving antibody-drug conjugates, prodrugs, proteins, peptide antigens, and enzyme substrates. The versatility extends to hydrogel chemistry, which is crucial for biomedical applications, yet it faces challenges in achieving precise cellularization. In situ activation of cytotoxic compounds from injectable biopolymer belongs to the click-activated protodrugs against cancer (CAPAC) platform, an innovative approach to tumor-targeted prodrug delivery and activation. The CAPAC platform, relying on click chemistry between trans-cyclooctene (TCO) and tetrazine-modified biopolymers, exhibits modularity across diverse tumor characteristics, presenting a promising approach in anticancer therapeutics. The review highlights the importance of bioorthogonal reactions in developing radiopharmaceuticals for positron emission tomography (PET) imaging and theranostics, offering a promising avenue for diverse therapeutic applications.

Stability of radiomic features from positron emission tomography images: a phantom study comparing advanced reconstruction algorithms and ordered subset expectation maximization

In this study, we compared the repeatability and reproducibility of radiomic features obtained from positron emission tomography (PET) images according to the reconstruction algorithm used-advanced reconstruction algorithms, such as HYPER iterative (IT), HYPER deep learning reconstruction (DLR), and HYPER deep progressive reconstruction (DPR), or traditional Ordered Subset Expectation Maximization (OSEM)-to understand the potential variations and implications of using advanced reconstruction techniques in PET-based radiomics. We used a heterogeneous phantom with acrylic spherical beads (4- or 8-mm diameter) filled with 18F. PET images were acquired and reconstructed using OSEM, IT, DLR, and DPR. Original and wavelet radiomic features were calculated using SlicerRadiomics. Radiomic feature repeatability was assessed using the Coefficient of Variance (COV) and intraclass correlation coefficient (ICC), and inter-acquisition time reproducibility was assessed using the concordance correlation coefficient (CCC). For the 4- and 8-mm diameter beads phantom, the proportion of radiomic features with a COV < 10% was equivocal or higher for the advanced reconstruction algorithm than for OSEM. ICC indicated that advanced methods generally outperformed OSEM in repeatability, except for the original features of the 8-mm beads phantom. In the inter-acquisition time reproducibility analysis, the combinations of 3 and 5 min exhibited the highest reproducibility in both phantoms, with IT and DPR showing the highest proportion of radiomic features with CCC > 0.8. Advanced reconstruction methods provided enhanced stability of radiomic features compared with OSEM, suggesting their potential for optimal image reconstruction in PET-based radiomics, offering potential benefits in clinical diagnostics and prognostics.

The impact of introducing deep learning based [18F]FDG PET denoising on EORTC and PERCIST therapeutic response assessments in digital PET/CT

BACKGROUND

[18F]FDG PET denoising by SubtlePET™ using deep learning artificial intelligence (AI) was previously found to induce slight modifications in lesion and reference organs' quantification and in lesion detection. As a next step, we aimed to evaluate its clinical impact on [18F]FDG PET solid tumour treatment response assessments, while comparing "standard PET" to "AI denoised half-duration PET" ("AI PET") during follow-up.

RESULTS

110 patients referred for baseline and follow-up standard digital [18F]FDG PET/CT were prospectively included. "Standard" EORTC and, if applicable, PERCIST response classifications by 2 readers between baseline standard PET1 and follow-up standard PET2 as a "gold standard" were compared to "mixed" classifications between standard PET1 and AI PET2 (group 1; n = 64), or between AI PET1 and standard PET2 (group 2; n = 46). Separate classifications were established using either standardized uptake values from ultra-high definition PET with or without AI denoising (simplified to "UHD") or EANM research limited v2 (EARL2)-compliant values (by Gaussian filtering in standard PET and using the same filter in AI PET). Overall, pooling both study groups, in 11/110 (10%) patients at least one EORTCUHD or EARL2 or PERCISTUHD or EARL2 mixed vs. standard classification was discordant, with 369/397 (93%) concordant classifications, unweighted Cohen's kappa = 0.86 (95% CI: 0.78-0.94). These modified mixed vs. standard classifications could have impacted management in 2% of patients.

CONCLUSIONS

Although comparing similar PET images is preferable for therapy response assessment, the comparison between a standard [18F]FDG PET and an AI denoised half-duration PET is feasible and seems clinically satisfactory.

Synthetic 18F labeled biomolecules that are selective and promising for PET imaging: major advances and applications

The concept of positron emission tomography (PET) based imaging was developed more than 40 years ago. It has been a widely adopted technique for detecting and staging numerous diseases in clinical settings, particularly cancer, neuro- and cardio-diseases. Here, we reviewed the evolution of PET and its advantages over other imaging modalities in clinical settings. Primarily, this review discusses recent advances in the synthesis of 18F radiolabeled biomolecules in light of the widely accepted performance for effective PET. The discussion particularly emphasizes the 18F-labeling chemistry of carbohydrates, lipids, amino acids, oligonucleotides, peptides, and protein molecules, which have shown promise for PET imaging in recent decades. In addition, we have deliberated on how 18F-labeled biomolecules enable the detection of metabolic changes at the cellular level and the selective imaging of gross anatomical localization via PET imaging. In the end, the review discusses the future perspective of PET imaging to control disease in clinical settings. We firmly believe that collaborative multidisciplinary research will further widen the comprehensive applications of PET approaches in the clinical management of cancer and other pathological outcomes.

Limited Additional Value of a Chest CT in Whole-Body Staging with PET-MRI: A Retrospective Cohort Study

Hybrid PET-MRI systems are being used more frequently. One of the drawbacks of PET-MRI imaging is its inferiority in detecting lung nodules, so it is often combined with a computed tomography (CT) of the chest. However, chest CT often detects additional, indeterminate lung nodules. The objective of this study was to assess the sensitivity of detecting metastatic versus indeterminate nodules with PET-MRI compared to chest CT. A total of 328 patients were included. All patients had a PET/MRI whole-body scan for (re)staging of cancer combined with an unenhanced chest CT performed at our center between 2014 and 2020. Patients had at least a two-year follow-up. Six percent of the patients had lung metastases at initial staging. The sensitivity and specificity of PET-MRI for detecting lung metastases were 85% and 100%, respectively. The incidence of indeterminate lung nodules on chest CT was 30%. The sensitivity of PET-MRI to detect indeterminate lung nodules was poor (23.0%). The average size of the indeterminate lung nodules detected on PET-MRI was 7 ± 4 mm, and the missed indeterminate nodules on PET-MRI were 4 ± 1 mm (p < 0.001). The detection of metastatic lung nodules is fairly good with PET-MRI, whereas the sensitivity of PET-MRI for detecting indeterminate lung nodules is size-dependent. This may be an advantage, limiting unnecessary follow-up of small, indeterminate lung nodules while adequately detecting metastases.

The Diagnostic Impact of Contrast-Enhanced Computed Tomography (CECT) in Evaluating Lymph Node Involvement in Colorectal Cancer: A Comprehensive Review

Colorectal cancer (CRC) remains a significant global health burden, necessitating accurate staging and treatment planning for optimal patient outcomes. Lymph node involvement is a critical determinant of prognosis in CRC, emphasizing the importance of reliable imaging techniques for its evaluation. Contrast-enhanced computed tomography (CECT) has emerged as a cornerstone in CRC imaging, offering high-resolution anatomical detail and vascular assessment. This comprehensive review synthesizes the existing literature to evaluate the diagnostic impact of CECT in assessing lymph node involvement in CRC. Key findings highlight CECT's high sensitivity and specificity in detecting lymph node metastases, facilitating accurate staging and treatment selection. However, challenges such as limited resolution for small lymph nodes and potential false-positives call for a cautious interpretation. Recommendations for clinical practice suggest the integration of CECT into multidisciplinary treatment algorithms, optimizing imaging protocols and enhancing collaboration between radiologists and clinicians. Future research directions include refining imaging protocols, comparative effectiveness studies with emerging modalities, and prospective validation of CECT's prognostic value. Overall, this review stresses the pivotal role of CECT in CRC management and identifies avenues for further advancements in imaging-guided oncology care.

