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Li Y, van Rijn-Dekker MI, de Vette SPM, van der Schaaf A, van den Bosch L, Langendijk JA, van Dijk LV, Sijtsema NM. Late-xerostomia prediction model based on 18F-FDG PET image biomarkers of the main salivary glands. Radiother Oncol 2024; 196:110319. [PMID: 38702014 DOI: 10.1016/j.radonc.2024.110319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Revised: 04/13/2024] [Accepted: 04/26/2024] [Indexed: 05/06/2024]
Abstract
BACKGROUND AND PURPOSE Recently, a comprehensive xerostomia prediction model was published, based on baseline xerostomia, mean dose to parotid glands (PG) and submandibular glands (SMG). Previously, PET imaging biomarkers (IBMs) of PG were shown to improve xerostomia prediction. Therefore, this study aimed to explore the potential improvement of the additional PET-IBMs from both PG and SMG to the recent comprehensive xerostomia prediction model (i.e., the reference model). MATERIALS AND METHODS Totally, 540 head and neck cancer patients were split into training and validation cohorts. PET-IBMs from the PG and SMG, were selected using bootstrapped forward selection based on the reference model. The IBMs from both the PG and SMG with the highest selection frequency were added to the reference model, resulting in a PG-IBM model and a SMG-IBM model which were combined into a composite model. Model performance was assessed using the area under the curve (AUC). Likelihood ratio test compared the predictive performance between the reference model and models including IBMs. RESULTS The final selected PET-IBMs were 90th percentile of the PG SUV and total energy of the SMG SUV. The additional two PET-IBMs in the composite model improved the predictive performance of the reference model significantly. The AUC of the reference model and the composite model were 0.67 and 0.69 in the training cohort, and 0.71 and 0.73 in the validation cohort, respectively. CONCLUSION The composite model including two additional PET-IBMs from PG and SMG improved the predictive performance of the reference xerostomia model significantly, facilitating a more personalized prediction approach.
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Affiliation(s)
- Yan Li
- Department of Radiation Oncology, University Medical Centre Groningen, University of Groningen, The Netherlands.
| | - Maria Irene van Rijn-Dekker
- Department of Radiation Oncology, University Medical Centre Groningen, University of Groningen, The Netherlands
| | | | - Arjen van der Schaaf
- Department of Radiation Oncology, University Medical Centre Groningen, University of Groningen, The Netherlands
| | - Lisa van den Bosch
- Department of Radiation Oncology, University Medical Centre Groningen, University of Groningen, The Netherlands
| | | | - Lisanne Vania van Dijk
- Department of Radiation Oncology, University Medical Centre Groningen, University of Groningen, The Netherlands
| | - Nanna Maria Sijtsema
- Department of Radiation Oncology, University Medical Centre Groningen, University of Groningen, The Netherlands
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Pells S, Zeraatkar N, Kalluri KS, Moore SC, May M, Furenlid LR, Kupinski MA, Kuo PH, King MA. Correction of multiplexing artefacts in multi-pinhole SPECT through temporal shuttering, de-multiplexing of projections, and alternating reconstruction. Phys Med Biol 2024; 69:10.1088/1361-6560/ad4f47. [PMID: 38776948 PMCID: PMC11212123 DOI: 10.1088/1361-6560/ad4f47] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Accepted: 05/22/2024] [Indexed: 05/25/2024]
Abstract
Objective.Single-photon emission computed tomography (SPECT) with pinhole collimators can provide high-resolution imaging, but is often limited by low sensitivity. Acquiring projections simultaneously through multiple pinholes affords both high resolution and high sensitivity. However, the overlap of projections from different pinholes on detectors, known as multiplexing, has been shown to cause artefacts which degrade reconstructed images.Approach.Multiplexed projection sets were considered here using an analytic simulation model of AdaptiSPECT-C-a brain-dedicated multi-pinhole SPECT system. AdaptiSPECT-C has fully adaptable aperture shutters, so can acquire projections with a combination of multiplexed and non-multiplexed frames using temporal shuttering. Two strategies for reducing multiplex artefacts were considered: an algorithm to de-multiplex projections, and an alternating reconstruction strategy for projections acquired with a combination of multiplexed and non-multiplexed frames. Geometric and anthropomorphic digital phantoms were used to assess a number of metrics.Main results.Both de-multiplexing strategies showed a significant reduction in image artefacts and improved fidelity, image uniformity, contrast recovery and activity recovery (AR). In all cases, the two de-multiplexing strategies resulted in superior metrics to those from images acquired with only mux-free frames. The de-multiplexing algorithm provided reduced image noise and superior uniformity, whereas the alternating strategy improved contrast and AR.Significance.The use of these de-multiplexing algorithms means that multi-pinhole SPECT systems can acquire projections with more multiplexing without degradation of images.
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Affiliation(s)
- Sophia Pells
- Department of Radiology, University of Massachusetts Chan Medical School, Worcester, MA, United States of America
| | - Navid Zeraatkar
- Department of Radiology, University of Massachusetts Chan Medical School, Worcester, MA, United States of America
| | - Kesava S Kalluri
- Department of Radiology, University of Massachusetts Chan Medical School, Worcester, MA, United States of America
| | - Stephen C Moore
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America
| | - Micaehla May
- James C. Wyant College of Optical Sciences, The University of Arizona, Tucson, AZ, United States of America
| | - Lars R Furenlid
- James C. Wyant College of Optical Sciences, The University of Arizona, Tucson, AZ, United States of America
- Department of Medical Imaging, The University of Arizona, Tucson, AZ, United States of America
| | - Matthew A Kupinski
- James C. Wyant College of Optical Sciences, The University of Arizona, Tucson, AZ, United States of America
| | - Phillip H Kuo
- Department of Medical Imaging, The University of Arizona, Tucson, AZ, United States of America
- Department of Medicine, The University of Arizona, Tucson, AZ, United States of America
- Department of Biomedical Engineering, The University of Arizona, Tucson, AZ, United States of America
| | - Michael A King
- Department of Radiology, University of Massachusetts Chan Medical School, Worcester, MA, United States of America
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Zhou M, Yin X, Chen B, Hu S, Zhou W. A PET probe targeting polyamine transport system for precise tumor diagnosis and therapy. Asian J Pharm Sci 2024; 19:100924. [PMID: 38903130 PMCID: PMC11186966 DOI: 10.1016/j.ajps.2024.100924] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2023] [Revised: 02/02/2024] [Accepted: 03/04/2024] [Indexed: 06/22/2024] Open
Abstract
Polyamine metabolism dysregulation is a hallmark of many cancers, offering a promising avenue for early tumor theranostics. This study presents the development of a nuclear probe derived from spermidine (SPM) for dual-purpose tumor PET imaging and internal radiation therapy. The probe, radiolabeled with either [68Ga]Ga for diagnostic applications or [177Lu]Lu for therapeutic use, was synthesized with exceptional purity, stability, and specific activity. Extensive testing involving 12 different tumor cell lines revealed remarkable specificity towards B16 melanoma cells, showcasing outstanding tumor localization and target-to-non-target ratio. Mechanistic investigations employing polyamines, non-labeled precursor, and polyamine transport system (PTS) inhibitor, consistently affirmed the probe's targetability through recognition of the PTS. Notably, while previous reports indicated PTS upregulation in various tumor types for targeted therapy, this study observed no positive signals, highlighting a concentration-dependent discrepancy between targeting for therapy and diagnosis. Furthermore, when labeled with [177Lu], the probe demonstrated its therapeutic potential by effectively controlling tumor growth and extending mouse survival. Investigations into biodistribution, excretion, and biosafety in healthy humans laid a robust foundation for clinical translation. This study introduces a versatile SPM-based nuclear probe with applications in precise tumor theranostics, offering promising prospects for clinical implementation.
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Affiliation(s)
- Ming Zhou
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, Changsha 410008, China
- Xiangya School of Pharmaceutical Sciences, Central South University, Changsha 410013, China
| | - Xiaoqin Yin
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, Changsha 410008, China
- Xiangya School of Pharmaceutical Sciences, Central South University, Changsha 410013, China
| | - Bei Chen
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, Changsha 410008, China
| | - Shuo Hu
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, Changsha 410008, China
- Key Laboratory of Biological Nanotechnology of National Health Commission, Changsha 410008, China
- National Clinical Research Center for Geriatric Disorders (Xiangya), Changsha 410008, China
| | - Wenhu Zhou
- Xiangya School of Pharmaceutical Sciences, Central South University, Changsha 410013, China
- National Clinical Research Center for Geriatric Disorders (Xiangya), Changsha 410008, China
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Bhandari A, Gu B, Kashkooli FM, Zhan W. Image-based predictive modelling frameworks for personalised drug delivery in cancer therapy. J Control Release 2024; 370:721-746. [PMID: 38718876 DOI: 10.1016/j.jconrel.2024.05.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2024] [Revised: 04/11/2024] [Accepted: 05/02/2024] [Indexed: 05/19/2024]
Abstract
Personalised drug delivery enables a tailored treatment plan for each patient compared to conventional drug delivery, where a generic strategy is commonly employed. It can not only achieve precise treatment to improve effectiveness but also reduce the risk of adverse effects to improve patients' quality of life. Drug delivery involves multiple interconnected physiological and physicochemical processes, which span a wide range of time and length scales. How to consider the impact of individual differences on these processes becomes critical. Multiphysics models are an open system that allows well-controlled studies on the individual and combined effects of influencing factors on drug delivery outcomes while accommodating the patient-specific in vivo environment, which is not economically feasible through experimental means. Extensive modelling frameworks have been developed to reveal the underlying mechanisms of drug delivery and optimise effective delivery plans. This review provides an overview of currently available models, their integration with advanced medical imaging modalities, and code packages for personalised drug delivery. The potential to incorporate new technologies (i.e., machine learning) in this field is also addressed for development.
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Affiliation(s)
- Ajay Bhandari
- Biofluids Research Lab, Department of Mechanical Engineering, Indian Institute of Technology (Indian School of Mines), Dhanbad, India
| | - Boram Gu
- School of Chemical Engineering, Chonnam National University, Gwangju, Republic of Korea
| | | | - Wenbo Zhan
- School of Engineering, University of Aberdeen, Aberdeen, UK.
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Lan W, Sari H, Rominger A, Fougère CL, Schmidt FP. Optimization and impact of sensitivity mode on abbreviated scan protocols with population-based input function for parametric imaging of [ 18F]-FDG for a long axial FOV PET scanner. Eur J Nucl Med Mol Imaging 2024:10.1007/s00259-024-06745-3. [PMID: 38763962 DOI: 10.1007/s00259-024-06745-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Accepted: 04/28/2024] [Indexed: 05/21/2024]
Abstract
BACKGROUND The long axial field of view, combined with the high sensitivity of the Biograph Vision Quadra PET/CT scanner enables the precise deviation of an image derived input function (IDIF) required for parametric imaging. Traditionally, this requires an hour-long dynamic PET scan for [18F]-FDG, which can be significantly reduced by using a population-based input function (PBIF). In this study, we expand these examinations and include the scanner's ultra-high sensitivity (UHS) mode in comparison to the high sensitivity (HS) mode and evaluate the potential for further shortening of the scan time. METHODS Patlak Ki and DV estimates were determined by the indirect and direct Patlak methods using dynamic [18F]-FDG data of 6 oncological patients with 26 lesions (0-65 min p.i.). Both sensitivity modes for different number/duration of PET data frames were compared, together with the potential of using abbreviated scan durations of 20, 15 and 10 min by using a PBIF. The differences in parametric images and tumour-to-background ratio (TBR) due to the shorter scans using the PBIF method and between the sensitivity modes were assessed. RESULTS A difference of 3.4 ± 7.0% (Ki) and 1.2 ± 2.6% (DV) was found between both sensitivity modes using indirect Patlak and the full IDIF (0-65 min). For the abbreviated protocols and indirect Patlak, the UHS mode resulted in a lower bias and higher precision, e.g., 45-65 min p.i. 3.8 ± 4.4% (UHS) and 6.4 ± 8.9% (HS), allowing shorter scan protocols, e.g. 50-65 min p.i. 4.4 ± 11.2% (UHS) instead of 7.3 ± 20.0% (HS). The variation of Ki and DV estimates for both Patlak methods was comparable, e.g., UHS mode 3.8 ± 4.4% and 2.7 ± 3.4% (Ki) and 14.4 ± 2.7% and 18.1 ± 7.5% (DV) for indirect and direct Patlak, respectively. Only a minor impact of the number of Patlak frames was observed for both sensitivity modes and Patlak methods. The TBR obtained with direct Patlak and PBIF was not affected by the sensitivity mode, was higher than that derived from the SUV image (6.2 ± 3.1) and degraded from 20.2 ± 12.0 (20 min) to 10.6 ± 5.4 (15 min). Ki and DV estimate images showed good agreement (UHS mode, RC: 6.9 ± 2.3% (Ki), 0.1 ± 3.1% (DV), peak signal-to-noise ratio (PSNR): 64.5 ± 3.3 dB (Ki), 61.2 ± 10.6 dB (DV)) even for abbreviated scan protocols of 50-65 min p.i. CONCLUSIONS Both sensitivity modes provide comparable results for the full 65 min dynamic scans and abbreviated scans using the direct Patlak reconstruction method, with good Ki and DV estimates for 15 min short scans. For the indirect Patlak approach the UHS mode improved the Ki estimates for the abbreviated scans.
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Affiliation(s)
- W Lan
- Department of Nuclear Medicine and Clinical Molecular Imaging, University Hospital Tuebingen, Tuebingen, Germany
| | - H Sari
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
| | - A Rominger
- Department of Nuclear Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - C la Fougère
- Department of Nuclear Medicine and Clinical Molecular Imaging, University Hospital Tuebingen, Tuebingen, Germany
- Cluster of Excellence iFIT (EXC 2180) "Image Guided and Functionally Instructed Tumor Therapies", University of Tuebingen, Tuebingen, Germany
| | - F P Schmidt
- Department of Nuclear Medicine and Clinical Molecular Imaging, University Hospital Tuebingen, Tuebingen, Germany.
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, University of Tuebingen, Tuebingen, Germany.
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Keijzer K, de Boer JW, van Doesum JA, Noordzij W, Huls GA, van Dijk LV, van Meerten T, Niezink AGH. Reducing and controlling metabolic active tumor volume prior to CAR T-cell infusion can improve survival outcomes in patients with large B-cell lymphoma. Blood Cancer J 2024; 14:41. [PMID: 38448432 PMCID: PMC10917787 DOI: 10.1038/s41408-024-01022-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Revised: 02/26/2024] [Accepted: 02/27/2024] [Indexed: 03/08/2024] Open
Abstract
Bridging therapy before CD19-directed chimeric antigen receptor (CAR) T-cell infusion is frequently applied in patients with relapsed or refractory Large B-cell lymphoma (r/r LBCL). This study aimed to assess the influence of quantified MATV and MATV-dynamics, between pre-apheresis (baseline) and pre-lymphodepleting chemotherapy (pre-LD) MATV, on CAR T-cell outcomes and toxicities in patients with r/r LBCL. MATVs were calculated semi-automatically at baseline (n = 74) and pre-LD (n = 68) in patients with r/r LBCL who received axicabtagene ciloleucel. At baseline, patients with a low MATV (< 190 cc) had a better time to progression (TTP) and overall survival (OS) compared to high MATV patients (p < 0.001). High MATV patients who remained stable or reduced upon bridging therapy showed a significant improvement in TTP (p = 0.041) and OS (p = 0.015), compared to patients with a high pre-LD MATV (> 480 cc). Furthermore, high MATV baseline was associated with severe cytokine release syndrome (CRS, p = 0.001). In conclusion, patients with low baseline MATV had the best TTP/OS and effective reduction or controlling MATV during bridging improved survival outcomes in patients with a high baseline MATV, providing rationale for the use of more aggressive bridging regimens.
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Affiliation(s)
- Kylie Keijzer
- Department of Hematology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713GZ, Groningen, The Netherlands
- Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713GZ, Groningen, The Netherlands
| | - Janneke W de Boer
- Department of Hematology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713GZ, Groningen, The Netherlands
| | - Jaap A van Doesum
- Department of Hematology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713GZ, Groningen, The Netherlands
| | - Walter Noordzij
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713GZ, Groningen, The Netherlands
| | - Gerwin A Huls
- Department of Hematology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713GZ, Groningen, The Netherlands
| | - Lisanne V van Dijk
- Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713GZ, Groningen, The Netherlands
| | - Tom van Meerten
- Department of Hematology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713GZ, Groningen, The Netherlands
| | - Anne G H Niezink
- Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713GZ, Groningen, The Netherlands.
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Olthof EP, Wenzel HHB, van der Velden J, Stalpers LJA, Mom CH, van der Aa MA. Treatment Strategies Guided by [18F]FDG-PET/CT in Patients with Locally Advanced Cervical Cancer and [18F]FDG-Positive Lymph Nodes. Cancers (Basel) 2024; 16:717. [PMID: 38398108 PMCID: PMC10887300 DOI: 10.3390/cancers16040717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 01/22/2024] [Accepted: 02/06/2024] [Indexed: 02/25/2024] Open
Abstract
BACKGROUND Modern treatment guidelines for women with advanced cervical cancer recommend staging using 2-deoxy-2-[18F]fluoro-D-glucose positron emission computed tomography ([18F]FDG-PET/CT). However, the risk of false-positive nodes and therapy-related adverse events requires caution in treatment planning. Using data from the Netherlands Cancer Registry (NCR), we estimated the impact of [18F]FDG-PET/CT on treatment management in women with locally advanced cervical cancer, i.e., on nodal boosting, field extension, and/or debulking in cases of suspected lymph nodes. METHODS Women diagnosed between 2009 and 2017, who received chemoradiotherapy for International Federation of Gynaecology and Obstetrics (2009) stage IB2, IIA2-IVB cervical cancer with an [18F]FDG-positive node, were retrospectively selected from the NCR database. Patients with pathological nodal examination before treatment were excluded. The frequency of nodal boosting, extended-field radiotherapy, and debulking procedures applied to patients with [18F]FDG-positive lymph nodes was evaluated. RESULTS Among the 434 eligible patients with [18F]FDG-positive nodes, 380 (88%) received interventions targeting these lymph nodes: 84% of these 380 patients received nodal boosting, 78% extended-field radiotherapy, and 12% debulking surgery. [18F]FDG-positive nodes in patients receiving these treatments were more likely to be classified as suspicious than inconclusive (p = 0.009), located in the para-aortic region (p < 0.001), and larger (p < 0.001) than in patients who did not receive these treatments. CONCLUSION While existing guidelines advocate [18F]FDG-PET/CT-guided treatment planning for the management of advanced cervical cancer, this study highlights that not all cases of [18F]FDG-positive nodes received an intervention, possibly due to the risk of false-positive results. Improvement of nodal staging may reduce suboptimal treatment planning.
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Affiliation(s)
- Ester P. Olthof
- Department of Research & Development, Netherlands Comprehensive Cancer Organisation, 3511 LC Utrecht, The Netherlands; (H.H.B.W.); (M.A.v.d.A.)
- Centre for Gynaecologic Oncology Amsterdam (CGOA), Department of Gynaecological Oncology, Amsterdam University Medical Centre, 1081 HV Amsterdam, The Netherlands; (J.v.d.V.); (C.H.M.)
| | - Hans H. B. Wenzel
- Department of Research & Development, Netherlands Comprehensive Cancer Organisation, 3511 LC Utrecht, The Netherlands; (H.H.B.W.); (M.A.v.d.A.)
| | - Jacobus van der Velden
- Centre for Gynaecologic Oncology Amsterdam (CGOA), Department of Gynaecological Oncology, Amsterdam University Medical Centre, 1081 HV Amsterdam, The Netherlands; (J.v.d.V.); (C.H.M.)
| | - Lukas J. A. Stalpers
- Department of Radiation Oncology, Amsterdam University Medical Centre, 1055 AZ Amsterdam, The Netherlands;
| | - Constantijne H. Mom
- Centre for Gynaecologic Oncology Amsterdam (CGOA), Department of Gynaecological Oncology, Amsterdam University Medical Centre, 1081 HV Amsterdam, The Netherlands; (J.v.d.V.); (C.H.M.)
| | - Maaike A. van der Aa
- Department of Research & Development, Netherlands Comprehensive Cancer Organisation, 3511 LC Utrecht, The Netherlands; (H.H.B.W.); (M.A.v.d.A.)
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Olthof EP, Bergink-Voorthuis BJ, Wenzel HHB, Mongula J, van der Velden J, Spijkerboer AM, Adam JA, Bekkers RLM, Beltman JJ, Slangen BFM, Nijman HW, Smolders RGV, van Trommel NE, Zusterzeel PLM, Zweemer RP, Stalpers LJA, Mom CH, van der Aa MA. Diagnostic accuracy of MRI, CT, and [ 18F]FDG-PET-CT in detecting lymph node metastases in clinically early-stage cervical cancer - a nationwide Dutch cohort study. Insights Imaging 2024; 15:36. [PMID: 38332397 PMCID: PMC10853153 DOI: 10.1186/s13244-023-01589-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 11/29/2023] [Indexed: 02/10/2024] Open
Abstract
OBJECTIVES Imaging is increasingly used to assess lymph node involvement in clinically early-stage cervical cancer. This retrospective study aimed to evaluate the diagnostic accuracy of MRI, CT, and [18F]FDG-PET-CT. METHODS Women with International Federation of Gynaecology and Obstetrics (FIGO) 2009 stage IA2-IIA cervical cancer and pretreatment imaging between 2009 and 2017 were selected from the Netherlands Cancer Registry. Patient-based and region-based (i.e. pelvic and common iliac) nodal status was extracted from radiology reports. Pathology results were considered the reference standard for calculating accuracy indices. Multiple imputation was used for missing pathology to limit verification bias risk. RESULTS Nodal assessment was performed in 1676 patients with MRI, 926 with CT, and 379 with [18F]FDG-PET-CT, with suspicious nodes detected in 17%, 16%, and 48%, respectively. [18F]FDG-PET-CT was used to confirm MRI/CT results in 95% of patients. Pathology results were imputed for 30% of patients. [18F]FDG-PET-CT outperformed MRI and CT in detecting patient-based nodal metastases with sensitivities of 80%, 48%, and 40%, and AUCs of 0.814, 0.706, and 0.667, respectively, but not in specificity: 79%, 92%, and 92%. Region-based analyses showed similar indices in the pelvic region, but worse performance in the common iliac region with AUCs of 0.575, 0.554, and 0.517, respectively. CONCLUSIONS [18F]FDG-PET-CT outperformed MRI and CT in detecting nodal metastases, which may be related to its use as a verification modality. However, MRI and CT had the highest specificity. As MRI is generally performed routinely to assess local and regional spread of cervical cancer, [18F]FDG-PET-CT can be used to confirm suspicious nodes. CRITICAL RELEVANCE STATEMENT Accurate assessment of the nodal status in clinically early-stage cervical cancer is essential for tumour staging, treatment decision making and prognosis. KEY POINTS • The accuracy of MRI, CT or [18F]FDG-PET-CT for nodal staging in early cervical cancer is a subject of discussion. • Overall, [18F]FDG-PET-CT outperformed MRI, followed by CT, when used as a verification modality. • Staging with MRI and the addition of [18F]FDG-PET-CT to verify high-risk cases seems to be a good approach.
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Affiliation(s)
- Ester P Olthof
- Department of Research & Development, Netherlands Comprehensive Cancer Organisation (IKNL), Godebaldkwartier 419, DT, Utrecht, 3511, The Netherlands.
- Department of Gynecological Oncology, Amsterdam University Medical Center, Center for Gynecologic Oncology Amsterdam (CGOA), Amsterdam, The Netherlands.
| | - Brenda J Bergink-Voorthuis
- Department of Health Technology and Services Research, Technical Medical Center, University of Twente, Enschede, The Netherlands
| | - Hans H B Wenzel
- Department of Research & Development, Netherlands Comprehensive Cancer Organisation (IKNL), Godebaldkwartier 419, DT, Utrecht, 3511, The Netherlands
| | - Jordy Mongula
- Department of Obstetrics and Gynaecology, Zuyderland Medical Center, Heerlen, The Netherlands
| | - Jacobus van der Velden
- Department of Gynecological Oncology, Amsterdam University Medical Center, Center for Gynecologic Oncology Amsterdam (CGOA), Amsterdam, The Netherlands
| | - Anje M Spijkerboer
- Department of Radiology, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Judit A Adam
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centre, University of Amsterdam, Amsterdam, The Netherlands
| | - Ruud L M Bekkers
- Department of Obstetrics and Gynaecology, Catharina Hospital, Eindhoven, The Netherlands
- Department of Obstetrics and Gynecology, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Obstetrics and Gynecology, Medical Center and GROW School for Oncology and Reproduction, Maastricht University, Maastricht, The Netherlands
| | - Jogchum J Beltman
- Department of Gynaecology, Leiden University Medical Center, Leiden, The Netherlands
| | - Brigitte F M Slangen
- Department of Obstetrics and Gynecology, Medical Center and GROW School for Oncology and Reproduction, Maastricht University, Maastricht, The Netherlands
| | - Hans W Nijman
- Department of Obstetrics and Gynaecology, University Medical Center Groningen, Groningen, The Netherlands
| | - Ramon G V Smolders
- Department of Gynaecological Oncology, Erasmus MC Cancer Institute University Medical Center, Rotterdam, The Netherlands
| | - Nienke E van Trommel
- Center for Gynaecologic Oncology Amsterdam (CGOA), The Netherlands Cancer Institute - Antoni van Leeuwenhoek, Amsterdam, The Netherlands
| | - Petra L M Zusterzeel
- Department of Obstetrics and Gynecology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Ronald P Zweemer
- Department of Gynaecological Oncology, University Medical Centre Utrecht, Utrecht Cancer Centre, Utrecht, The Netherlands
| | - Lukas J A Stalpers
- Department of Radiation Oncology, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Constantijne H Mom
- Department of Gynecological Oncology, Amsterdam University Medical Center, Center for Gynecologic Oncology Amsterdam (CGOA), Amsterdam, The Netherlands
| | - Maaike A van der Aa
- Department of Research & Development, Netherlands Comprehensive Cancer Organisation (IKNL), Godebaldkwartier 419, DT, Utrecht, 3511, The Netherlands
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Sagara H, Inoue K, Yaku H, Ohsawa A, Mano C, Morita T, Hiyama T, Muramatsu Y, Inaki A, Fujii H. A new simpler image quality index based on body size for FDG-PET/CT. Nucl Med Commun 2024; 45:93-101. [PMID: 37901919 DOI: 10.1097/mnm.0000000000001787] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2023]
Abstract
Noise equivalent count density (NEC density ) is often used to evaluate the image quality of whole-body fluorodeoxyglucose tomography tests. However, this index is calculated using the patient volume, which is difficult to obtain at every facility. In this study, we proposed new image quality indices that can be evaluated at all facilities. In total, 94 patients were enrolled in the study. The correlations of patients' body weight and BMI with volume were examined. New image quality indices normalized by body weight and BMI were defined as NEC bw and NEC bmi , respectively. Correlations between NEC bw , NEC bmi , and NEC density were examined. Further, the correlations between these two new indices and visual scores were evaluated. Good correlations were observed between volume and body weight (r = 0.861, P < 0.001) and between volume and BMI (r = 0.728, P < 0.001). NEC bw and NEC bmi correlated well with NEC density (r = 0.954 for NEC bw and r = 0.897 for NEC bmi , P < 0.001). These correlations improved when the examined bed positions were set to the same number. Additionally, the correlations of visual scores with NEC bw and NEC bmi were similar to those between the visual score and NEC density . Our investigation indicated that the newly proposed image quality metrics, NEC bw and NEC bmi , were easily calculated and as useful as NEC density for evaluating image quality when subjects had similar physiques.