Intersecting Paths: Unraveling the Complex Journey of Cancer to Bone Metastasis

The phenomenon of bone metastases presents a significant challenge within the context of advanced cancer treatments, particularly pertaining to breast, prostate, and lung cancers. These metastatic occurrences stem from the dissemination of cancerous cells into the bone, thereby interrupting the equilibrium between osteoblasts and osteoclasts. Such disruption results in skeletal complications, adversely affecting patient morbidity and quality of life. This review discusses the intricate interplay between cancer cells and the bone microenvironment, positing the bone not merely as a passive recipient of metastatic cells but as an active contributor to cancer progression through its distinctive biochemical and cellular makeup. A thorough examination of bone structure and the dynamics of bone remodeling is undertaken, elucidating how metastatic cancer cells exploit these processes. This review explores the genetic and molecular pathways that underpin the onset and development of bone metastases. Particular emphasis is placed on the roles of cytokines and growth factors in facilitating osteoclastogenesis and influencing osteoblast activity. Additionally, this paper offers a meticulous critique of current diagnostic methodologies, ranging from conventional radiography to advanced molecular imaging techniques, and discusses the implications of a nuanced understanding of bone metastasis biology for therapeutic intervention. This includes the development of targeted therapies and strategies for managing bone pain and other skeletal-related events. Moreover, this review underscores the imperative of ongoing research efforts aimed at identifying novel therapeutic targets and refining management approaches for bone metastases. It advocates for a multidisciplinary strategy that integrates advancements in medical oncology and radiology with insights derived from molecular biology and genetics, to enhance prognostic outcomes and the quality of life for patients afflicted by this debilitating condition. In summary, bone metastases constitute a complex issue that demands a comprehensive and informed approach to treatment. This article contributes to the ongoing discourse by consolidating existing knowledge and identifying avenues for future investigation, with the overarching objective of ameliorating patient care in the domain of oncology.

Robust Quantification of Phosphodiesterase-4D in Monkey Brain with PET and 11C-Labeled Radioligands That Avoid Radiometabolite Contamination

Phosphodiesterase-4D (PDE4D) has emerged as a significant target for treating neuropsychiatric disorders, but no PET radioligand currently exists for robustly quantifying human brain PDE4D to assist biomedical research and drug discovery. A prior candidate PDE4D PET radioligand, namely [11C]T1650, failed in humans because of poor time stability of brain PDE4D-specific signal (indexed by total volume of distribution), likely due to radiometabolites accumulating in brain. Its nitro group was considered to be a source of the brain radiometabolites. Methods: We selected 5 high-affinity and selective PDE4D inhibitors, absent of a nitro group, from our prior structure-activity relationship study for evaluation as PET radioligands. Results: All 5 radioligands were labeled with 11C (half-time, 20.4 min) in useful yields and with high molar activity. All displayed sizable PDE4D-specific signals in rhesus monkey brain. Notably, [11C]JMJ-81 and [11C]JMJ-129 exhibited excellent time stability of signal (total volume of distribution). Furthermore, as an example, [11C]JMJ-81 was found to be free of radiometabolites in ex vivo monkey brain, affirming that this radioligand can provide robust quantification of brain PDE4D with PET. Conclusion: Given their high similarity in structures and metabolic profiles, both [11C]JMJ-81 and [11C]JMJ-129 warrant further evaluation in human subjects. [11C]JMJ-129 shows a higher PDE4D specific-to-nonspecific binding ratio and will be the first to be evaluated.

The Utility of [18]F-Fluorocholine Positron Emission Computed Tomography and [18]F-Fluorodeoxyglucose Positron Emission Tomography-Computed Tomography in Evaluating Breast Cancer Phenotypes: A Pilot Study

The utility of the [18]F fluorodeoxyglucose positron emission tomography-computed tomography ([18]F FDG PET-CT) marker for breast cancer is well established. Given its limitations in localizing FDG-negative malignant tumors, the expression of [18]F-fluorocholine ([18]-FCH) may potentially be helpful to improve the overall accuracy in evaluating breast cancer. This study determined the potential of [18]- FCH PET CT as a potential marker in assessing breast cancer phenotypes. We recruited consecutive patients with biopsy-proven breast carcinoma who underwent [18] F-FCH PET-CT following the [18]F-FDG PET-CT imaging. The subjects were dichotomized into human epidermal growth factor receptor 2 (HER2)-negative and HER2-positive genotypes. The maximum standardized uptake value (SUVmax; g/dL) was used to predict the two groups of variables. Global health status (GHS) score based on the EORTC quality of life questionnaire (QLQ) was used to evaluate the outcome of the cohort subjects at 6, 12, and 24 months. There were 21 females with a mean age of 54.48 ± 12.17 years. Eighteen patients had invasive ductal carcinoma (18/21;85.8%) on histology, with 11 (52.4%) were HER2-negative genotype. There was higher sensitivity and specificity of [18]-FCH-PET/CT in breast lesions at 40% and 68.8% compared to [18]FDGPET/CT with 33.3% and 66.7%, respectively. There were significant differences between [18]F-FCH SUVmax (g/dL) of the HER-negative as compared to the HER2- positive group (1.99 g/dL vs. 0.2 g/dL; P < .05). High SUVmax (g/dL) of [18]F-FCH had predicted the HER-negative genotype at the cutoff value of 0.75 (P < .05). High [18]F-FCH showed significantly poor scoring of GHS parameters compared to low FCH at 6 months (mean SUVmax 8.06 vs. 5.40 respectively; P < .05). [18]F-FCH PET-CT is a potential marker in localizing and predicting aggressive breast carcinoma phenotypes.

An automated methodology for whole-body, multimodality tracking of individual cancer lesions

Objective. Manual analysis of individual cancer lesions to assess disease response is clinically impractical and requires automated lesion tracking methodologies. However, no methodology has been developed for whole-body individual lesion tracking, across an arbitrary number of scans, and acquired with various imaging modalities.Approach. This study introduces a lesion tracking methodology and benchmarked it using 2368Ga-DOTATATE PET/CT and PET/MR images of eight neuroendocrine tumor patients. The methodology consists of six steps: (1) alignment of multiple scans via image registration, (2) body-part labeling, (3) automatic lesion-wise dilation, (4) clustering of lesions based on local lesion shape metrics, (5) assignment of lesion tracks, and (6) output of a lesion graph. Registration performance was evaluated via landmark distance, lesion matching accuracy was evaluated between each image pair, and lesion tracking accuracy was evaluated via identical track ratio. Sensitivity studies were performed to evaluate the impact of lesion dilation (fixed versus automatic dilation), anatomic location, image modalities (inter- versus intra-modality), registration mode (direct versus indirect registration), and track size (number of time-points and lesions) on lesion matching and tracking performance.Main results. Manual contouring yielded 956 lesions, 1570 lesion-matching decisions, and 493 lesion tracks. The median residual registration error was 2.5 mm. The automatic lesion dilation led to 0.90 overall lesion matching accuracy, and an 88% identical track ratio. The methodology is robust regarding anatomic locations, image modalities, and registration modes. The number of scans had a moderate negative impact on the identical track ratio (94% for 2 scans, 91% for 3 scans, and 81% for 4 scans). The number of lesions substantially impacted the identical track ratio (93% for 2 nodes versus 54% for ≥5 nodes).Significance. The developed methodology resulted in high lesion-matching accuracy and enables automated lesion tracking in PET/CT and PET/MR.

Current Development of Lanthanide Complexes for Biomedical Applications

Luminescent molecule-based bioimaging system is widely used for precise localization and distinction of cancer/tumor cells. Luminescent lanthanide (Ln(III)) complexes offer long-lived (sub-millisecond time scale) and sharp (FWHM <10 nm) emission, arising from the forbidden 4f-4f electronic transitions. Luminescent Ln(III) complex-based bioimaging has emerged as a promising option for both in vitro and in vivo visualizations. In this mini-review, the historical development and recent significant progress of luminescent Ln(III) probes for bioapplications are introduced. The recent studies are mainly focused on three points: (i) the structural modifications of Ln(III) complexes in both macrocyclic and small ligands, (ii) the acquirement of high resolution luminescence images of cancer/tumor cells and (iii) the constructions of ratiometric biosensors. Furthermore, our recent study is explained as a new Cancer GPS (cancer grade probing for determining tumor grade through photophysical property analyses of intracellular Eu(III) complex.

Repeatability of 18F-FDG uptake in metastatic bone lesions of breast cancer patients and implications for accrual to clinical trials

BACKGROUND

Standard measures of response such as Response Evaluation Criteria in Solid Tumors are ineffective for bone lesions, often making breast cancer patients that have bone-dominant metastases ineligible for clinical trials with potentially helpful therapies. In this study we prospectively evaluated the test-retest uptake variability of 2-deoxy-2-[18F]fluoro-D-glucose (18F-FDG) in a cohort of breast cancer patients with bone-dominant metastases to determine response criteria. The thresholds for 95% specificity of change versus no-change were then applied to a second cohort of breast cancer patients with bone-dominant metastases.