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Affiliation(s)
- Hiroaki Sagara
- Division of Functional Imaging, Exploratory Oncology Research and Clinical Trial Center, National Cancer Center,
- Department of Radiologic Technology, National Cancer Center Hospital East, Kashiwa,
- Department of Radiological Sciences, Graduate School of Human Health Sciences, Tokyo Metropolitan University, Tokyo,
| | - Kazumasa Inoue
- Department of Radiological Sciences, Graduate School of Human Health Sciences, Tokyo Metropolitan University, Tokyo,
| | - Hideki Yaku
- RYUKYU ISG Co., Ltd, Kyoto,
- Optical Information Engineering, Systems Innovation Engineering, Graduate School of Advanced Technology and Science, Tokushima University 2-1 Minamijyousanjima-cho, Tokushima and
| | - Amon Ohsawa
- Department of Radiologic Technology, National Cancer Center Hospital East, Kashiwa,
| | - Chikara Mano
- Department of Radiologic Technology, National Cancer Center Hospital East, Kashiwa,
| | - Takahiro Morita
- Department of Diagnostic Radiology, National Cancer Center Hospital East, Kashiwa, Japan
| | - Takashi Hiyama
- Department of Diagnostic Radiology, National Cancer Center Hospital East, Kashiwa, Japan
| | - Yoshihisa Muramatsu
- Department of Radiologic Technology, National Cancer Center Hospital East, Kashiwa,
| | - Anri Inaki
- Division of Functional Imaging, Exploratory Oncology Research and Clinical Trial Center, National Cancer Center,
| | - Hirofumi Fujii
- Division of Functional Imaging, Exploratory Oncology Research and Clinical Trial Center, National Cancer Center,
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10
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Seth S, Gallagher EJ. Optimal Management of Insulin in Patients Undergoing 18F-Fluorodeoxyglucose Positron Emission Tomography Scans. Endocr Pract 2023; 29:705-709. [PMID: 37369292 PMCID: PMC10529812 DOI: 10.1016/j.eprac.2023.06.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Revised: 06/08/2023] [Accepted: 06/19/2023] [Indexed: 06/29/2023]
Abstract
OBJECTIVE The management of insulin injections and insulin pumps before 18F-fluorodeoxyglucose-positron emission tomography integrated computerized tomography (FDG-PET/CT) scans is an important area to investigate given the rising rate of diabetes, the significant association between diabetes and cancer, and the complex relationship among glucose, insulin, and FDG tumor uptake. The purpose of this study was to determine the recommendations around subcutaneous insulin administration, insulin pumps, and hybrid closed-loop systems before FDG-PET scans. METHODS We examined the websites of 100 hospitals selected from the 2022 US News and World Report top cancer hospitals for specific strategies around diabetes medication management before FDG-PET/CT scans. RESULTS Of the 100 hospital websites, 61 had instructions addressing patients with diabetes. Of the 61 hospitals, 47.5% (n = 29) referred patients to their provider for further instructions, 18% (n = 11) referred patients to their own internal radiology department for further instructions, 16.4% (n = 10) had instructions on oral diabetic medications, 23% (n = 14) had instructions on insulin, and 3.3% (n = 2) had instructions on insulin pump management. Most commonly, instructions were to stop insulin 3 to 4 hours before the study and direct patients to their referring provider for more detailed instructions (n = 7). CONCLUSION There is a lack of guidance and consensus among US cancer hospitals on managing insulin and continuous subcutaneous insulin infusions before FDG-PET/CT studies and a majority rely on referring providers to advise patients. However, society guidelines offer inconsistent recommendations and little research has been carried out to help guide referring providers. A multidisciplinary panel of specialists could help to guide practitioners on optimal management.
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Affiliation(s)
- Shivani Seth
- Department of Medicine, Icahn School of Medicine at Mount Sinai, New York
| | - Emily J Gallagher
- Division of Endocrinology, Diabetes and Bone Disease, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York; Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York.
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11
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Bacour YAA, van Kanten MP, Smit F, Comans EFI, Akarriou M, de Vet HCW, Voskuyl AE, van der Laken CJ, Smulders YM. Development of a simple standardized scoring system for assessing large vessel vasculitis by 18F-FDG PET-CT and differentiation from atherosclerosis. Eur J Nucl Med Mol Imaging 2023; 50:2647-2655. [PMID: 37115211 PMCID: PMC10317865 DOI: 10.1007/s00259-023-06220-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Accepted: 04/02/2023] [Indexed: 04/29/2023]
Abstract
PURPOSE This study is to develop a structured approach to distinguishing large-artery vasculitis from atherosclerosis using 18-fluorodeoxyglucose positron emission tomography combined with low-dose computed tomography (FDG PET/CT). METHODS FDG PET/CT images of 60 patients were evaluated, 30 having biopsy-proven giant cell arteritis (GCA; the most common form of large-artery vasculitis), and 30 with severe atherosclerosis. Images were evaluated by 12 nuclear medicine physicians using 5 criteria: FDG uptake pattern (intensity, distribution, circularity), the degree of calcification, and co-localization of calcifications with FDG-uptake. Criteria that passed agreement, and reliability tests were subsequently analysed for accuracy using receiver operator curve (ROC) analyses. Criteria that showed discriminative ability were then combined in a multi-component scoring system. Both initial and final 'gestalt' conclusion were also reported by observers before and after detailed examination of the images. RESULTS Agreement and reliability analyses disqualified 3 of the 5 criteria, leaving only FDG uptake intensity compared to liver uptake and arterial wall calcification for potential use in a scoring system. ROC analysis showed an area under the curve (AUC) of 0.90 (95%CI 0.87-0.92) for FDG uptake intensity. Degree of calcification showed poor discriminative ability on its own (AUC of 0.62; 95%CI 0.58-0.66). When combining presence of calcification with FDG uptake intensity into a 6-tiered scoring system, the AUC remained similar at 0.91 (95%CI 0.88-0.93). After exclusion of cases with arterial prostheses, the AUC increased to 0.93 (95%CI 0.91-0.95). The accuracy of the 'gestalt' conclusion was initially 89% (95%CI 86-91%) and increased to 93% (95%CI 91-95%) after detailed image examination. CONCLUSION Standardised assessment of arterial wall FDG uptake intensity, preferably combined with assessment of arterial calcifications into a scoring method, enables accurate, but not perfect, distinction between large artery vasculitis and atherosclerosis.
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Affiliation(s)
- Y A A Bacour
- Department of Internal Medicine, Amsterdam University Medical Center, Amsterdam 1007MB, PO Box 7057, Amsterdam, The Netherlands
| | - M P van Kanten
- Department of Internal Medicine, Amsterdam University Medical Center, Amsterdam 1007MB, PO Box 7057, Amsterdam, The Netherlands
| | - F Smit
- Department of Radiology and Nuclear Medicine, Alrijne Hospital, Simon, Smitweg 1, 2353GA, Leiderdorp, The Netherlands
| | - E F I Comans
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, PO Box 7057, Amsterdam 1007MB, Amsterdam, The Netherlands
| | - M Akarriou
- Department of Radiology and Nuclear Medicine, Spaarne Hospital, PO Box 770, Hoofddorp, 2130AT, The Netherlands
| | - H C W de Vet
- Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam University Medical Center, VrijeUniversiteit Amsterdam, Amsterdam 1007MB, PO Box 7057, Amsterdam, The Netherlands
| | - A E Voskuyl
- Amsterdam UMC-Location VUmc, Amsterdam Rheumatology and Immunology Center (ARC), Amsterdam 1007MB, PO Box 7057, Amsterdam, The Netherlands
| | - C J van der Laken
- Amsterdam UMC-Location VUmc, Amsterdam Rheumatology and Immunology Center (ARC), Amsterdam 1007MB, PO Box 7057, Amsterdam, The Netherlands
| | - Y M Smulders
- Department of Internal Medicine, Amsterdam University Medical Center, Amsterdam 1007MB, PO Box 7057, Amsterdam, The Netherlands.
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12
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Black R, Barentsz J, Howell D, Bostwick DG, Strum SB. Optimized 18F-FDG PET-CT Method to Improve Accuracy of Diagnosis of Metastatic Cancer. Diagnostics (Basel) 2023; 13:diagnostics13091580. [PMID: 37174971 PMCID: PMC10178450 DOI: 10.3390/diagnostics13091580] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 03/28/2023] [Accepted: 04/12/2023] [Indexed: 05/15/2023] Open
Abstract
The diagnosis of cancer by FDG PET-CT is often inaccurate owing to subjectivity of interpretation. We compared the accuracy of a novel normalized (standardized) method of interpretation with conventional non-normalized SUV. Patients (n = 393) with various malignancies were studied with FDG PET/CT to determine the presence or absence of cancer. Target lesions were assessed by two methods: (1) conventional SUVmax (conSUVmax) and (2) a novel method that combined multiple factors to optimize SUV (optSUVmax), including the patient's normal liver SUVmax, a liver constant (k) derived from a review of the literature, and use of site-specific thresholds for malignancy. The two methods were compared to pathology findings in 154 patients being evaluated for mediastinal and/or hilar lymph node (MHLNs) metastases, 143 evaluated for extra-thoracic lymph node (ETLNs) metastases, and 96 evaluated for liver metastases. OptSUVmax was superior to conSUVmax for all patient groups. For MHLNs, sensitivity was 83.8% vs. 80.7% and specificity 88.7% vs. 9.6%, respectively; for ETLNs, sensitivity was 92.1% vs. 77.8% and specificity 80.1% vs. 27.6%, respectively; and for lesions in the liver parenchyma, sensitivity was 96.1% vs. 82.3% and specificity 88.8% vs. 23.0%, respectively. Optimized SUVmax increased diagnostic accuracy of FDG PET-CT for cancer when compared with conventional SUVmax interpretation.
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Affiliation(s)
| | - Jelle Barentsz
- Department of Radiology, Andros Clinics, Meester E.N. van Kleffensstraat 5, 6842 CV Arnhem, The Netherlands
| | - David Howell
- Department of Radiation Oncology, Ohio Health Cancer Center, 75 Hospital Drive, Athens, OH 45701, USA
| | - David G Bostwick
- Rampart Health, 601 Biotech Drive, North Chesterfield, VA 23235, USA
| | - Stephen B Strum
- Community Practice of Hematology, Oncology and Internal Medicine, Focus on Prostate Cancer and Prostate Diseases, Medford, OR 97504, USA
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13
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Song Y, Meng X, Cao Z, Zhao W, Zhang Y, Guo R, Zhou X, Yang Z, Li N. Harmonization of standard uptake values across different positron emission tomography/computed tomography systems and different reconstruction algorithms: validation in oncology patients. EJNMMI Phys 2023; 10:19. [PMID: 36920590 PMCID: PMC10017904 DOI: 10.1186/s40658-023-00540-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Accepted: 03/01/2023] [Indexed: 03/16/2023] Open
Abstract
BACKGROUND EQ.PET is a software package that overcomes the reconstruction-dependent variation of standard uptake values (SUV). In this study, we validated the use of EQ.PET for harmonizing SUVs between different positron emission tomography/computed tomography (PET/CT) systems and reconstruction algorithms. METHODS In this retrospective study, 49 patients with various cancers were scanned on a Biograph mCT (mCT) or Gemini TF 16 (Gemini) after [18F]FDG injections. Three groups of patient data were collected: Group 1, patients scanned on mCT or Gemini with data reconstructed using two parameters; Group 2, patients scanned twice on different PET scanners (interval between two scans, 68.9 ± 41.4 days); and Group 3, patients scanned twice using mCT with data reconstructed using different algorithms (interval between two scans, 109.5 ± 60.6 days). The SUVs of the lesions and background were measured, and the tumor-to-background ratios (TBRs) were calculated. In addition, the consistency between the two reconstruction algorithms and confounding factors were evaluated. RESULTS In Group 1, the consistency of SUV and TBR between different reconstruction algorithms improved when the EQ.PET filter was applied. In Group 2, by comparing ΔSUV, ΔSUV%, ΔTBR, and ΔTBR% with and without the EQ.PET, the results showed significant differences (P < 0.05). In Group 3, Bland-Altman analysis of ΔSUV with EQ.PET showed an improved consistency relative to that without EQ.PET. CONCLUSIONS EQ.PET is an efficient tool to harmonize SUVs and TBRs across different reconstruction algorithms. Patients could benefit from the harmonized SUV, ΔSUV, and ΔSUV% for therapy responses and follow-up evaluations.
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Affiliation(s)
- Yufei Song
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Key Laboratory for Research and Evaluation of Radiopharmaceuticals (National Medical Products Administration), Department of Nuclear Medicine, Peking University Cancer Hospital and Institute, Beijing, China
| | - Xiangxi Meng
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Key Laboratory for Research and Evaluation of Radiopharmaceuticals (National Medical Products Administration), Department of Nuclear Medicine, Peking University Cancer Hospital and Institute, Beijing, China
| | - Zhen Cao
- Siemens Healthineers Ltd., Shanghai, China
| | - Wei Zhao
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Key Laboratory for Research and Evaluation of Radiopharmaceuticals (National Medical Products Administration), Department of Nuclear Medicine, Peking University Cancer Hospital and Institute, Beijing, China
| | - Yan Zhang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Key Laboratory for Research and Evaluation of Radiopharmaceuticals (National Medical Products Administration), Department of Nuclear Medicine, Peking University Cancer Hospital and Institute, Beijing, China
| | - Rui Guo
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Key Laboratory for Research and Evaluation of Radiopharmaceuticals (National Medical Products Administration), Department of Nuclear Medicine, Peking University Cancer Hospital and Institute, Beijing, China
| | - Xin Zhou
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Key Laboratory for Research and Evaluation of Radiopharmaceuticals (National Medical Products Administration), Department of Nuclear Medicine, Peking University Cancer Hospital and Institute, Beijing, China
| | - Zhi Yang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Key Laboratory for Research and Evaluation of Radiopharmaceuticals (National Medical Products Administration), Department of Nuclear Medicine, Peking University Cancer Hospital and Institute, Beijing, China.
| | - Nan Li
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Key Laboratory for Research and Evaluation of Radiopharmaceuticals (National Medical Products Administration), Department of Nuclear Medicine, Peking University Cancer Hospital and Institute, Beijing, China.
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14
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Li Y, Sijtsema NM, de Vette SPM, Steenbakkers RJHM, Zhang F, Noordzij W, Van den Bosch L, Langendijk JA, van Dijk LV. Validation of the 18F-FDG PET image biomarker model predicting late xerostomia after head and neck cancer radiotherapy. Radiother Oncol 2023; 180:109458. [PMID: 36608769 DOI: 10.1016/j.radonc.2022.109458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 12/23/2022] [Accepted: 12/28/2022] [Indexed: 01/05/2023]
Abstract
BACKGROUND AND PURPOSE Previously, PET image biomarkers (PET-IBMs) - the 90th percentile standardized uptake value (P90-SUV) and the Mean SUV (Mean-SUV) of the contralateral parotid gland (cPG) - were identified as predictors for late-xerostomia following head and neck cancer (HNC) radiotherapy. The aim of the current study was to assess in an independent validation cohort whether these pre-treatment PET-IBM can improve late-xerostomia prediction compared to the prediction with baseline xerostomia and mean cPG dose alone. MATERIALS AND METHODS The prediction endpoint was patient-rated moderate-to-severe xerostomia at 12 months after radiotherapy. The PET-IBMs were extracted from pre-treatment 18 F-FDG PET images. The performance of the model (base model) with baseline xerostomia and mean cPG dose alone and models with additionally P90-SUV or Mean-SUV were tested in the current independent validation cohort. Specifically, model discrimination (area under the curve: AUC) and calibration (calibration plot) were evaluated. RESULTS The current validation cohort consisted of 137 patients of which 40% developed moderate-to-severe xerostomia at 12 months. Both the PET-P90 model (AUC:PET-P90 = 0.71) and the PET-Mean model (AUC: PET-Mean = 0.70) performed well in the current validation cohort. Moreover, their performance were improved compared to the base model (AUC:base model= 0.68). The calibration plots showed a good fit of the prediction to the actual rates for all tested models. CONCLUSION PET-IBMs showed an improved prediction of late-xerostomia when added to the base model in this validation cohort. This contributed to the published hypothesis that PET-IBMs include individualized information and can serve as a pre-treatment risk factor for late-xerostomia.
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Affiliation(s)
- Yan Li
- Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands.
| | - Nanna Maria Sijtsema
- Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | | | | | - Fan Zhang
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Walter Noordzij
- Department of Nuclear Medicine, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Lisa Van den Bosch
- Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Johannes Albertus Langendijk
- Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Lisanne Vania van Dijk
- Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
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15
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Criterios PERCIST, Hopkins y parámetros metabólicos de la PET/TC como factores pronósticos en el cáncer escamoso de cabeza y cuello. Rev Esp Med Nucl Imagen Mol 2023; 42:163-170. [PMID: 36858187 DOI: 10.1016/j.remnie.2023.02.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 12/07/2022] [Accepted: 12/18/2022] [Indexed: 03/03/2023]
Abstract
AIM To assess the clinical utility of PERCIST and Hopkins criteria and changes in [18F]FDG PET/CT quantitative parameters as prognostic factors for progression-free survival (PFS) and cancer-specific survival (CSS) in patients with head and neck squamous cell carcinoma treated by chemoradiotherapy. MATERIAL AND METHODS Forty patients (34 men) diagnosed with head and neck squamous cell carcinoma were retrospectively assessed over an interval of 8 years. PERCIST and Hopkins criteria were used to assess response to treatment. Variations in the metabolic parameters maximum SUV (ΔSUVmax), metabolic tumor volume (ΔMTV) and total lesion glycolysis (ΔTLG) between pre- and post-treatment PET/CT studies were also determined. The Cox regression model, ROC curves and the Kaplan-Meier method were used for the analysis of prognostic factors and survival curves. RESULTS The mean follow-up was 39.4 months, with 24 progressions and 22 deaths. Both PERCIST and Hopkins criteria and the three metabolic parameters were predictive factors in the univariate analysis and only ΔSUVmax was in the multivariate analysis. Survival analysis showed statistically significant differences in PFS and CSS curves for the five parameters considered. CONCLUSION Application of PERCIST and Hopkins criteria as well as ΔSUVmax, ΔMTV and ΔTLG from PET/CT studies proved to be prognostic factors for survival in patients in our setting for treating head and neck cancer. The results may help to personalize treatment.
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16
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Added Value of Abnormal Lymph Nodes Detected with FDG-PET/CT in Suspected Vascular Graft Infection. BIOLOGY 2023; 12:biology12020251. [PMID: 36829528 PMCID: PMC9953627 DOI: 10.3390/biology12020251] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Revised: 02/01/2023] [Accepted: 02/03/2023] [Indexed: 02/08/2023]
Abstract
Vascular graft and endograft infections (VGEI) cause a serious morbidity and mortality burden. 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) imaging is frequently used in the diagnostic workup, but the additional value of abnormal (18F-FDG active and/or enlarged) locoregional lymph nodes is unknown. In this retrospective study, the additional diagnostic value of abnormal locoregional lymph nodes on 18F-FDG PET/CT imaging for VGEI was evaluated, including 54 patients with a culture-proven VGEI (defined according to the Management of Aortic Graft Infection [MAGIC] group classification) and 25 patients without VGEI. 18F-FDG PET/CT was qualitatively and quantitatively assessed for tracer uptake and pattern at the location of the vascular graft, and locoregional lymph node uptake and enlargement (>10 mm). 18F-FDG uptake intensity and pattern independently predicted the presence of VGEI by logistic regression (Χ2: 46.19, p < 0.001), with an OR of 7.38 (95% CI [1.65, 32.92], p = 0.009) and 18.32 (95% CI [3.95, 84.88], p < 0.001), respectively. Single visual assessment of abnormal locoregional lymph nodes predicted the presence of VGEI with a sensitivity of 35%, specificity of 96%, PPV of 95%, and NPV of 41%. The visual assessment of abnormal lymph nodes after qualitative assessment of 18F-FDG uptake intensity and pattern at the vascular graft location did not independently predict the presence of VGEI by logistic regression (Χ2: 3.60, p = 0.058; OR: 8.25, 95% CI [0.74, 63.37], p = 0.096). In conclusion, detection of abnormal locoregional lymph nodes on 18F-FDG PET/CT has a high specificity (96%) and PPV (95%) for VGEI. However, it did not add to currently used 18F-FDG PET/CT interpretation criteria.
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18F-FDG-PET guided vs whole tumour radiotherapy dose escalation in patients with locally advanced non-small cell lung cancer (PET-Boost): Results from a randomised clinical trial. Radiother Oncol 2023; 181:109492. [PMID: 36706958 DOI: 10.1016/j.radonc.2023.109492] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Revised: 12/20/2022] [Accepted: 01/17/2023] [Indexed: 01/26/2023]
Abstract
BACKGROUND AND PURPOSE We aimed to assess if radiation dose escalation to either the whole primary tumour, or to an 18F-FDG-PET defined subvolume within the primary tumour known to be at high risk of local relapse, could improve local control in patients with locally advanced non-small-cell lung cancer. MATERIALS AND METHODS Patients with inoperable, stage II-III NSCLC were randomised (1:1) to receive dose-escalated radiotherapy to the whole primary tumour or a PET-defined subvolume, in 24 fractions. The primary endpoint was freedom from local failure (FFLF), assessed by central review of CT-imaging. A phase II 'pick-the-winner' design (alpha = 0.05; beta = 0.80) was applied to detect a 15 % increase in FFLF at 1-year. CLINICALTRIALS gov:NCT01024829. RESULTS 150 patients were enrolled. 54 patients were randomised to the whole tumour group and 53 to the PET-subvolume group. The trial was closed early due to slow accrual. Median dose/fraction to the boosted volume was 3.30 Gy in the whole tumour group, and 3.50 Gy in the PET-subvolume group. The 1-year FFLF rate was 97 % (95 %CI 91-100) in whole tumour group, and 91 % (95 %CI 82-100) in the PET-subvolume group. Acute grade ≥ 3 adverse events occurred in 23 (43 %) and 20 (38 %) patients, and late grade ≥ 3 in 12 (22 %) and 17 (32 %), respectively. Grade 5 events occurred in 19 (18 %) patients in total, of which before disease progression in 4 (7 %) in the whole tumour group, and 5 (9 %) in the PET-subvolume group. CONCLUSION Both strategies met the primary objective to improve local control with 1-year rates. However, both strategies led to unexpected high rates of grade 5 toxicity. Dose differentiation, improved patient selection and better sparing of central structures are proposed to improve dose-escalation strategies.
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Keijzer K, Niezink AG, de Boer JW, van Doesum JA, Noordzij W, van Meerten T, van Dijk LV. Semi-automated 18F-FDG PET segmentation methods for tumor volume determination in Non-Hodgkin lymphoma patients: a literature review, implementation and multi-threshold evaluation. Comput Struct Biotechnol J 2023; 21:1102-1114. [PMID: 36789266 PMCID: PMC9900370 DOI: 10.1016/j.csbj.2023.01.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 01/18/2023] [Accepted: 01/18/2023] [Indexed: 01/21/2023] Open
Abstract
In the treatment of Non-Hodgkin lymphoma (NHL), multiple therapeutic options are available. Improving outcome predictions are essential to optimize treatment. The metabolic active tumor volume (MATV) has shown to be a prognostic factor in NHL. It is usually retrieved using semi-automated thresholding methods based on standardized uptake values (SUV), calculated from 18F-Fluorodeoxyglucose Positron Emission Tomography (18F-FDG PET) images. However, there is currently no consensus method for NHL. The aim of this study was to review literature on different segmentation methods used, and to evaluate selected methods by using an in house created software tool. A software tool, MUltiple SUV Threshold (MUST)-segmenter was developed where tumor locations are identified by placing seed-points on the PET images, followed by subsequent region growing. Based on a literature review, 9 SUV thresholding methods were selected and MATVs were extracted. The MUST-segmenter was utilized in a cohort of 68 patients with NHL. Differences in MATVs were assessed with paired t-tests, and correlations and distributions figures. High variability and significant differences between the MATVs based on different segmentation methods (p < 0.05) were observed in the NHL patients. Median MATVs ranged from 35 to 211 cc. No consensus for determining MATV is available based on the literature. Using the MUST-segmenter with 9 selected SUV thresholding methods, we demonstrated a large and significant variation in MATVs. Identifying the most optimal segmentation method for patients with NHL is essential to further improve predictions of toxicity, response, and treatment outcomes, which can be facilitated by the MUST-segmenter.
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Key Words
- 18F-FDG PET
- AT, adaptive thresholding methods
- CAR, chimeric antigen receptor
- CT, computed tomography
- DICOM, Digital Imaging and Communications in Medicine
- DLBCL, Diffuse large B-cell lymphoma
- EANM, European Association of Nuclear Medicine
- EARL, EANM Research Ltd.
- FDG, fluorodeoxyglucose
- HL, Hodgkin lymphoma
- IMG, robustness across image reconstruction methods
- IQR, interquartile range
- LBCL, Large B-cell lymphoma
- LDH, lactate dehydrogenase
- MAN, clinician based evaluation using manual segmentations
- MATV, Metabolic active tumor volume
- MIP, Maximum Intensity Projection
- MUST, Multiple SUV Thresholding
- Metabolic tumor volume
- NHL, Non-Hodgkin lymphoma
- Non-Hodgkin lymphoma
- OBS, robustness across observers
- OS, overall survival
- PD-L1, programmed cell death ligand-1
- PET segmentation
- PET, positron emission tomography
- PFS, progression free survival
- PROG, progression vs non-progression
- PTCL, Peripheral T-cell lymphoma
- PTLD, Post-transplant lymphoproliferative disorder
- QS, quality scores
- SOFT, robustness across software
- SUV thresholding
- SUV, standardized uptake value
- Segmentation software
- TCL, T-cell lymphoma
- UMCG, University Medical Center Groningen
- VOI, volume of interest
- cc, cubic centimeter
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Affiliation(s)
- Kylie Keijzer
- Department of Hematology, University Medical Center Groningen, Hanzeplein 1, 9713GZ Groningen, the Netherlands,Department of Radiation Oncology, University Medical Center Groningen, Hanzeplein 1, 9713GZ Groningen, the Netherlands
| | - Anne G.H. Niezink
- Department of Radiation Oncology, University Medical Center Groningen, Hanzeplein 1, 9713GZ Groningen, the Netherlands
| | - Janneke W. de Boer
- Department of Hematology, University Medical Center Groningen, Hanzeplein 1, 9713GZ Groningen, the Netherlands
| | - Jaap A. van Doesum
- Department of Hematology, University Medical Center Groningen, Hanzeplein 1, 9713GZ Groningen, the Netherlands
| | - Walter Noordzij
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, Hanzeplein 1, 9713GZ Groningen, the Netherlands
| | - Tom van Meerten
- Department of Hematology, University Medical Center Groningen, Hanzeplein 1, 9713GZ Groningen, the Netherlands
| | - Lisanne V. van Dijk
- Department of Radiation Oncology, University Medical Center Groningen, Hanzeplein 1, 9713GZ Groningen, the Netherlands,Corresponding author.