METHODS

For this study, nine patients with 38 bone lesions were imaged with 18F-FDG in the same calibrated scanner twice within 14 days. Tumor uptake was quantified by the most commonly used PET parameter, the maximum tumor voxel normalized by dose and body weight (SUVmax) and also by the mean of a 1-cc maximal uptake volume normalized by dose and lean-body-mass (SULpeak). The asymmetric repeatability coefficients with confidence intervals for SUVmax and SULpeak were used to determine the limits of 18F-FDG uptake variability. A second cohort of 28 breast cancer patients with bone-dominant metastases that had 146 metastatic bone lesions was imaged with 18F-FDG before and after standard-of-care therapy for response assessment.

RESULTS

The mean relative difference of SUVmax and SULpeak in 38 bone tumors of the first cohort were 4.3% and 6.7%. The upper and lower asymmetric limits of the repeatability coefficient were 19.4% and - 16.3% for SUVmax, and 21.2% and - 17.5% for SULpeak. 18F-FDG repeatability coefficient confidence intervals resulted in the following patient stratification using SULpeak for the second patient cohort: 11-progressive disease, 5-stable disease, 7-partial response, and 1-complete response with three inevaluable patients. The asymmetric repeatability coefficients response criteria for SULpeak changed the status of 3 patients compared to the standard Positron Emission Tomography Response Criteria in Solid Tumors of ± 30% SULpeak.

CONCLUSION

In evaluating bone tumor response for breast cancer patients with bone-dominant metastases using 18F-FDG SUVmax, the repeatability coefficients from test-retest studies show that reductions of more than 17% and increases of more than 20% are unlikely to be due to measurement variability. Serial 18F-FDG imaging in clinical trials investigating bone lesions in these patients, such as the ECOG-ACRIN EA1183 trial, benefit from confidence limits that allow interpretation of response.

Impact of different reconstruction algorithms and setting parameters on radiomics features of PSMA PET images: A preliminary study

PURPOSE

Radiomics analysis of oncologic positron emission tomography (PET) images is an area of significant activity and potential. The reproducibility of radiomics features is an important consideration for routine clinical use. This preliminary study investigates the robustness of radiomics features in PSMA-PET images across penalized-likelihood (Q.Clear) and standard ordered subset expectation maximization (OSEM) reconstruction algorithms and their setting parameters in phantom and prostate cancer (PCa) patients.

METHOD

A NEMA image quality (IQ) phantom and 8 PCa patients were selected for phantom and patient analyses, respectively. PET images were reconstructed using Q.Clear (reconstruction β-value: 100-700, at intervals of 100 for both NEMA IQ phantom and patients) and OSEM (duration: 15sec, 30sec, 1 min, 2 min, 3 min, 4 min and 5 min for NEMA phantom and duration: 30 s, 1 min and 2 min for patients) reconstruction methods. Subsequently, 129 radiomic features were extracted from the reconstructed images. The coefficient of variation (COV) of each feature across reconstruction methods and their parameters was calculated to determine feature robustness.

RESULTS

The extracted radiomics features showed a different range of variability, depending on the reconstruction algorithms and setting parameters. Specifically, 23.0 % and 53.5 % of features were found as robust against β-value variations in Q.Clear and different durations in OSEM reconstruction algorithms, respectively. Taking into account the two algorithms and their parameters, eleven features (8.5 %) showed COV ≤ 5 % and eighteen (14 %) showed 5 % 20 %. The mean COVs of the extracted radiomics features were significantly different between the two reconstruction methods (p < 0.05) except for the phantom morphological features.

CONCLUSIONS

All radiomics features were affected by reconstruction methods and parameters, but features with small or very small variations are considered better candidates for reproducible quantification of either tumor or metastatic tissues in clinical trials. There is a need for standardization before the implementation of PET radiomics in clinical practice.

Bridging the Gap in Understanding Bone Metastasis: A Multifaceted Perspective

The treatment of patients with advanced cancer poses clinical problems due to the complications that arise as the disease progresses. Bone metastases are a common problem that cancer patients may face, and currently, there are no effective drugs to treat these individuals. Prostate, breast, and lung cancers often spread to the bone, causing significant and disabling health conditions. The bone is a highly active and dynamic tissue and is considered a favorable environment for the growth of cancer. The role of osteoblasts and osteoclasts in the process of bone remodeling and the way in which their interactions change during the progression of metastasis is critical to understanding the pathophysiology of this disease. These interactions create a self-perpetuating loop that stimulates the growth of metastatic cells in the bone. The metabolic reprogramming of both cancer cells and cells in the bone microenvironment has serious implications for the development and progression of metastasis. Insight into the process of bone remodeling and the systemic elements that regulate this process, as well as the cellular changes that occur during the progression of bone metastases, is critical to the discovery of a cure for this disease. It is crucial to explore different therapeutic options that focus specifically on malignancy in the bone microenvironment in order to effectively treat this disease. This review will focus on the bone remodeling process and the effects of metabolic disorders as well as systemic factors like hormones and cytokines on the development of bone metastases. We will also examine the various therapeutic alternatives available today and the upcoming advances in novel treatments.

Single-cell low-pass whole genome sequencing accurately detects circulating tumor cells for liquid biopsy-based multi-cancer diagnosis

Accurate detection of circulating tumor cells (CTCs) in blood and non-blood body fluids enables generation of deterministic cancer diagnosis and represent a less invasive and safer liquid biopsy approach. Although genomic alternations have been widely used in circulating tumor DNA (ctDNA) analysis, studies on cell-based genomic alternations profiling for CTC detection are rare due to major technical limitations in single-cell whole genome sequencing (WGS) including low throughput, low accuracy and high cost. We report a single-cell low-pass WGS-based protocol (scMet-Seq) for sensitive and accurate CTC detection by combining a metabolic function-associated marker Hexokinase 2 (HK2) and a Tn5 transposome-based WGS method with improved cell fixation strategy. To explore the clinical use, scMet-Seq has been investigated with blood and non-blood body fluids in diagnosing metastatic diseases, including ascites-based diagnosis of malignant ascites (MA) and blood-based diagnosis of metastatic small-cell lung cancer (SCLC). ScMet-Seq shows high diagnostic sensitivity (MA: 79% in >10 cancer types; metastatic SCLC: 90%) and ~100% of diagnostic specificity and positive predictive value, superior to clinical cytology that exhibits diagnostic sensitivity of 52% in MA diagnosis and could not generate blood-based diagnosis. ScMet-Seq represents a liquid biopsy approach for deterministic cancer diagnosis in different types of cancers and body fluids.

Repeatability of 18F-FDG uptake in metastatic bone lesions of breast cancer patients and implications for accrual to clinical trials

BACKGROUND

Standard measures of response such as Response Evaluation Criteria in Solid Tumors are ineffective for bone lesions, often making breast cancer patients with bone-dominant metastases ineligible for clinical trials with potentially helpful therapies. In this study we prospectively evaluated the test-retest uptake variability of 2-deoxy-2-[18F]fluoro-D-glucose (18F-FDG) in a cohort of breast cancer patients with bone-dominant metastases to determine response criteria. The thresholds for 95% specificity of change versus no-change were then applied to a second cohort of breast cancer patients with bone-dominant metastases.In this study, nine patients with 38 bone lesions were imaged with 18F-FDG in the same calibrated scanner twice within 14 days. Tumor uptake was quantified as the maximum tumor voxel normalized by dose and body weight (SUVmax) and the mean of a 1-cc maximal uptake volume normalized by dose and lean-body-mass (SULpeak). The asymmetric repeatability coefficients with confidence intervals of SUVmax and SULpeak were used to determine limits of 18F-FDG uptake variability. A second cohort of 28 breast cancer patients with bone-dominant metastases that had 146 metastatic bone lesions was imaged with 18F-FDG before and after standard-of-care therapy for response assessment.

RESULTS

The mean relative difference of SUVmax in 38 bone tumors of the first cohort was 4.3%. The upper and lower asymmetric limits of the repeatability coefficient were 19.4% and -16.3%, respectively. The 18F-FDG repeatability coefficient confidence intervals resulted in the following patient stratification for the second patient cohort: 11-progressive disease, 5-stable disease, 7-partial response, and 1-complete response with three inevaluable patients. The asymmetric repeatability coefficients response criteria changed the status of 3 patients compared to standard the standard Positron Emission Tomography Response Criteria in Solid Tumors of ±30% SULpeak.

CONCLUSIONS

In evaluating bone tumor response for breast cancer patients with bone-dominant metastases using 18F-FDG uptake, the repeatability coefficients from test-retest studies show that reductions of more than 17% and increases of more than 20% are unlikely to be due to measurement variability. Serial 18F-FDG imaging in clinical trials investigating bone lesions from these patients, such as the ECOG-ACRIN EA1183 trial, benefit from confidence limits that allow interpretation of response.

Overcoming Chemotherapy Resistance in Metastatic Cancer: A Comprehensive Review

The management of metastatic cancer is complicated by chemotherapy resistance. This manuscript provides a comprehensive academic review of strategies to overcome chemotherapy resistance in metastatic cancer. The manuscript presents background information on chemotherapy resistance in metastatic cancer cells, highlighting its clinical significance and the current challenges associated with using chemotherapy to treat metastatic cancer. The manuscript delves into the molecular mechanisms underlying chemotherapy resistance in subsequent sections. It discusses the genetic alterations, mutations, and epigenetic modifications that contribute to the development of resistance. Additionally, the role of altered drug metabolism and efflux mechanisms, as well as the activation of survival pathways and evasion of cell death, are explored in detail. The strategies to overcome chemotherapy resistance are thoroughly examined, covering various approaches that have shown promise. These include combination therapy approaches, targeted therapies, immunotherapeutic strategies, and the repurposing of existing drugs. Each strategy is discussed in terms of its rationale and potential effectiveness. Strategies for early detection and monitoring of chemotherapy drug resistance, rational drug design vis-a-vis personalized medicine approaches, the role of predictive biomarkers in guiding treatment decisions, and the importance of lifestyle modifications and supportive therapies in improving treatment outcomes are discussed. Lastly, the manuscript outlines the clinical implications of the discussed strategies. It provides insights into ongoing clinical trials and emerging therapies that address chemotherapy resistance in metastatic cancer cells. The manuscript also explores the challenges and opportunities in translating laboratory findings into clinical practice and identifies potential future directions and novel therapeutic avenues. This comprehensive review provides a detailed analysis of strategies to overcome chemotherapy resistance in metastatic cancer. It emphasizes the importance of understanding the molecular mechanisms underlying resistance and presents a range of approaches for addressing this critical issue in treating metastatic cancer.

Identification of Skin Lesions by Snapshot Hyperspectral Imaging

This study pioneers the application of artificial intelligence (AI) and hyperspectral imaging (HSI) in the diagnosis of skin cancer lesions, particularly focusing on Mycosis fungoides (MF) and its differentiation from psoriasis (PsO) and atopic dermatitis (AD). By utilizing a comprehensive dataset of 1659 skin images, including cases of MF, PsO, AD, and normal skin, a novel multi-frame AI algorithm was used for computer-aided diagnosis. The automatic segmentation and classification of skin lesions were further explored using advanced techniques, such as U-Net Attention models and XGBoost algorithms, transforming images from the color space to the spectral domain. The potential of AI and HSI in dermatological diagnostics was underscored, offering a noninvasive, efficient, and accurate alternative to traditional methods. The findings are particularly crucial for early-stage invasive lesion detection in MF, showcasing the model's robust performance in segmenting and classifying lesions and its superior predictive accuracy validated through k-fold cross-validation. The model attained its optimal performance with a k-fold cross-validation value of 7, achieving a sensitivity of 90.72%, a specificity of 96.76%, an F1-score of 90.08%, and an ROC-AUC of 0.9351. This study marks a substantial advancement in dermatological diagnostics, thereby contributing significantly to the early and precise identification of skin malignancies and inflammatory conditions.

Application of preoperative fluorodeoxyglucose-PET/CT parameters for predicting prognosis of high-grade neuroendocrine cervical cancer

OBJECTIVE

High-grade neuroendocrine cervical cancer (HGNECC) is a rare and aggressive cervical cancer subtype. In this study, we aimed to evaluate the prognostic value of fluorodeoxyglucose-PET/computed tomography (CT) parameters for HGNECC.

MATERIALS AND METHODS

This single-center retrospective study included 29 patients with HGNECC who underwent fluorodeoxyglucose-PET/CT scan followed by surgery between 2006 and 2016.

RESULTS

The median follow-up period was 40 (range, 4-184) months. After surgery, the resection margins were tumor-negative in 28 patients (96.6%), 8 (27.6%) patients had parametrial tumor invasion, and 7 patients (24.1%) tested positive for lymph node metastasis. The tumor recurred in 20 patients (69%) and 18 patients (62.1%) died during the observation period. In the univariate analyses, age and total lesion glycolysis (TLG) were associated with worse disease-free survival (DFS) (age, hazard ratio 1.056, 95% CI 1.014-1.100, P  = 0.009; TLG2.5, hazard ratio 1.003, 95% CI 1-1.006, P  = 0.033; and TLG3.0, hazard ratio 1.003, 95% CI 1-1.006, P  = 0.034). In the multivariate analyses, older age and higher TLG3.0 were identified as independent poor prognostic factors for DFS (age, hazard ratio 1.058, 95% CI 1.014-1.104, P  = 0.009; TLG3.0, hazard ratio 1.004, 95% CI 1-1.007, P  = 0.033), while resection margin involvement was identified as an independent factor to predict poor overall survival (hazard ratio 20.717, 95% CI 1.289-332.964, P  = 0.032).

CONCLUSION

Among the preoperative fluorodeoxyglucose-PET/CT parameters, TLG3.0 may be useful for predicting DFS in patients with HGNECC.

Role of volumetric parameters obtained from 68 Ga-PSMA PET/CT and 18F-FDG PET/CT in predicting overall survival in patients with mCRPC receiving taxane therapy

OBJECTIVE

The aim of this study was to determine the prognostic role of volumetric parameters and Pro-PET scores obtained from 68 Ga-prostate-specific membrane antigen (PSMA) PET/CT and 18F-FDG PET/CT in patients with metastatic castration-resistant prostate cancer (mCRPC) receiving taxane therapy.

MATERIALS AND METHODS

The study included 71 patients who underwent simultaneous PSMA and 18F-FDG PET/CT imaging between January 2019 and January 2022, had a Pro-PET score of 3-5 and had received taxane therapy after imaging. 18F-FDG tumor volume (TV-F) and PSMA tumor volume (TV-P) values of the lesions and total lesion glycolysis (TL-G) and total lesion PSMA (TL-P) values of the lesions were calculated on both imaging studies and the effects of these parameters on overall survival (OS) were investigated.

RESULTS

The median age of the patients included herein was 71 years (56-89) and the median prostate-specific antigen (PSA) level was 16.4 (0.01-1852 ng/dL). According to the Kaplan-Meier survival analysis, TTV-P ≥ 78.5, TTL-P ≥ 278.8, TTV-F ≥ 94.98, TTL-G ≥ 458.3, TTV-P + F ≥ 195.45, TTL-G + P ≥ 855.78, lymph node (L)TV-FDG ≥ 3.4, LFDG-SUVmax ≥ 3.2, LFDG-SUVmean ≥ 2.25, LFDG-SUVpeak ≥ 2.55, and bone (B)TV-F ≥ 51.15 values were found to be prognostic factors in predicting short OS. Multivariate Cox regression analysis showed that a Vscore ≥ 3 (95% confidence interval [CI]: 7.069-98.251, p < 0.001) and TTL-G + P ≥ 855.78 (95% CI: 4.878-1037.860, p = 0.006) were found to be independent prognostic factors in predicting short OS.

CONCLUSION

Volumetric parameters and Pro-PET scores obtained from 68 Ga-PSMA PET/CT and 18F-FDG PET/CT imaging have been shown to have an impact on OS in patients with mCRPC receiving taxane therapy.

The assessment of left ventricular volume and function in gated small animal 18F-FDG PET/CT imaging: a comparative study of three commercially available software tools

BACKGROUND

Several software tools have been developed for gated PET imaging that use distinct algorithms to analyze tracer uptake, myocardial perfusion, and left ventricle volumes and function. Studies suggest that different software tools cannot be used interchangeably in humans. In this study, we sought to compare the left ventricular parameters in gated 18F-FDG PET/CT imaging in mice by three commercially available software tools: PMOD, MIM, and QGS.