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Shankar LK, Huang E, Litiere S, Hoekstra OS, Schwartz L, Collette S, Boellaard R, Bogaerts J, Seymour L, deVries EGE. Meta-Analysis of the Test-Retest Repeatability of [18F]-Fluorodeoxyglucose Standardized Uptake Values: Implications for Assessment of Tumor Response. Clin Cancer Res 2023; 29:143-153. [PMID: 36302172 DOI: 10.1158/1078-0432.ccr-21-3143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Revised: 01/28/2022] [Accepted: 10/24/2022] [Indexed: 02/06/2023]
Abstract
PURPOSE Currently, guidelines for PET with 18F-fluorodeoxyglucose (FDG-PET) interpretation for assessment of therapy response in oncology primarily involve visual evaluation of FDG-PET/CT scans. However, quantitative measurements of the metabolic activity in tumors may be even more useful in evaluating response to treatment. Guidelines based on such measurements, including the European Organization for Research and Treatment of Cancer Criteria and PET Response Criteria in Solid Tumors, have been proposed. However, more rigorous analysis of response criteria based on FDG-PET measurements is needed to adopt regular use in practice. EXPERIMENTAL DESIGN Well-defined boundaries of repeatability and reproducibility of quantitative measurements to discriminate noise from true signal changes are a needed initial step. An extension of the meta-analysis from de Langen and colleagues (2012) of the test-retest repeatability of quantitative FDG-PET measurements, including mean, maximum, and peak standardized uptake values (SUVmax, SUVmean, and SUVpeak, respectively), was performed. Data from 11 studies in the literature were used to estimate the relationship between the variance in test-retest measurements with uptake level and various study-level, patient-level, and lesion-level characteristics. RESULTS Test-retest repeatability of percentage fluctuations for all three types of SUV measurement (max, mean, and peak) improved with higher FDG uptake levels. Repeatability in all three SUV measurements varied for different lesion locations. Worse repeatability in SUVmean was also associated with higher tumor volumes. CONCLUSIONS On the basis of these results, recommendations regarding SUV measurements for assessing minimal detectable changes based on repeatability and reproducibility are proposed. These should be applied to differentiate between response categories for a future set of FDG-PET-based criteria that assess clinically significant changes in tumor response.
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Affiliation(s)
| | - Erich Huang
- National Cancer Institute, Bethesda, Maryland
| | - Saskia Litiere
- European Organisation for Research and Treatment of Cancer Headquarters, Brussels, Belgium
| | - Otto S Hoekstra
- Vrije Universiteit Medical Center, Amsterdam, the Netherlands
| | - Larry Schwartz
- Columbia University Medical Center and New York Presbyterian Hospital, New York, New York
| | | | | | - Jan Bogaerts
- European Organisation for Research and Treatment of Cancer Headquarters, Brussels, Belgium
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20
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Choi JW, Dean EA, Lu H, Thompson Z, Qi J, Krivenko G, Jain MD, Locke FL, Balagurunathan Y. Repeatability of metabolic tumor burden and lesion glycolysis between clinical readers. Front Immunol 2023; 14:994520. [PMID: 36875072 PMCID: PMC9975754 DOI: 10.3389/fimmu.2023.994520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 01/10/2023] [Indexed: 02/17/2023] Open
Abstract
The Metabolic Tumor Volume (MTV) and Tumor Lesion Glycolysis (TLG) has been shown to be independent prognostic predictors for clinical outcome in Diffuse Large B-cell Lymphoma (DLBCL). However, definitions of these measurements have not been standardized, leading to many sources of variation, operator evaluation continues to be one major source. In this study, we propose a reader reproducibility study to evaluate computation of TMV (& TLG) metrics based on differences in lesion delineation. In the first approach, reader manually corrected regional boundaries after automated detection performed across the lesions in a body scan (Reader M using a manual process, or manual). The other reader used a semi-automated method of lesion identification, without any boundary modification (Reader A using a semi- automated process, or auto). Parameters for active lesion were kept the same, derived from standard uptake values (SUVs) over a 41% threshold. We systematically contrasted MTV & TLG differences between expert readers (Reader M & A). We find that MTVs computed by Readers M and A were both concordant between them (concordant correlation coefficient of 0.96) and independently prognostic with a P-value of 0.0001 and 0.0002 respectively for overall survival after treatment. Additionally, we find TLG for these reader approaches showed concordance (CCC of 0.96) and was prognostic for over -all survival (p ≤ 0.0001 for both). In conclusion, the semi-automated approach (Reader A) provides acceptable quantification & prognosis of tumor burden (MTV) and TLG in comparison to expert reader assisted measurement (Reader M) on PET/CT scans.
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Affiliation(s)
- Jung W Choi
- Department of Diagnostic Imaging and Interventional Radiology, H Lee Moffitt Cancer Center, Tampa, FL, United States
| | - Erin A Dean
- Blood and Marrow Transplant and Cellular Immunotherapy, H. Lee. Moffitt Cancer Center, Tampa, FL, United States.,Division of Hematology and Oncology, University of Florida, Gainesville, FL, , United States
| | - Hong Lu
- Cancer Physiology, H. Lee. Moffitt Cancer Center, Tampa, FL, United States.,Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Zachary Thompson
- Biostatistics & Bioinformatics, H. Lee. Moffitt Cancer Center, Tampa, FL, United States
| | - Jin Qi
- Cancer Physiology, H. Lee. Moffitt Cancer Center, Tampa, FL, United States
| | - Gabe Krivenko
- Blood and Marrow Transplant and Cellular Immunotherapy, H. Lee. Moffitt Cancer Center, Tampa, FL, United States
| | - Michael D Jain
- Blood and Marrow Transplant and Cellular Immunotherapy, H. Lee. Moffitt Cancer Center, Tampa, FL, United States
| | - Frederick L Locke
- Blood and Marrow Transplant and Cellular Immunotherapy, H. Lee. Moffitt Cancer Center, Tampa, FL, United States
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21
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Baena García Á, Infante de la Torre J, Barco Carbonero R, Cabrera Rodríguez J, Martínez Esteve A, Serrano Vicente J, Jiménez Granero P, Utrera Costero A, Ignacio Rayo J. Criterios PERCIST, Hopkins y parámetros metabólicos de la PET/TC como factores pronósticos en el cáncer escamoso de cabeza y cuello. Rev Esp Med Nucl Imagen Mol 2023. [DOI: 10.1016/j.remn.2022.12.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
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22
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Long Axial Field-of-View PET for Ultra-Low-Dose Imaging of Non-Hodgkin Lymphoma during Pregnancy. Diagnostics (Basel) 2022; 13:diagnostics13010028. [PMID: 36611320 PMCID: PMC9818305 DOI: 10.3390/diagnostics13010028] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 12/13/2022] [Accepted: 12/19/2022] [Indexed: 12/24/2022] Open
Abstract
Generally, positron emission tomography imaging is not often performed in the case of pregnant patients. The careful weighing of the risks of radiation exposure to the fetus and benefits for cancer staging and the swift onset of treatment for the mother complicates decision making in clinical practice. In oncology, the most commonly used PET radiotracer is 2-deoxy-2-[fluorine-18] fluoro-D-glucose (18F-FDG), a glucose analog which has established roles in the daily routines for, among other applications, initial diagnosis, staging, (radiation) therapy planning, and response monitoring. The introduction of long axial Field-of-View (LAFOV) PET systems allows for PET imaging with a reduced level of injected 18F-FDG activity while maintaining the image quality. Here, we discuss the first reported case of a pregnant patient diagnosed with follicular lymphoma using LAFOV PET imaging for the staging and therapy selection. The acquired PET images show diagnostic quality images with clearly distinguishable areas of lymphadenopathy, even with only 34 MBq of injected 18F-FDG activity, leading to a considerable decrease in the level of radiation exposure to the fetus.
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23
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Prognostic value of PERCIST and PET/CT metabolic parameters after neoadjuvant treatment in patients with esophageal cancer. Rev Esp Med Nucl Imagen Mol 2022; 41:360-367. [DOI: 10.1016/j.remnie.2021.09.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Revised: 09/21/2021] [Accepted: 09/21/2021] [Indexed: 11/08/2022]
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van Sluis J, van Snick JH, Brouwers AH, Noordzij W, Dierckx RAJO, Borra RJH, Lammertsma AA, Glaudemans AWJM, Slart RHJA, Yaqub M, Tsoumpas C, Boellaard R. Shortened duration whole body 18F-FDG PET Patlak imaging on the Biograph Vision Quadra PET/CT using a population-averaged input function. EJNMMI Phys 2022; 9:74. [PMID: 36308568 PMCID: PMC9618000 DOI: 10.1186/s40658-022-00504-9] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 10/21/2022] [Indexed: 11/13/2022] Open
Abstract
Background Excellent performance characteristics of the Vision Quadra PET/CT, e.g. a substantial increase in sensitivity, allow for precise measurements of image-derived input functions (IDIF) and tissue time activity curves. Previously we have proposed a method for a reduced 30 min (as opposed to 60 min) whole body 18F-FDG Patlak PET imaging procedure using a previously published population-averaged input function (PIF) scaled to IDIF values at 30–60 min post-injection (p.i.). The aim of the present study was to apply this method using the Vision Quadra PET/CT, including the use of a PIF to allow for shortened scan durations. Methods Twelve patients with suspected lung malignancy were included and received a weight-based injection of 18F-FDG. Patients underwent a 65-min dynamic PET acquisition which were reconstructed using European Association of Nuclear Medicine Research Ltd. (EARL) standards 2 reconstruction settings. A volume of interest (VOI) was placed in the ascending aorta (AA) to obtain the IDIF. An external PIF was scaled to IDIF values at 30–60, 40–60, and 50–60 min p.i., respectively, and parametric 18F-FDG influx rate constant (Ki) images were generated using a t* of 30, 40 or 50 min, respectively. Herein, tumour lesions as well as healthy tissues, i.e. liver, muscle tissue, spleen and grey matter, were segmented. Results Good agreement between the IDIF and corresponding PIF scaled to 30–60 min p.i. and 40–60 min p.i. was obtained with 7.38% deviation in Ki. Bland–Altman plots showed excellent agreement in Ki obtained using the PIF scaled to the IDIF at 30–60 min p.i. and at 40–60 min p.i. as all data points were within the limits of agreement (LOA) (− 0.004–0.002, bias: − 0.001); for the 50–60 min p.i. Ki, all except one data point fell in between the LOA (− 0.021–0.012, bias: − 0.005). Conclusions Parametric whole body 18F-FDG Patlak Ki images can be generated non-invasively on a Vision Quadra PET/CT system. In addition, using a scaled PIF allows for a substantial (factor 2 to 3) reduction in scan time without substantial loss of accuracy (7.38% bias) and precision (image quality and noise interference). Supplementary Information The online version contains supplementary material available at 10.1186/s40658-022-00504-9.
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25
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Badawe EM, Abdel Gawad H, El-Nagdy MS, Khalil MM. Variations induced by body weight and background lesion normalization in standardized uptake value estimated by F18-FDG PET/CT. Eur J Hybrid Imaging 2022; 6:22. [PMID: 36224438 PMCID: PMC9556683 DOI: 10.1186/s41824-022-00142-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Accepted: 07/12/2022] [Indexed: 11/10/2022] Open
Abstract
AIM This work aims to study the impact of different SUV variants in terms of mean and maximum measures as well as various normalization methods with respect to body weight, body mass index, body surface area, and lean body mass in patients with lymphoma. METHODS Sixty-nine patients (34 male-35 female) were retrospectively selected. All patients had undergone F18-FDG PET/CT using the standard imaging protocol. In the first part of this study, SUVmean and SUVmax of patients' lesions and three background sites including liver, aorta, and muscle were determined. Then, the normalization of lesion SUV to body weight and body background sites was performed. The ratio of lesion SUVmax to body background sites (muscle, aorta, and liver) SUVmax was determined in addition to the ratio of lesion SUVmean to body background sites SUVmean. The second part of the study included the calculations of the body mass index (BMI), body surface area (BSA), and lean body mass (LBM). The normalization of lesion, liver, aorta, and muscle SUV to BMI, BSA, and LBM was calculated and compared to each other. RESULTS After performing the appropriate statistical calculations, the results showed that there is a significant difference in SUV measurements between the three background sites. Lesions normalized to the liver were significantly lower than those normalized to aorta and muscle and the results also showed a higher magnitude of lesions normalized to muscle in comparison to the aorta. The SUVmax and SUVmean normalized to different body weight indices showed the lowest variation with BSA and BMI while being increasingly higher with lean body mass using the two methods James and Janmahasatian, respectively, and then highest with body weight. CONCLUSION The SUVmax and SUVmean showed lower variance in comparison to other background regions. Less variation was also remarkable in SUVmean normalized to BSA and Janma lean mass and also when SUVmax is normalized to James lean body mass. The SUVmax normalized to lean (i.e., James) as well as SUVmean normalized to lean (i.e., Janma) and BSA showed a significant independence with body weight.
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Affiliation(s)
- Eman M. Badawe
- grid.412093.d0000 0000 9853 2750Department of Physics, Faculty of Science, Helwan University, Cairo, Egypt
| | - Hesham Abdel Gawad
- grid.7776.10000 0004 0639 9286Faculty of Medicine, Kasr Al-Aini Center for Nuclear Medicine and Oncology (NEMROK), Cairo University Hospitals, Cairo University, Giza, Egypt
| | - Mohamed S. El-Nagdy
- grid.412093.d0000 0000 9853 2750Department of Physics, Faculty of Science, Helwan University, Cairo, Egypt
| | - Magdy M. Khalil
- grid.412093.d0000 0000 9853 2750Department of Physics, Faculty of Science, Helwan University, Cairo, Egypt ,grid.507995.70000 0004 6073 8904School of Biotechnology, Badr University in Cairo (BUC), Badr City, Cairo Egypt
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26
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van Sluis J, van Snick JH, Brouwers AH, Noordzij W, Dierckx RAJO, Borra RJH, Slart RHJA, Lammertsma AA, Glaudemans AWJM, Boellaard R, Tsoumpas C. EARL compliance and imaging optimisation on the Biograph Vision Quadra PET/CT using phantom and clinical data. Eur J Nucl Med Mol Imaging 2022; 49:4652-4660. [DOI: 10.1007/s00259-022-05919-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 07/16/2022] [Indexed: 11/04/2022]
Abstract
Abstract
Purpose
Current European Association of Nuclear Medicine (EANM) Research Ltd. (EARL) guidelines for the standardisation of PET imaging developed for conventional systems have not yet been adjusted for long axial field-of-view (LAFOV) systems. In order to use the LAFOV Siemens Biograph Vision Quadra PET/CT (Siemens Healthineers, Knoxville, TN, USA) in multicentre research and harmonised clinical use, compliance to EARL specifications for 18F-FDG tumour imaging was explored in the current study. Additional tests at various locations throughout the LAFOV and the use of shorter scan durations were included. Furthermore, clinical data were collected to further explore and validate the effects of reducing scan duration on semi-quantitative PET image biomarker accuracy and precision when using EARL-compliant reconstruction settings.
Methods
EARL compliance phantom measurements were performed using the NEMA image quality phantom both in the centre and at various locations throughout the LAFOV. PET data (maximum ring difference (MRD) = 85) were reconstructed using various reconstruction parameters and reprocessed to obtain images at shorter scan durations. Maximum, mean and peak activity concentration recovery coefficients (RC) were obtained for each sphere and compared to EARL standards specifications.
Additionally, PET data (MRD = 85) of 10 oncological patients were acquired and reconstructed using various reconstruction settings and reprocessed from 10 min listmode acquisition into shorter scan durations. Per dataset, SUVs were derived from tumour lesions and healthy tissues. ANOVA repeated measures were performed to explore differences in lesion SUVmax and SUVpeak. Wilcoxon signed-rank tests were performed to evaluate differences in background SUVpeak and SUVmean between scan durations. The coefficient of variation (COV) was calculated to characterise noise.
Results
Phantom measurements showed EARL compliance for all positions throughout the LAFOV for all scan durations. Regarding patient data, EARL-compliant images showed no clinically meaningful significant differences in lesion SUVmax and SUVpeak or background SUVmean and SUVpeak between scan durations. Here, COV only varied slightly.
Conclusion
Images obtained using the Vision Quadra PET/CT comply with EARL specifications. Scan duration and/or activity administration can be reduced up to a factor tenfold without the interference of increased noise.
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27
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Esen I, Jiemy WF, van Sleen Y, Bijzet J, de Jong DM, Nienhuis PH, Slart RHJA, Heeringa P, Boots AMH, Brouwer E. Plasma Pyruvate Kinase M2 as a marker of vascular inflammation in giant cell arteritis. Rheumatology (Oxford) 2022; 61:3060-3070. [PMID: 34730794 PMCID: PMC9258600 DOI: 10.1093/rheumatology/keab814] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Revised: 10/29/2021] [Indexed: 11/28/2022] Open
Abstract
OBJECTIVES GCA is a large vessel vasculitis in which metabolically active immune cells play an important role. GCA diagnosis is based on CRP/ESR and temporal artery biopsies (TABs), in combination with 18F-fluorodeoxyglucose ([18F]FDG)-PET/CT relying on enhanced glucose uptake by glycolytic macrophages. Here, we studied circulating Pyruvate Kinase M2 (PKM2), a glycolytic enzyme, as a possible systemic marker of vessel wall inflammation in GCA. METHODS Immunohistochemical detection of PKM2 was performed on inflamed (n = 12) and non-inflamed (n = 4) TABs from GCA patients and non-GCA (n = 9) patients. Dimeric PKM2 levels were assessed in plasma of GCA patients (n = 44), age-matched healthy controls (n = 41), metastatic melanoma patients (n = 7) and infection controls (n = 11). CRP, ESR and macrophage markers calprotectin and YKL-40 were correlated with plasma PKM2 levels. To detect the cellular source of plasma PKM2 in tissue, double IF staining was performed on inflamed GCA TABs. [18F]FDG-PET scans of 23 GCA patients were analysed and maximum standard uptake values and target to background ratios were calculated. RESULTS PKM2 is abundantly expressed in TABs of GCA patients. Dimeric PKM2 plasma levels were elevated in GCA and correlated with CRP, ESR, calprotectin and YKL-40 levels. Elevated plasma PKM2 levels were downmodulated by glucocorticoid treatment. PKM2 was detected in both macrophages and T cells at the site of vascular inflammation. Circulating PKM2 levels correlated with average target to background ratios PET scores. CONCLUSION Elevated plasma PKM2 levels reflect active vessel inflammation in GCA and may assist in disease diagnosis and in disease monitoring.
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Affiliation(s)
- Idil Esen
- Department of Rheumatology and Clinical Immunology
| | | | | | - Johan Bijzet
- Department of Rheumatology and Clinical Immunology
| | | | - Pieter H Nienhuis
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen
| | - Riemer H J A Slart
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen
- Department of Biomedical Photonic Imaging, Faculty of Science and Technology, University of Twente, Enschede
| | - Peter Heeringa
- Department of Pathology and Medical Biology, University of Groningen, Groningen, The Netherlands
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Hicks RJ. The value of the Standardized Uptake Value (SUV) and Metabolic Tumor Volume (MTV) in lung cancer. Semin Nucl Med 2022; 52:734-744. [PMID: 35624032 DOI: 10.1053/j.semnuclmed.2022.04.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 04/21/2022] [Indexed: 11/11/2022]
Abstract
The diagnosis, staging and therapeutic monitoring of lung cancer were amongst the first applications for which the utility of FDG PET was documented and FDG PET/CT is now a routine diagnostic tool for clinical decision-making. As well as having high sensitivity for detection of disease sites, which provides critical information about stage, the intensity of uptake provides deeper biological characterization, while the burden of disease also has potential clinical significance. These disease characteristics can easily be quantified on delayed whole-body imaging as the maximum standardized uptake value (SUVmax) and metabolic tumor volume (MTV), respectively. There have been significant efforts to harmonize the measurement of these features, particularly within the context of clinical trials. Nevertheless, however calculated, in general, a high SUVmax and large MTV have been shown to have an adverse prognostic significance. Nevertheless, the use of these parameters in the interpretation and reporting of clinical scans remains inconsistent and somewhat controversial. This review details the current status of semi-quantitative FDG PET/CT in the evaluation of lung cancer.
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Affiliation(s)
- Rodney J Hicks
- Department of Medicine, St Vincent's Medical School, University of Melbourne, Melbourne Academic Centre for Health, University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Central Clinical School, Alfred Hospital, Monash University, Melbourne VIC, Australia.
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Prenosil GA, Hentschel M, Weitzel T, Sari H, Shi K, Afshar-Oromieh A, Rominger A. EARL compliance measurements on the biograph vision Quadra PET/CT system with a long axial field of view. EJNMMI Phys 2022; 9:26. [PMID: 35394263 PMCID: PMC8994003 DOI: 10.1186/s40658-022-00455-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 03/28/2022] [Indexed: 02/06/2023] Open
Abstract
Background Our aim was to determine sets of reconstruction parameters for the Biograph Vision Quadra (Siemens Healthineers) PET/CT system that result in quantitative images compliant with the European Association of Nuclear Medicine Research Ltd. (EARL) criteria. Using the Biograph Vision 600 (Siemens Healthineers) PET/CT technology but extending the axial field of view to 106 cm, gives the Vision Quadra currently an around fivefold higher sensitivity over the Vision 600 with otherwise comparable spatial resolution. Therefore, we also investigated how the number of incident positron decays—i.e., exposure—affects EARL compliance. This will allow estimating a minimal acquisition time or a minimal applied dose in clinical scans while retaining data comparability. Methods We measured activity recovery curves on a NEMA IEC body phantom filled with an aqueous 18F solution and a sphere to background ratio of 10–1 according to the latest EARL guidelines. Reconstructing 3570 image sets with varying OSEM PSF iterations, post-reconstruction Gaussian filter full width at half maximum (FWHM), and varying exposure from 59 kDecays/ml (= 3 s frame duration) to 59.2 MDecays/ml (= 1 h), allowed us to determine sets of parameters to achieve compliance with the current EARL 1 and EARL 2 standards. Recovery coefficients (RCs) were calculated for the metrics RCmax, RCmean, and RCpeak, and the respective recovery curves were analyzed for monotonicity. The background’s coefficient of variation (COV) was also calculated. Results Using 6 iterations, 5 subsets and 7.8 mm Gauss filtering resulted in optimal EARL1 compliance and recovery curve monotonicity in all analyzed frames, except in the 3 s frames. Most robust EARL2 compliance and monotonicity were achieved with 2 iterations, 5 subsets, and 3.6 mm Gauss FWHM in frames with durations between 30 s and 10 min. RCpeak only impeded EARL2 compliance in the 10 s and 3 s frames. Conclusions While EARL1 compliance was robust over most exposure ranges, EARL2 compliance required exposures between 1.2 MDecays/ml to 11.5 MDecays/ml. The Biograph Vision Quadra’s high sensitivity makes frames as short as 10 s feasible for comparable quantitative images. Lowering EARL2 RCmax limits closer to unity would possibly even permit shorter frames.
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Affiliation(s)
- George A Prenosil
- Department of Nuclear Medicine, Inselspital Bern, Bern University Hospital, University of Bern, 3010, Bern, Switzerland.
| | - Michael Hentschel
- Department of Nuclear Medicine, Inselspital Bern, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
| | - Thilo Weitzel
- Department of Nuclear Medicine, Inselspital Bern, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
| | - Hasan Sari
- Department of Nuclear Medicine, Inselspital Bern, Bern University Hospital, University of Bern, 3010, Bern, Switzerland.,Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
| | - Kuangyu Shi
- Department of Nuclear Medicine, Inselspital Bern, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
| | - Ali Afshar-Oromieh
- Department of Nuclear Medicine, Inselspital Bern, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
| | - Axel Rominger
- Department of Nuclear Medicine, Inselspital Bern, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
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30
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Fournier L, de Geus-Oei LF, Regge D, Oprea-Lager DE, D’Anastasi M, Bidaut L, Bäuerle T, Lopci E, Cappello G, Lecouvet F, Mayerhoefer M, Kunz WG, Verhoeff JJC, Caruso D, Smits M, Hoffmann RT, Gourtsoyianni S, Beets-Tan R, Neri E, deSouza NM, Deroose CM, Caramella C. Twenty Years On: RECIST as a Biomarker of Response in Solid Tumours an EORTC Imaging Group - ESOI Joint Paper. Front Oncol 2022; 11:800547. [PMID: 35083155 PMCID: PMC8784734 DOI: 10.3389/fonc.2021.800547] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2021] [Accepted: 11/30/2021] [Indexed: 12/15/2022] Open
Abstract
Response evaluation criteria in solid tumours (RECIST) v1.1 are currently the reference standard for evaluating efficacy of therapies in patients with solid tumours who are included in clinical trials, and they are widely used and accepted by regulatory agencies. This expert statement discusses the principles underlying RECIST, as well as their reproducibility and limitations. While the RECIST framework may not be perfect, the scientific bases for the anticancer drugs that have been approved using a RECIST-based surrogate endpoint remain valid. Importantly, changes in measurement have to meet thresholds defined by RECIST for response classification within thus partly circumventing the problems of measurement variability. The RECIST framework also applies to clinical patients in individual settings even though the relationship between tumour size changes and outcome from cohort studies is not necessarily translatable to individual cases. As reproducibility of RECIST measurements is impacted by reader experience, choice of target lesions and detection/interpretation of new lesions, it can result in patients changing response categories when measurements are near threshold values or if new lesions are missed or incorrectly interpreted. There are several situations where RECIST will fail to evaluate treatment-induced changes correctly; knowledge and understanding of these is crucial for correct interpretation. Also, some patterns of response/progression cannot be correctly documented by RECIST, particularly in relation to organ-site (e.g. bone without associated soft-tissue lesion) and treatment type (e.g. focal therapies). These require specialist reader experience and communication with oncologists to determine the actual impact of the therapy and best evaluation strategy. In such situations, alternative imaging markers for tumour response may be used but the sources of variability of individual imaging techniques need to be known and accounted for. Communication between imaging experts and oncologists regarding the level of confidence in a biomarker is essential for the correct interpretation of a biomarker and its application to clinical decision-making. Though measurement automation is desirable and potentially reduces the variability of results, associated technical difficulties must be overcome, and human adjudications may be required.