METHODS AND RESULTS

Healthy mice underwent ECG-gated 18F-FDG imaging using a small-animal nanoPET/CT (Mediso) under isoflurane narcosis. Reconstructed gates PET images were subsequently analyzed in three different software tools, and cardiac volume and function (end-diastolic (EDV), end-systolic volumes (ESV), stroke volume (SV), and ejection fraction (EF)) were evaluated. While cardiac volumes correlated well between PMOD, MIM, and QGS, the left ventricular parameters and cardiac function differed in agreement using Bland-Altman analysis. EDV in PMOD vs. QGS: r = 0.85; p < 0.001, MIM vs. QGS: r = 0.92; p < 0.001, and MIM vs. PMOD: r = 0.88; p < 0.001, showed good correlations. Correlation was also found in ESV: PMOD vs. QGS: r = 0.48; p = 0.07, MIM vs QGS: r = 0.79; p < 0.001, and MIM vs. PMOD: r = 0.69; p < 0.01. SV showed good correlations in: PMOD vs. QGS: r = 0.73; p < 0.01, MIM vs. QGS: r = 0.86; p < 0.001, and MIM vs. PMOD: r = 0.92; p < 0.001. However, EF among correlated poorly: PMOD vs. QGS: r = -0.31; p = 0.26, MIM vs. QGS: r = 0.48; p = 0.07, and MIM vs. PMOD: r = 0.23; p = 0.41. Inter-class and intra-class correlation coefficient were > 0.9 underlining repeatability in using PMOD, MIM, and QGS for cardiac volume and function assessment.

CONCLUSIONS

All three commercially available software tools are feasible in small animal cardiac volume assessment in gated 18F-FDG PET/CT imaging. However, due to software-related differences in agreement analysis for cardiac volumes and function, PMOD, MIM, and QGS cannot be used interchangeably in murine research.

New Long-Acting [89Zr]Zr-DFO GLP-1 PET Tracers with Increased Molar Activity and Reduced Kidney Accumulation

Positron emission tomography (PET) imaging is used in drug development to noninvasively measure biodistribution and receptor occupancy. Ideally, PET tracers retain target binding and biodistribution properties of the investigated drug. Previously, we developed a zirconium-89 PET tracer based on a long-circulating glucagon-like peptide 1 receptor agonist (GLP-1RA) using desferrioxamine (DFO) as a chelator. Here, we aimed to develop an improved zirconium-89-labeled GLP-1RA with increased molar activity to increase the uptake in low receptor density tissues, such as brain. Furthermore, we aimed at reducing tracer accumulation in the kidneys. Introducing up to four additional Zr-DFOs resulted in higher molar activity and stability, while retaining potency. Branched placement of DFOs was especially beneficial. Tracers with either two or four DFOs had similar biodistribution as the tracer with one DFO in vivo, albeit increased kidney and liver uptake. Reduced kidney accumulation was achieved by introducing an enzymatically cleavable Met-Val-Lys (MVK) linker motif between the chelator and the peptide.

Variability in PET image quality and quantification measured with a permanently filled 68Ge-phantom: a multi-center study

BACKGROUND

This study evaluated, as a snapshot, the variability in quantification and image quality (IQ) of the clinically utilized PET [¹⁸F]FDG whole-body protocols in Finland using a NEMA/IEC IQ phantom permanently filled with ⁶⁸Ge.

METHODS

The phantom was imaged on 14 PET-CT scanners, including a variety of models from two major vendors. The variability of the recovery coefficients (RC_max, RC_mean and RC_peak) of the hot spheres as well as percent background variability (PBV), coefficient of variation of the background (COV_BG) and accuracy of corrections (AOC) were studied using images from clinical and standardized protocols with 20 repeated measurements. The ranges of the RCs were also compared to the limits of the EARL ¹⁸F standards 2 accreditation (EARL2). The impact of image noise on these parameters was studied using averaged images (AVIs).

RESULTS

The largest variability in RC values of the routine protocols was found for the RC_max with a range of 68% and with 10% intra-scanner variability, decreasing to 36% when excluding protocols with suspected cross-calibration failure or without point-spread-function (PSF) correction. The RC ranges of individual hot spheres in routine or standardized protocols or AVIs fulfilled the EARL2 ranges with two minor exceptions, but fulfilling the exact EARL2 limits for all hot spheres was variable. RC_peak was less dependent on averaging and reconstruction parameters than RC_max and RC_mean. The PBV, COV_BG and AOC varied between 2.3-11.8%, 9.6-17.8% and 4.8-32.0%, respectively, for the routine protocols. The RC ranges, PBV and COV_BG were decreased when using AVIs. With AOC, when excluding routine protocols without PSF correction, the maximum value dropped to 15.5%.

CONCLUSION

The maximum variability of the RC values for the [¹⁸F]FDG whole-body protocols was about 60%. The RC ranges of properly cross-calibrated scanners with PSF correction fitted to the EARL2 RC ranges for individual sphere sizes, but fulfilling the exact RC limits would have needed further optimization. RC_peak was the most robust RC measure. Besides COV_BG, also RCs and PVB were sensitive to image noise.

Deep learning model for automatic image quality assessment in PET

BACKGROUND

A variety of external factors might seriously degrade PET image quality and lead to inconsistent results. The aim of this study is to explore a potential PET image quality assessment (QA) method with deep learning (DL).

METHODS

A total of 89 PET images were acquired from Peking Union Medical College Hospital (PUMCH) in China in this study. Ground-truth quality for images was assessed by two senior radiologists and classified into five grades (grade 1, grade 2, grade 3, grade 4, and grade 5). Grade 5 is the best image quality. After preprocessing, the Dense Convolutional Network (DenseNet) was trained to automatically recognize optimal- and poor-quality PET images. Accuracy (ACC), sensitivity, specificity, receiver operating characteristic curve (ROC), and area under the ROC Curve (AUC) were used to evaluate the diagnostic properties of all models. All indicators of models were assessed using fivefold cross-validation. An image quality QA tool was developed based on our deep learning model. A PET QA report can be automatically obtained after inputting PET images.

RESULTS

Four tasks were generated. Task2 showed worst performance in AUC,ACC, specificity and sensitivity among 4 tasks, and task1 showed unstable performance between training and testing and task3 showed low specificity in both training and testing. Task 4 showed the best diagnostic properties and discriminative performance between poor image quality (grade 1, grade 2) and good quality (grade 3, grade 4, grade 5) images. The automated quality assessment of task 4 showed ACC = 0.77, specificity = 0.71, and sensitivity = 0.83, in the train set; ACC = 0.85, specificity = 0.79, and sensitivity = 0.91, in the test set, respectively. The ROC measuring performance of task 4 had an AUC of 0.86 in the train set and 0.91 in the test set. The image QA tool could output basic information of images, scan and reconstruction parameters, typical instances of PET images, and deep learning score.

CONCLUSIONS

This study highlights the feasibility of the assessment of image quality in PET images using a deep learning model, which may assist with accelerating clinical research by reliably assessing image quality.

MSRA-Net: Tumor segmentation network based on Multi-scale Residual Attention

Automatic Medical segmentation of medical images is an important part in the field of computer medical diagnosis, among which tumor segmentation is an important branch of medical image segmentation. Accurate automatic segmentation method is very important in medical diagnosis and treatment. Positron emission computed tomography (PET) and X-ray computed tomography (CT) images are widely used in medical image segmentation to help doctors accurately locate information such as tumor location and shape, providing metabolic and anatomical information, respectively. At present, PET/CT images have not been effectively combined in the research of medical image segmentation, and the complementary semantic information between the superficial and deep layers of neural network has not been ensured. To solve the above problems, this paper proposed a Multi-scale Residual Attention network (MSRA-Net) for tumor segmentation of PET/CT. We first use an attention-fusion based approach to automatically learn the tumor-related areas of PET images and weaken the irrelevant area. Then, the segmentation results of PET branch are processed to optimize the segmentation results of CT branch by using attention mechanism. The proposed neural network (MSRA-Net) can effectively fuse PET image and CT image, which can improve the precision of tumor segmentation by using complementary information of the multi-modal image, and reduce the uncertainty of single modal image segmentation. Proposed model uses multi-scale attention mechanism and residual module, which fuse multi-scale features to form complementary features of different scales. We compare with state-of-the-art medical image segmentation methods. The experiment showed that the Dice coefficient of the proposed network in soft tissue sarcoma and lymphoma datasets increased by 8.5% and 6.1% respectively compared with UNet, showing a significant improvement.

A Phase I Dose-escalation Study of AZD3965, an Oral Monocarboxylate Transporter 1 Inhibitor, in Patients with Advanced Cancer

PURPOSE

Inhibition of monocarboxylate transporter (MCT) 1-mediated lactate transport may have cytostatic and/or cytotoxic effects on tumor cells. We report results from the dose-escalation part of a first-in-human trial of AZD3965, a first-in-class MCT1 inhibitor, in advanced cancer.