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Affiliation(s)
- Laure Fournier
- Imaging Group, European Organisation of Research and Treatment in Cancer (EORTC), Brussels, Belgium
- European Society of Oncologic Imaging (ESOI), European Society of Radiology, Vienna, Austria
- Université de Paris, Assistance Publique–Hôpitaux de Paris (AP-HP), Hopital europeen Georges Pompidou, Department of Radiology, Paris Cardiovascular Research Center (PARCC) Unité Mixte de Recherche (UMRS) 970, Institut national de la santé et de la recherche médicale (INSERM), Paris, France
| | - Lioe-Fee de Geus-Oei
- Imaging Group, European Organisation of Research and Treatment in Cancer (EORTC), Brussels, Belgium
- Department of Radiology, Leiden University Medical Center, Leiden, Netherlands
- Biomedical Photonic Imaging Group, University of Twente, Enschede, Netherlands
| | - Daniele Regge
- European Society of Oncologic Imaging (ESOI), European Society of Radiology, Vienna, Austria
- Department of Surgical Sciences, University of Turin, Turin, Italy
- Radiology Unit, Candiolo Cancer Institute, Fondazione del Piemonte per l’Oncologia-Istituto Di Ricovero e Cura a Carattere Scientifico (FPO-IRCCS), Turin, Italy
| | - Daniela-Elena Oprea-Lager
- Imaging Group, European Organisation of Research and Treatment in Cancer (EORTC), Brussels, Belgium
- Department of Radiology & Nuclear Medicine, Cancer Centre Amsterdam, Amsterdam University Medical Centers [Vrije Universiteit (VU) University], Amsterdam, Netherlands
| | - Melvin D’Anastasi
- European Society of Oncologic Imaging (ESOI), European Society of Radiology, Vienna, Austria
- Medical Imaging Department, Mater Dei Hospital, University of Malta, Msida, Malta
| | - Luc Bidaut
- Imaging Group, European Organisation of Research and Treatment in Cancer (EORTC), Brussels, Belgium
- College of Science, University of Lincoln, Lincoln, United Kingdom
| | - Tobias Bäuerle
- European Society of Oncologic Imaging (ESOI), European Society of Radiology, Vienna, Austria
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Egesta Lopci
- Imaging Group, European Organisation of Research and Treatment in Cancer (EORTC), Brussels, Belgium
- Nuclear Medicine Unit, Istituto Di Ricovero e Cura a Carattere Scientifico (IRCCS) – Humanitas Research Hospital, Milan, Italy
| | - Giovanni Cappello
- Department of Surgical Sciences, University of Turin, Turin, Italy
- Radiology Unit, Candiolo Cancer Institute, Fondazione del Piemonte per l’Oncologia-Istituto Di Ricovero e Cura a Carattere Scientifico (FPO-IRCCS), Turin, Italy
| | - Frederic Lecouvet
- Imaging Group, European Organisation of Research and Treatment in Cancer (EORTC), Brussels, Belgium
- Department of Radiology, Institut de Recherche Expérimentale et Clinique (IREC), Cliniques Universitaires Saint Luc, Université Catholique de Louvain (UCLouvain), Brussels, Belgium
| | - Marius Mayerhoefer
- European Society of Oncologic Imaging (ESOI), European Society of Radiology, Vienna, Austria
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Wolfgang G. Kunz
- Imaging Group, European Organisation of Research and Treatment in Cancer (EORTC), Brussels, Belgium
- European Society of Oncologic Imaging (ESOI), European Society of Radiology, Vienna, Austria
- Department of Radiology, University Hospital, Ludwig Maximilian University (LMU) Munich, Munich, Germany
| | - Joost J. C. Verhoeff
- Imaging Group, European Organisation of Research and Treatment in Cancer (EORTC), Brussels, Belgium
- Department of Radiotherapy, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Damiano Caruso
- European Society of Oncologic Imaging (ESOI), European Society of Radiology, Vienna, Austria
- Department of Medical-Surgical Sciences and Translational Medicine, Sapienza University of Rome, Rome, Italy
| | - Marion Smits
- Imaging Group, European Organisation of Research and Treatment in Cancer (EORTC), Brussels, Belgium
- Department of Radiology & Nuclear Medicine, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, Netherlands
- Brain Tumour Centre, Erasmus Medical Centre (MC) Cancer Institute, Rotterdam, Netherlands
| | - Ralf-Thorsten Hoffmann
- European Society of Oncologic Imaging (ESOI), European Society of Radiology, Vienna, Austria
- Institute and Policlinic for Diagnostic and Interventional Radiology, University Hospital, Carl-Gustav-Carus Technical University Dresden, Dresden, Germany
| | - Sofia Gourtsoyianni
- European Society of Oncologic Imaging (ESOI), European Society of Radiology, Vienna, Austria
- Department of Radiology, School of Medicine, National and Kapodistrian University of Athens, Areteion Hospital, Athens, Greece
| | - Regina Beets-Tan
- European Society of Oncologic Imaging (ESOI), European Society of Radiology, Vienna, Austria
- Department of Radiology, The Netherlands Cancer Institute, Amsterdam, Netherlands
- School For Oncology and Developmental Biology (GROW) School for Oncology and Developmental Biology, Maastricht University, Maastricht, Netherlands
| | - Emanuele Neri
- European Society of Oncologic Imaging (ESOI), European Society of Radiology, Vienna, Austria
- Diagnostic and Interventional Radiology, Department of Translational Research and of New Surgical and Medical Technologies, University of Pisa, Pisa, Italy
| | - Nandita M. deSouza
- Imaging Group, European Organisation of Research and Treatment in Cancer (EORTC), Brussels, Belgium
- Division of Radiotherapy and Imaging, The Institute of Cancer Research and Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom
- European Imaging Biomarkers Alliance (EIBALL), European Society of Radiology, Vienna, Austria
- Quantitative Imaging Biomarkers Alliance, Radiological Society of North America, Oak Brook, IL, United States
| | - Christophe M. Deroose
- Imaging Group, European Organisation of Research and Treatment in Cancer (EORTC), Brussels, Belgium
- Nuclear Medicine, University Hospitals Leuven, Leuven, Belgium
- Nuclear Medicine & Molecular Imaging, Department of Imaging and Pathology, Katholieke Universiteit (KU) Leuven, Leuven, Belgium
| | - Caroline Caramella
- Imaging Group, European Organisation of Research and Treatment in Cancer (EORTC), Brussels, Belgium
- Radiology Department, Hôpital Marie Lannelongue, Groupe Hospitalier Paris Saint Joseph Centre International des Cancers Thoraciques, Université Paris-Saclay, Le Plessis-Robinson, France
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Kennedy J, Chicheportiche A, Keidar Z. Quantitative SPECT/CT for dosimetry of peptide receptor radionuclide therapy. Semin Nucl Med 2021; 52:229-242. [PMID: 34911637 DOI: 10.1053/j.semnuclmed.2021.11.004] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Neuroendocrine tumors (NETs) are uncommon malignancies of increasing incidence and prevalence. As these slow growing tumors usually overexpress somatostatin receptors (SSTRs), the use of 68Ga-DOTA-peptides (gallium-68 chelated with dodecane tetra-acetic acid to somatostatin), which bind to the SSTRs, allows for PET based imaging and selection of patients for peptide receptor radionuclide therapy (PRRT). PRRT with radiolabeled somatostatin analogues such as 177Lu-DOTATATE (lutetium-177-[DOTA,Tyr3]-octreotate), is mainly used for the treatment of metastatic or inoperable NETs. However, PRRT is generally administered at a fixed injected activity in order not to exceed dose limits in critical organs, which is suboptimal given the variability in radiopharmaceutical uptake among patients. Advances in SPECT (single photon emission computed tomography) imaging enable the absolute quantitative measure of the true radiopharmaceutical distribution providing for PRRT dosimetry in each patient. Personalized PRRT based on patient-specific dosimetry could improve therapeutic efficacy by optimizing effective tumor absorbed dose while limiting treatment related radiotoxicity.
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Affiliation(s)
- John Kennedy
- Department of Nuclear Medicine, Rambam Health Care Campus, Haifa, Israel; B. Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel.
| | - Alexandre Chicheportiche
- Department of Nuclear Medicine and Biophysics, Hadassah Medical Organization and Faculty of Medicine, Hebrew University of Jerusalem, Israel
| | - Zohar Keidar
- Department of Nuclear Medicine, Rambam Health Care Campus, Haifa, Israel; B. Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel
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de Jesus FM, Yin Y, Mantzorou-Kyriaki E, Kahle XU, de Haas RJ, Yakar D, Glaudemans AWJM, Noordzij W, Kwee TC, Nijland M. Machine learning in the differentiation of follicular lymphoma from diffuse large B-cell lymphoma with radiomic [ 18F]FDG PET/CT features. Eur J Nucl Med Mol Imaging 2021; 49:1535-1543. [PMID: 34850248 DOI: 10.1007/s00259-021-05626-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2021] [Accepted: 11/16/2021] [Indexed: 12/17/2022]
Abstract
BACKGROUND One of the challenges in the management of patients with follicular lymphoma (FL) is the identification of individuals with histological transformation, most commonly into diffuse large B-cell lymphoma (DLBCL). [18F]FDG-PET/CT is used for staging of patients with lymphoma, but visual interpretation cannot reliably discern FL from DLBCL. This study evaluated whether radiomic features extracted from clinical baseline [18F]FDG PET/CT and analyzed by machine learning algorithms may help discriminate FL from DLBCL. MATERIALS AND METHODS Patients were selected based on confirmed histopathological diagnosis of primary FL (n=44) or DLBCL (n=76) and available [18F]FDG PET/CT with EARL reconstruction parameters within 6 months of diagnosis. Radiomic features were extracted from the volume of interest on co-registered [18F]FDG PET and CT images. Analysis of selected radiomic features was performed with machine learning classifiers based on logistic regression and tree-based ensemble classifiers (AdaBoosting, Gradient Boosting, and XG Boosting). The performance of radiomic features was compared with a SUVmax-based logistic regression model. RESULTS From the segmented lesions, 121 FL and 227 DLBCL lesions were included for radiomic feature extraction. In total, 79 radiomic features were extracted from the SUVmap, 51 from CT, and 6 shape features. Machine learning classifier Gradient Boosting achieved the best discrimination performance using 136 radiomic features (AUC of 0.86 and accuracy of 80%). SUVmax-based logistic regression model achieved an AUC of 0.79 and an accuracy of 70%. Gradient Boosting classifier had a significantly greater AUC and accuracy compared to the SUVmax-based logistic regression (p≤0.01). CONCLUSION Machine learning analysis of radiomic features may be of diagnostic value for discriminating FL from DLBCL tumor lesions, beyond that of the SUVmax alone.
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Affiliation(s)
| | - Y Yin
- Universitair Medisch Centrum Groningen, Groningen, Netherlands
| | | | - X U Kahle
- Universitair Medisch Centrum Groningen, Groningen, Netherlands
| | - R J de Haas
- Universitair Medisch Centrum Groningen, Groningen, Netherlands
| | - D Yakar
- Universitair Medisch Centrum Groningen, Groningen, Netherlands
| | | | - W Noordzij
- Universitair Medisch Centrum Groningen, Groningen, Netherlands
| | - T C Kwee
- Universitair Medisch Centrum Groningen, Groningen, Netherlands
| | - M Nijland
- Universitair Medisch Centrum Groningen, Groningen, Netherlands
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33
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Valor pronóstico de los criterios PERCIST y los parámetros metabólicos de la PET/TC en pacientes con cáncer de esófago tras tratamiento neoadyuvante. Rev Esp Med Nucl Imagen Mol 2021. [DOI: 10.1016/j.remn.2021.09.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/09/2022]
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Martínez A, Infante JR, Quirós J, Rayo JI, Serrano J, Moreno M, Jiménez P, Cobo A, Baena A. Baseline 18F-FDG PET/CT quantitative parameters as prognostic factors in esophageal squamous cell cancer. Rev Esp Med Nucl Imagen Mol 2021; 41:164-170. [PMID: 34452867 DOI: 10.1016/j.remnie.2021.07.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Accepted: 03/18/2021] [Indexed: 11/19/2022]
Abstract
AIM To determine the utility of [18F]FDG PET/CT quantitative parameters as prognostic factors for the response to neoadjuvant treatment, progression-free survival (PFS) and cancer-specific survival (CSS) in patients with esophageal squamous cell carcinoma (SCC). MATERIAL AND METHODS Thirty patients (29 men) diagnosed with SCC were retrospectively evaluated over a 6-year interval. Metabolic parameters were determined: maximum SUV (SUVmax), mean SUV (SUVmed), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) from baseline PET/CT study. After treatment with chemotherapy and/or radiotherapy, response to treatment and patient survival were assessed. The comparison of parameters between groups of responders and non-responders was carried out using a Mann-Whitney U test ROC curves and the Kaplan-Meier method were used for analysis of prognostic factors and survival curves. RESULTS The average follow-up was 22.4 months, with 22 recurrence-progressions and 25 deaths. Significant differences were demonstrated between responders and non-responders with respect to tumor size, MTV and TLG. Survival analysis found significant differences for SCE and CSS depending on these three parameters. CONCLUSION Metabolic parameters MTV and TLG, and tumor size were prognostic factors for neoadjuvant treatment response, PFS, and CSS in patients diagnosed with SCC. Neither SUVmax nor SUVmed were predictive for any of the evaluation criteria. Results could help to personalize patient treatment.