PATIENTS AND METHODS

This multicentre, phase I, dose-escalation and dose-expansion trial enrolled patients with advanced solid tumors or lymphoma and no standard therapy options. Exclusion criteria included history of retinal and/or cardiac disease, due to MCT1 expression in the eye and heart. Patients received daily oral AZD3965 according to a 3+3 then rolling six design. Primary objectives were to assess safety and determine the MTD and/or recommended phase II dose (RP2D). Secondary objectives for dose escalation included measurement of pharmacokinetic and pharmacodynamic activity. Exploratory biomarkers included tumor expression of MCT1 and MCT4, functional imaging of biological impact, and metabolomics.

RESULTS

During dose escalation, 40 patients received AZD3965 at 5-30 mg once daily or 10 or 15 mg twice daily. Treatment-emergent adverse events were primarily grade 1 and/or 2, most commonly electroretinogram changes (retinopathy), fatigue, anorexia, and constipation. Seven patients receiving ≥20 mg daily experienced dose-limiting toxicities (DLT): grade 3 cardiac troponin rise (n = 1), asymptomatic ocular DLTs (n = 5), and grade 3 acidosis (n = 1). Plasma pharmacokinetics demonstrated attainment of target concentrations; pharmacodynamic measurements indicated on-target activity.

CONCLUSIONS

AZD3965 is tolerated at doses that produce target engagement. DLTs were on-target and primarily dose-dependent, asymptomatic, reversible ocular changes. An RP2D of 10 mg twice daily was established for use in dose expansion in cancers that generally express high MCT1/low MCT4).

Glucose Infusion Induced Change in Intracellular pH and Its Relationship with Tumor Glycolysis in a C6 Rat Model of Glioblastoma

INTRODUCTION

The reliance on glycolytic metabolism is a hallmark of tumor metabolism. Excess acid and protons are produced, leading to an acidic tumor environment. Therefore, we explored the relationship between the tumor glycolytic metabolism and tissue pH by comparing ¹⁸F-fluorodeoxyglucose positron emission tomography (FDG-PET) and hyperpolarized [1-¹³C]pyruvate MR spectroscopy imaging (MRSI) to chemical exchange saturation transfer (CEST) MRI measurements of tumor pH.

METHODS

10⁶ C6 glioma cells were implanted in the brains of male Wistar rats (N = 11) using stereotactic surgery. A 60-min PET acquisition after a bolus of FDG was performed at 11-13 days post implantation, and standardized uptake value (SUV) was calculated. CEST measurements were acquired the following day before and during constant infusion of glucose solution. Tumor intracellular pH (pHi) was evaluated using amine and amide concentration-independent detection (AACID) CEST MRI. The change of pH_i (∆pH_i) was calculated as the difference between pH_i pre- and during glucose infusion. Rats were imaged immediately with hyperpolarized [1-¹³C]pyruvate MRSI. Regional maps of the ratio of Lac:Pyr were acquired. The correlations between SUV, Lac:Pyr ratio, and ∆pH_i were evaluated using Pearson's correlation.

RESULTS

A decrease of 0.14 in pH_i was found after glucose infusion in tumor region. Significant correlations between tumor glycolysis measurements of Lac:Pyr and ∆pH_i within the tumor (ρ = 0.83, P = 0.01) and peritumoral region (ρ = 0.76, P = 0.028) were observed. No significant correlations were found between tumor SUV and ∆pH_i within the tumor (ρ =  - 0.45, P = 0.17) and peritumor regions (ρ =  - 0.6, P = 0.051).

CONCLUSION

AACID detected the changes in pH_i induced by glucose infusion. Significant correlations between tumor glycolytic measurement of Lac:Pyr and tumoral and peritumoral pH_i and ∆pH_i suggest the intrinsic relationship between tumor glycolytic metabolism and the tumor pH environment as well as the peritumor pH environment.

Metabolic activity grows in human cancers pushed by phenotypic variability

Different evolutionary processes push cancers to increasingly aggressive behaviors, energetically sustained by metabolic reprogramming. The collective signature emerging from this transition is macroscopically displayed by positron emission tomography (PET). In fact, the most readily PET measure, the maximum standardized uptake value (SUV_max), has been found to have prognostic value in different cancers. However, few works have linked the properties of this metabolic hotspot to cancer evolutionary dynamics. Here, by analyzing diagnostic PET images from 512 patients with cancer, we found that SUV_max scales superlinearly with the mean metabolic activity (SUV_mean), reflecting a dynamic preferential accumulation of activity on the hotspot. Additionally, SUV_max increased with metabolic tumor volume (MTV) following a power law. The behavior from the patients data was accurately captured by a mechanistic evolutionary dynamics model of tumor growth accounting for phenotypic transitions. This suggests that non-genetic changes may suffice to fuel the observed sustained increases in tumor metabolic activity.

Characteristics of Radiopharmaceutical Uptake in Primary Tumor and Metastatic Lesions of Prostate Carcinoma: Comparison of Oligometastatic with Multimetastatic Disease

Objectives

Oligometastases may generate secondary to indolent tumor biology. In this study, we investigated whether semiquantitative measures of ¹⁸F-fluorodeoxyglucose (FDG) and gallium-68 (⁶⁸Ga) prostate-specific membrane antigen (PSMA) uptake of metastatic lesions and prostatic sites are different between oligometastatic (OM) and multimetastatic (MM) disease of prostate carcinoma (PC).

Methods

Patients with PC, who underwent positron emission tomography/computed tomography (PET/CT) from October 2012 to February 2020 were retrospectively reviewed. Patients, whose reports were consistent with metastatic diseases were selected. Patients classified as with MM or OM disease. Maximum standardized uptake values (SUV_max) were calculated from metastatic lesions and the prostatic site. The median of the SUV_max results between patients with OM and MM disease were compared.

Results

A totally 145 patients with a mean age of 71.46±9.26, were evaluated. In 59 of 145 patients, ¹⁸F-FDG PET/CT was performed;86 patients had gone through ⁶⁸Ga PSMA PET/CT. Thirty-seven of 145 patients were OM, whereas 108 patients were MM. The median of the SUV_max of metastatic lesions in patients with OM and MM disease in the ¹⁸F-FDG group were 5.60 and 9.51, respectively. The results of the calculated median SUV_max values in OM and MM disease in the Ga-68 PSMA group were 13.44 and 29.84, respectively. A significant difference was observed in the median SUV_max results of metastatic lesions between OM and MM disease (p<0.05). Median values of SUV_max calculated from the prostatic site in OM and MM disease were 7.83 and 12.29 respectively in ¹⁸F-FDG; 26.23 and 26.74 in the ⁶⁸Ga PSMA group. No significant difference was found in the SUV_max results of the prostatic site between OM and MM disease (p>0.05).

Conclusion

SUV_max results of metastatic lesions are significantly higher in patients with MM than in patients with OM disease in patients with PC, which may be secondary to their different biological contents in terms of aggressiveness.

Prognostic role of baseline 18F-FDG pet/CT in stage I and stage ii non-small cell lung cancer

OBJECTIVE

investigate the prognostic role of baseline ¹⁸F-FDG PET/CT in stage I-II NSCLC.

MATERIAL AND METHODS

296 patients were included. Clinicopathological features and PET/CT semiquantitative parameters [standardized uptake value (SUV) body weight max (SUVmax), SUV body weight mean (SUVmean), SUV lean body mass (SUVlbm), SUV body surface area (SUVbsa), metabolic tumor volume (MTV), total lesion glycolysis (TLG), ratio SUVmax/liver (S-L) and ratio SUVmax/blood-pool (S-BP) were extracted]. Anova and Kruskall-Wallis tests were used to assess the relationship between these parameters. Kaplan-Meier, univariate and multivariate analysis were performed to search independent prognostic factors for progression free (PFS), overall survival (OS) and disease specific survival (DSS).

RESULTS

Correlation between PET/CT semiquantitative parameters and histology, stage, size, grading and presence of nodal metastasis were reported. Mean PFS was 28.1 months, relapse/progression of disease occurred in 85 patients (28.7%). Mean OS was 33.3 months, death occurred in 43 patients (14.5%); specific death by NSCLC occurred in 26 subjects (8.8%). Kaplan-Meier analyses revealed most of semiquantitative parameters as predictive for PFS, OS and DSS. For DSS, this was confirmed when dividing between patients with surgery and surgery with other therapies. SUVmax, SUVmean, SUVlbm, SUVbsa and S-L revealed to be independent prognosticators for OS and DSS. S-BP was an independent prognosticator for DSS. SUVmax, SUVmean, SUVlbm, S-L and S-BP were confirmed as independent prognosticators for DSS in the group of patients treated with surgery and subsequent adjuvant therapy.

CONCLUSION

Baseline ¹⁸F-FDG PET/CT semiquantitative parameters are confirmed as prognostic tools for stage I-II NSCLC, in particular for DSS.

Atypical location of primary cardiac lymphoma in the left heart with atypical clinical presentation: A case report and literature review

Background

Primary cardiac lymphoma (PCL) is a rare and aggressive cardiac tumor with very poor prognosis that occurs mostly in the right cardiac cavity. Early diagnosis and treatment may improve its prognosis. In the present report, we describe the diagnosis and treatment of a primary cardiac diffuse large B-cell lymphoma (PC-DLBCL) with atypical location and clinical presentation. Additionally, a literature review was conducted to summarize the current knowledge of the disease.

Case Presentation

A 71-year-old man visited his local hospital because of syncope, recurrent chest tightness, shortness of breath, palpitations, and profuse sweating for more than 20 days. Chest radiography revealed a mediastinal mass. Cardiac computed tomography (CT) showed multiple enlarged mediastinal lymph nodes. Transthoracic echocardiography (TTE) showed a cardiac mass in the posterior-inferior wall of the left atrium. He was then transferred to our hospital for positron emission tomography-CT (PET-CT) which showed active uptake of fluorodeoxyglucose both in the cardiac mass and in the multiple enlarged mediastinal lymph nodes. Biopsy of the enlarged mediastinal lymph nodes was carried out by using video-assisted thoracic surgery (VATS) technique, and pathological examination confirmed the subtype of PC-DLBCL, Stage IV, NCCN IPI 3. Therefore, the patient received a combination of chemotherapy and immunotherapy with R-CDOP (rituximab, cyclophosphamide, liposome doxorubicin, vincristine, and prednisone). After four courses of treatment in 4 months, the cardiac lymphoma and the enlarged mediastinal lymph nodes achieved complete remission with mild side effects of the chemotherapy.

Conclusion

Early diagnosis and a precise choice of chemotherapy and immunotherapy based on cardiac imaging and pathological examination may improve the prognosis of PC-DLBCL in an atypical location.

Advanced Techniques in Head and Neck Cancer Imaging: Guide to Precision Cancer Management

Precision treatment requires precision imaging. With the advent of various advanced techniques in head and neck cancer treatment, imaging has become an integral part of the multidisciplinary approach to head and neck cancer care from diagnosis to staging and also plays a vital role in response evaluation in various tumors. Conventional anatomic imaging (CT scan, MRI, ultrasound) remains basic and focuses on defining the anatomical extent of the disease and its spread. Accurate assessment of the biological behavior of tumors, including tumor cellularity, growth, and response evaluation, is evolving with recent advances in molecular, functional, and hybrid/multiplex imaging. Integration of these various advanced diagnostic imaging and nonimaging methods aids understanding of cancer pathophysiology and provides a more comprehensive evaluation in this era of precision treatment. Here we discuss the current status of various advanced imaging techniques and their applications in head and neck cancer imaging.

Misinterpretation of an inflammatory FDG uptake in a patient treated for Hodgkin lymphoma: a case report

Hodgkin Lymphoma (HL) is a malignancy involving lymph nodes and lymphatic system. [¹⁸F]F-FDG PET/CT (FDG-PET) imaging is routinely used for staging, to assess early chemotherapy response (interim FDG-PET), at the end of treatment (EoT FDG-PET) and for the identification of disease recurrence. We present a case of a 39-year-old man treated for HL. FDG-PET scans performed after first line therapy (both Interim PET and at the end of therapy) demonstrated a persistent and significant mediastinal FDG uptake. The patient was treated with a second line therapy but the FDG-PET uptake did not change. After board discussion a new surgical, thoracoscopy-guided biopsy was performed. Histopathology demonstrated a dense fibrous tissue with occasional chronic inflammatory infiltrates. Persistent FDG-PET positivity may suggest refractory or relapsed disease. However, occasionally, non-malignant conditions are responsible for a persistent FDG uptake, not related to primary disease. An accurate evaluation of clinical history and previous imaging exams is mandatory for clinicians and others experts to avoid misinterpretations of FDG-PET results. Nevertheless, in some cases, only a more invasive procedure, such as a biopsy, may finally lead to a definitive diagnosis.

Role of Radiomics Features and Machine Learning for the Histological Classification of Stage I and Stage II NSCLC at [18F]FDG PET/CT: A Comparison between Two PET/CT Scanners

The aim of this study was to compare two different PET/CT tomographs for the evaluation of the role of radiomics features (RaF) and machine learning (ML) in the prediction of the histological classification of stage I and II non-small-cell lung cancer (NSCLC) at baseline [18F]FDG PET/CT. A total of 227 patients were retrospectively included and, after volumetric segmentation, RaF were extracted. All of the features were tested for significant differences between the two scanners and considering both the scanners together, and their performances in predicting the histology of NSCLC were analyzed by testing of different ML approaches: Logistic Regressor (LR), k-Nearest Neighbors (kNN), Decision Tree (DT) and Random Forest (RF). In general, the models with best performances for all the scanners were kNN and LR and moreover the kNN model had better performances compared to the other. The impact of the PET/CT scanner used for the acquisition of the scans on the performances of RaF was evident: mean area under the curve (AUC) values for scanner 2 were lower compared to scanner 1 and both the scanner considered together. In conclusion, our study enabled the selection of some [18F]FDG PET/CT RaF and ML models that are able to predict with good performances the histological subtype of NSCLC. Furthermore, the type of PET/CT scanner may influence these performances.

Application of Metabolic Reprogramming to Cancer Imaging and Diagnosis

Cellular metabolism governs the signaling that supports physiological mechanisms and homeostasis in an individual, including neuronal transmission, wound healing, and circadian clock manipulation. Various factors have been linked to abnormal metabolic reprogramming, including gene mutations, epigenetic modifications, altered protein epitopes, and their involvement in the development of disease, including cancer. The presence of multiple distinct hallmarks and the resulting cellular reprogramming process have gradually revealed that these metabolism-related molecules may be able to be used to track or prevent the progression of cancer. Consequently, translational medicines have been developed using metabolic substrates, precursors, and other products depending on their biochemical mechanism of action. It is important to note that these metabolic analogs can also be used for imaging and therapeutic purposes in addition to competing for metabolic functions. In particular, due to their isotopic labeling, these compounds may also be used to localize and visualize tumor cells after uptake. In this review, the current development status, applicability, and limitations of compounds targeting metabolic reprogramming are described, as well as the imaging platforms that are most suitable for each compound and the types of cancer to which they are most appropriate.

Single Camera-Based Dual-Channel Near-Infrared Fluorescence Imaging system

In this study, we propose a single camera-based dual-channel near-infrared (NIR) fluorescence imaging system that produces color and dual-channel NIR fluorescence images in real time. To simultaneously acquire color and dual-channel NIR fluorescence images of two fluorescent agents, three cameras and additional optical parts are generally used. As a result, the volume of the image acquisition unit increases, interfering with movements during surgical procedures and increasing production costs. In the system herein proposed, instead of using three cameras, we set a single camera equipped with two image sensors that can simultaneously acquire color and single-channel NIR fluorescence images, thus reducing the volume of the image acquisition unit. The single-channel NIR fluorescence images were time-divided into two channels by synchronizing the camera and two excitation lasers, and the noise caused by the crosstalk effect between the two fluorescent agents was removed through image processing. To evaluate the performance of the system, experiments were conducted for the two fluorescent agents to measure the sensitivity, crosstalk effect, and signal-to-background ratio. The compactness of the resulting image acquisition unit alleviates the inconvenient movement obstruction of previous devices during clinical and animal surgery and reduces the complexity and costs of the manufacturing process, which may facilitate the dissemination of this type of system.

Development of scalable lymphatic system in the 4D XCAT phantom: Application to quantitative evaluation of lymphoma PET segmentations

BACKGROUND

Digital anthropomorphic phantoms, such as the 4D extended cardiac-torso (XCAT) phantom, are actively used to develop, optimize, and evaluate a variety of imaging applications, allowing for realistic patient modeling and knowledge of ground truth. The XCAT phantom defines the activity and attenuation for a simulated patient, which includes a complete set of organs, muscle, bone, and soft tissue, while also accounting for cardiac and respiratory motion. However, the XCAT phantom does not currently include the lymphatic system, critical for evaluating medical imaging tasks such as sentinel node detection, node density measurement, and radiation dosimetry.

PURPOSE

In this study, we aimed to develop a scalable lymphatic system in the XCAT phantom, to facilitate improved research of the lymphatic system in medical imaging. Using this scalable lymphatic system, we modeled the lymph node conglomerate pathology that is characteristically observed in primary mediastinal B-cell lymphoma (PMBCL). As an extended application, we evaluated positron emission tomography (PET) image quantification of metabolic tumor volume (MTV) and total lesion glycolysis (TLG) of these simulated lymphomas, though the phantoms may be applied to other imaging modalities and study design paradigms (e.g., image quality, detection).

METHODS

A template model for the lymphatic system was developed based on anatomical data from the Visible Human Project of the National Library of Medicine. The segmented nodes and vessels were fit with non-uniform rational basis spline surfaces, and multichannel large deformation diffeomorphic metric mapping was used to propagate the template to different XCAT anatomies. To model conglomerates observed in PMBCL, lymph nodes were enlarged, converged within the mediastinum, and tracer concentration was increased. We used the phantoms as inputs to a PET simulation tool, which generated images using ordered subsets expectation maximization reconstruction with 2-8 mm Gaussian filters. Fixed thresholding (FT) and gradient segmentation were used to determine MTV and TLG. Percent bias (%Bias) and coefficient of variation (COV) were computed as measures of accuracy and precision, respectively, for each MTV and TLG measurement.

RESULTS

Using the methodology described above, we introduced a scalable lymphatic system in the XCAT phantom, which allows for the radioactivity and attenuation ground truth to be generated in 116 ± 2.5 s using a 2.3 GHz processor. Within the Rhinoceros interface, lymph node anatomy and function were modified to create a cohort of 10 phantoms with lymph node conglomerates. Using the lymphoma phantoms to evaluate PET quantification of MTV, mean %Bias values were -9.3%, -41.3%, and 20.9%, while COV values were 4.08%, 7.6%, and 3.4% using 25% FT, 40% FT, and gradient segmentations, respectively. Comparatively for TLG, mean %Bias values were -27.4%, -45.8%, and -16.0%, while COV values were 1.9%, 5.7%, and 1.4%, for the 25% FT, 40% FT, and gradient segmentations, respectively.

CONCLUSIONS

In this work, we upgraded the XCAT phantom to include a lymphatic system, comprised of a network of 276 scalable lymph nodes and corresponding vessels. As an application, we created a cohort of phantoms with lymph node conglomerates to evaluate lymphoma quantification in PET imaging, which highlights an important application of this work.

The role of PET/CT in thyroid autoimmune diseases

Autoimmune thyroid diseases (AITD) are a heterogeneous group of disorders. They include, in particular, Graves' disease and Hashimoto's thyroiditis with a wide range of different functional status ranging from subclinical biochemical abnormalities to severe hyperthyroidism or severe hypothyroidism respectively. Furthermore, other conditions more frequently infectious or drug related can cause an immune reaction in the thyroid tissue. In AITDs, positron emission tomography/computed tomography (PET/CT) does not play a primary role for disease diagnosis or management, but accidental findings can occur in both symptomatic and asymptomatic patients, and they should be recognized and well interpreted. A comprehensive literature search of the PubMed databases was conducted to identify papers (systematic review, prospective and retrospective study, case report) evaluating the role of PET/CT in thyroid autoimmune diseases. Thyroid diffuse uptake of 18F-fluoro-2-deoxy-2-d-glucose ([18F]FDG) has been shown to be frequently associated with AITDs, but also with immune-induced thyroid disorders related to SARS-CoV-2 or immunotherapy, while malignant lesions more often have a focal aspect. Other radiopharmaceuticals as [68Ga]-DOTA-peptides, [68Ga]-fibroblast activation protein inhibitors (FAPIs) and [68Ga]-prostate specific membrane antigen ([68Ga]-PSMA) showed similar findings. In conclusion, PET/CT scan in AITDs does not play a primary role in the diagnosis, but the occasional finding of a thyroid uptake must always be described in the report and possibly investigated for a better patient's management.

Synthesis and In Vitro Evaluation of a Set of 6-Deoxy-6-thio-carboranyl d-Glucoconjugates Shed Light on the Substrate Specificity of the GLUT1 Transporter

Glucose- and sodium-dependent glucose transporters (GLUTs and SGLTs) play vital roles in human biology. Of the 14 GLUTs and 12 SGLTs, the GLUT1 transporter has gained the most widespread recognition because GLUT1 is overexpressed in several cancers and is a clinically valid therapeutic target. We have been pursuing a GLUT1-targeting approach in boron neutron capture therapy (BNCT). Here, we report on surprising findings encountered with a set of 6-deoxy-6-thio-carboranyl d-glucoconjugates. In more detail, we show that even subtle structural changes in the carborane cluster, and the linker, may significantly reduce the delivery capacity of GLUT1-based boron carriers. In addition to providing new insights on the substrate specificity of this important transporter, we reach a fresh perspective on the boundaries within which a GLUT1-targeting approach in BNCT can be further refined.

Imaging ligands targeting glypican-3 receptor expression in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the third leading cause of cancer mortality. Early detection of HCC is important since potentially curative therapies exist in the initial stages of HCC; no curative therapies exist for late-stage HCC. However, the initial detection of HCC remains challenging due to the lack of symptoms during the early stage of the disease. Other methods of screening and detecting HCC, including blood serum tests and conventional imaging methods, remain inadequate due to genetic differences between patients and the high background activity of liver tissues. Thus, there is a need for an accurate imaging agent for the diagnosis, staging, and prognosis of HCC. Glypican-3 (GPC3) is an oncofetal receptor responsible for regulating cell division, growth, and survival. GPC3 is a clinically relevant biomarker for imaging and therapeutics, as its expression is HCC tumor-specific and absent from normal and other pathological liver tissues. The development of novel GPC3-targeting imaging agents has encompassed three classes of biomolecules: peptides, antibodies, and aptamers. These biomolecules serve as constructs for diagnostic imaging (demonstrating potential as positron emission tomography [PET], single-photon emission tomography [SPECT], and optical imaging agents) and HCC treatment delivery. More than 20 unique ligands have been identified in the literature as showing specificity for the GPC3 receptor. Although several ligands are currently under clinical investigation as therapies for HCC, clinical translation of GPC3-targeting ligands as imaging agents is lacking. This review highlights the current landscape of ligands targeting GPC3 and describes their promising possibilities as imaging agents for HCC.

Volumetric parameters from [18 F]FDG PET/CT predicts survival in patients with high-grade gastroenteropancreatic neuroendocrine neoplasms

A positive fluorine-18 labelled 2-deoxy-2-fluoroglucose ([¹⁸ F]FDG) positron emission tomography/computed tomography (PET/CT) has been associated with more aggressive disease and less differentiated neuroendocrine neoplasms (NEN). Although a high maximum standardized uptake value (SUV_max ) predicts poor outcome in NEN, volumetric parameters from [¹⁸ F]FDG PET have not been evaluated for prognostication in a pure high-grade gastroenteropancreatic (GEP) NEN cohort. In this retrospective observational study, we evaluated the volumetric PET parameters total metabolic tumour volume (tMTV) and total total lesion glycolysis (tTLG) for independent prognostication of overall survival (OS). High-grade GEP NEN patients with [¹⁸ F]FDG PET/CT examination and biopsy within 90 days were included. Total MTV and tTLG were calculated using an adaptive thresholding software. Patients were dichotomised into low and high metabolic groups based on median tMTV and tTLG. OS was compared using Kaplan-Meier estimator and log-rank test. Uni and multivariable Cox regression was used to estimate effect sizes and adjust for tumour differentiation and SUV_max . Sixty-six patients (median age 64 years) were included with 14 NET G3 and 52 NEC cases after histological re-evaluation. Median tMTV was 208 cm³ and median tTLG 1899 g. Median OS in the low versus high tMTV-group was 21.2 versus 5.7 months (HR 2.53, p = 0.0007) and 22.8 versus 5.7 months (HR 2.42, p = 0.0012) in the tTLG-group. Adjusted for tumour differentiation and SUV_max , tMTV and tTLG still predicted for poor OS, and both tMTV and tTLG were stronger prognostic parameters than SUV_max . Both regression models showed a strong association between volumetric parameters and OS for both neuroendocrine tumours (NET) G3 and neuroendocrine carcinomas (NEC). OS for the tTLG low metabolic NEC was much higher than for the tTLG high metabolic NET G3 (18.3 vs. 5.7 months). High-grade GEP NEN patients with high tMTV or tTLG had a worse OS regardless of tumour differentiation (NET G3 or NEC). Volumetric PET parameters were stronger prognostic parameters than SUV_max .