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Affiliation(s)
- A Martínez
- Servicio de Medicina Nuclear, Hospital Universitario de Badajoz, Badajoz, Spain.
| | - J R Infante
- Servicio de Medicina Nuclear, Hospital Universitario de Badajoz, Badajoz, Spain
| | - J Quirós
- Servicio de Oncología Radioterápica, Hospital Universitario de Badajoz, Badajoz, Spain
| | - J I Rayo
- Servicio de Medicina Nuclear, Hospital Universitario de Badajoz, Badajoz, Spain
| | - J Serrano
- Servicio de Medicina Nuclear, Hospital Universitario de Badajoz, Badajoz, Spain
| | - M Moreno
- Servicio de Medicina Nuclear, Hospital Universitario de Badajoz, Badajoz, Spain
| | - P Jiménez
- Servicio de Medicina Nuclear, Hospital Universitario de Badajoz, Badajoz, Spain
| | - A Cobo
- Servicio de Medicina Nuclear, Hospital Universitario de Badajoz, Badajoz, Spain
| | - A Baena
- Servicio de Medicina Nuclear, Hospital Universitario de Badajoz, Badajoz, Spain
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Oliveira C, Amstutz F, Vuong D, Bogowicz M, Hüllner M, Foerster R, Basler L, Schröder C, Eboulet EI, Pless M, Thierstein S, Peters S, Hillinger S, Tanadini-Lang S, Guckenberger M. Preselection of robust radiomic features does not improve outcome modelling in non-small cell lung cancer based on clinical routine FDG-PET imaging. EJNMMI Res 2021; 11:79. [PMID: 34417899 PMCID: PMC8380219 DOI: 10.1186/s13550-021-00809-3] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Accepted: 07/08/2021] [Indexed: 12/25/2022] Open
Abstract
Background Radiomics is a promising tool for identifying imaging-based biomarkers. Radiomics-based models are often trained on single-institution datasets; however, multi-centre imaging datasets are preferred for external generalizability owing to the influence of inter-institutional scanning differences and acquisition settings. The study aim was to determine the value of preselection of robust radiomic features in routine clinical positron emission tomography (PET) images to predict clinical outcomes in locally advanced non-small cell lung cancer (NSCLC). Methods A total of 1404 primary tumour radiomic features were extracted from pre-treatment [18F]fluorodeoxyglucose (FDG)-PET scans of stage IIIA/N2 or IIIB NSCLC patients using a training cohort (n = 79; prospective Swiss multi-centre randomized phase III trial SAKK 16/00; 16 centres) and an internal validation cohort (n = 31; single centre). Robustness studies investigating delineation variation, attenuation correction and motion were performed (intraclass correlation coefficient threshold > 0.9). Two 12-/24-month event-free survival (EFS) and overall survival (OS) logistic regression models were trained using standardized imaging: (1) with robust features alone and (2) with all available features. Models were then validated using fivefold cross-validation, and validation on a separate single-centre dataset. Model performance was assessed using area under the receiver operating characteristic curve (AUC). Results Robustness studies identified 179 stable features (13%), with 25% stable features for 3D versus 4D acquisition, 31% for attenuation correction and 78% for delineation. Univariable analysis found no significant robust features predicting 12-/24-month EFS and 12-month OS (p value > 0.076). Prognostic models without robust preselection performed well for 12-month EFS in training (AUC = 0.73) and validation (AUC = 0.74). Patient stratification into two risk groups based on 12-month EFS was significant for training (p value = 0.02) and validation cohorts (p value = 0.03). Conclusions A PET-based radiomics model using a standardized, multi-centre dataset to predict EFS in locally advanced NSCLC was successfully established and validated with good performance. Prediction models with robust feature preselection were unsuccessful, indicating the need for a standardized imaging protocol. Supplementary Information The online version contains supplementary material available at 10.1186/s13550-021-00809-3.
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Affiliation(s)
- Carol Oliveira
- Department of Radiation Oncology, University Hospital Zurich, University of Zurich, Zurich, Switzerland. .,Division of Radiation Oncology, Cancer Center of Southeastern Ontario, Queen's University, Kingston, ON, Canada.
| | - Florian Amstutz
- Department of Radiation Oncology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Diem Vuong
- Department of Radiation Oncology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Marta Bogowicz
- Department of Radiation Oncology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Martin Hüllner
- Department of Nuclear Medicine, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Robert Foerster
- Department of Radiation Oncology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Lucas Basler
- Department of Radiation Oncology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Christina Schröder
- Department of Radiation Oncology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Eric I Eboulet
- Swiss Group for Clinical Cancer Research (SAKK) Coordinating Center, Bern, Switzerland
| | - Miklos Pless
- Department of Medical Oncology, Kantonsspital Winterthur, Winterthur, Switzerland
| | - Sandra Thierstein
- Swiss Group for Clinical Cancer Research (SAKK) Coordinating Center, Bern, Switzerland
| | - Solange Peters
- Department of Oncology, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland
| | - Sven Hillinger
- Department of Thoracic Surgery, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Stephanie Tanadini-Lang
- Department of Radiation Oncology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Matthias Guckenberger
- Department of Radiation Oncology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
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Koike T, Sato N, Hosoda Y, Tazawa M, Goto T, Sato S, Yamazaki M, Toyabe SI, Tsuchida M. Maximum Standardized Uptake Value on Positron Emission Tomography is Associated With More Advanced Disease and High-risk Features in Lung Adenocarcinoma. Semin Thorac Cardiovasc Surg 2021; 34:1051-1060. [PMID: 34320398 DOI: 10.1053/j.semtcvs.2021.07.019] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 07/21/2021] [Indexed: 01/15/2023]
Abstract
18F-fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (FDG-PET/CT) has been widely used for preoperative staging of lung adenocarcinomas. The aim of this study was to determine whether a high maximum standardized uptake value (SUVmax) could correlate with pathological characteristics in those patients. We retrospectively reviewed patients with clinical stage 0-IA lung adenocarcinoma who underwent preoperative 18F-fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography followed by curative anatomical resection. To identify more advanced disease and high-risk features, representing visceral pleural involvement, pulmonary metastasis, lymph node involvement, and lymphovascular involvement in resected surgical specimens, univariate and multivariate logistic regression analyses were performed. The optimal cutoff point for the SUVmax was determined by receiver operating characteristic analysis. In 2 groups divided according to the cutoff point, the disease-free survivals were calculated and compared using the Kaplan-Meier method and the log-rank test. More advanced disease and high-risk features were identified in 55 (18.9%) of the 291 patients. SUVmax was significantly correlated with more advanced disease and high-risk features, as did the consolidation/tumor ratio on computed tomography. Only 2 (1.2%) of the 169 patients with a SUVmax <3.20 showed more advanced disease and high-risk features, compared with 43.4% of patients with a SUVmax ≥3.20. The disease-free survival was significantly higher in patients with a SUVmax <3.20 than in those with a SUVmax ≥3.20 (P = 0.002). A high SUVmax correlates with more advanced disease and high-risk features in patients with clinical stage 0-IA lung adenocarcinoma. The SUVmax should be considered when deciding treatment strategy in early-stage lung adenocarcinoma.
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Affiliation(s)
- Terumoto Koike
- Division of Thoracic and Cardiovascular Surgery, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan.
| | - Noriaki Sato
- Division of Thoracic and Cardiovascular Surgery, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan
| | - Yuta Hosoda
- Division of Thoracic and Cardiovascular Surgery, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan
| | - Masayuki Tazawa
- Division of Thoracic and Cardiovascular Surgery, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan
| | - Tatsuya Goto
- Division of Thoracic and Cardiovascular Surgery, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan
| | - Seijiro Sato
- Division of Thoracic and Cardiovascular Surgery, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan
| | - Motohiko Yamazaki
- Department of Radiology and Radiation Oncology, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan
| | - Shin-Ichi Toyabe
- Niigata University Crisis Management Office, Niigata University, Niigata, Japan
| | - Masanori Tsuchida
- Division of Thoracic and Cardiovascular Surgery, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan
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Krokos G, Pike LC, Cook GJR, Marsden PK. Standardisation of conventional and advanced iterative reconstruction methods for Gallium-68 multi-centre PET-CT trials. EJNMMI Phys 2021; 8:52. [PMID: 34273020 PMCID: PMC8286213 DOI: 10.1186/s40658-021-00400-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Accepted: 07/05/2021] [Indexed: 11/16/2022] Open
Abstract
PURPOSE To assess the applicability of the Fluorine-18 performance specifications defined by EANM Research Ltd (EARL), in Gallium-68 multi-centre PET-CT trials using conventional (ordered subset expectation maximisation, OSEM) and advanced iterative reconstructions which include the systems' point spread function (PSF) and a Bayesian penalised likelihood algorithm (BPL) commercially known as Q.CLEAR. The possibility of standardising the two advanced reconstruction methods was examined. METHODS The NEMA image quality phantom was filled with Gallium-68 and scanned on a GE PET-CT system. PSF and BPL with varying post-reconstruction Gaussian filter width (2-6.4 mm) and penalisation factor (200-1200), respectively, were applied. The average peak-to-valley ratio from six profiles across each sphere was estimated to inspect any edge artefacts. Image noise was assessed using background variability and image roughness. Six GE and Siemens PET-CT scanners provided Gallium-68 images of the NEMA phantom using both conventional and advanced reconstructions from which the maximum, mean and peak recoveries were drawn. Fourteen patients underwent 68Ga-PSMA PET-CT imaging. BPL (200-1200) reconstructions of the data were compared against PSF smoothed with a 6.4-mm Gaussian filter. RESULTS A Gaussian filter width of approximately 6 mm for PSF and a penalisation factor of 800 for BPL were needed to suppress the edge artefacts. In addition, those reconstructions provided the closest agreement between the two advanced iterative reconstructions and low noise levels with the background variability and the image roughness being lower than 7.5% and 11.5%, respectively. The recoveries for all methods generally performed at the lower limits of the EARL specifications, especially for the 13- and 10-mm spheres for which up to 27% (conventional) and 41% (advanced reconstructions) lower limits are suggested. The lesion standardised uptake values from the clinical data were significantly different between BPL and PSF smoothed with a Gaussian filter of 6.4 mm wide for all penalisation factors except for 800 and 1000. CONCLUSION It is possible to standardise the advanced reconstruction methods with the reconstruction parameters being also sufficient for minimising the edge artefacts and noise in the images. For both conventional and advanced reconstructions, Gallium-68 specific recovery coefficient limits were required, especially for the smallest phantom spheres.
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Affiliation(s)
- Georgios Krokos
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
| | - Lucy C Pike
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Gary J R Cook
- Department of Cancer Imaging, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Paul K Marsden
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
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Lapa C, Nestle U, Albert NL, Baues C, Beer A, Buck A, Budach V, Bütof R, Combs SE, Derlin T, Eiber M, Fendler WP, Furth C, Gani C, Gkika E, Grosu AL, Henkenberens C, Ilhan H, Löck S, Marnitz-Schulze S, Miederer M, Mix M, Nicolay NH, Niyazi M, Pöttgen C, Rödel CM, Schatka I, Schwarzenboeck SM, Todica AS, Weber W, Wegen S, Wiegel T, Zamboglou C, Zips D, Zöphel K, Zschaeck S, Thorwarth D, Troost EGC. Value of PET imaging for radiation therapy. Strahlenther Onkol 2021; 197:1-23. [PMID: 34259912 DOI: 10.1007/s00066-021-01812-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Accepted: 06/09/2021] [Indexed: 12/13/2022]
Abstract
This comprehensive review written by experts in their field gives an overview on the current status of incorporating positron emission tomography (PET) into radiation treatment planning. Moreover, it highlights ongoing studies for treatment individualisation and per-treatment tumour response monitoring for various primary tumours. Novel tracers and image analysis methods are discussed. The authors believe this contribution to be of crucial value for experts in the field as well as for policy makers deciding on the reimbursement of this powerful imaging modality.
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Affiliation(s)
- Constantin Lapa
- Nuclear Medicine, Medical Faculty, University of Augsburg, Augsburg, Germany
| | - Ursula Nestle
- Department of Radiation Oncology, Faculty of Medicine, University Medical Center Freiburg, Freiburg, Germany
- German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany
- Department of Radiation Oncology, Kliniken Maria Hilf, Mönchengladbach, Germany
| | - Nathalie L Albert
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Christian Baues
- Department of Radiation Oncology, Cyberknife and Radiotherapy, Medical Faculty, University Hospital Cologne, Cologne, Germany
| | - Ambros Beer
- Department of Nuclear Medicine, Ulm University Hospital, Ulm, Germany
| | - Andreas Buck
- Department of Nuclear Medicine, University Hospital Würzburg, Würzburg, Germany
| | - Volker Budach
- Department of Radiation Oncology, Charité Universitätsmedizin Berlin, Campus Virchow-Klinikum, Berlin, Germany
| | - Rebecca Bütof
- Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
- OncoRay-National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany
| | - Stephanie E Combs
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
- Department of Radiation Oncology, Technical University of Munich (TUM), Klinikum rechts der Isar, Munich, Germany
- Department of Radiation Sciences (DRS), Institute of Radiation Medicine (IRM), Neuherberg, Germany
| | - Thorsten Derlin
- Department of Nuclear Medicine, Hannover Medical School, Hannover, Germany
| | - Matthias Eiber
- Department of Nuclear Medicine, Technical University of Munich (TUM), Klinikum rechts der Isar, Munich, Germany
| | - Wolfgang P Fendler
- Department of Nuclear Medicine, University of Duisburg-Essen and German Cancer Consortium (DKTK)-University Hospital Essen, Essen, Germany
| | - Christian Furth
- Department of Nuclear Medicine, Charité-Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany
| | - Cihan Gani
- German Cancer Consortium (DKTK), Partner Site Tübingen, and German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Radiation Oncology, University of Tübingen, Tübingen, Germany
| | - Eleni Gkika
- Department of Radiation Oncology, Faculty of Medicine, University Medical Center Freiburg, Freiburg, Germany
| | - Anca-L Grosu
- Department of Radiation Oncology, Faculty of Medicine, University Medical Center Freiburg, Freiburg, Germany
- German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany
| | - Christoph Henkenberens
- Department of Radiotherapy and Special Oncology, Medical School Hannover, Hannover, Germany
| | - Harun Ilhan
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Steffen Löck
- Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
- OncoRay-National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany
| | - Simone Marnitz-Schulze
- Department of Radiation Oncology, Cyberknife and Radiotherapy, Medical Faculty, University Hospital Cologne, Cologne, Germany
| | - Matthias Miederer
- Department of Nuclear Medicine, University Hospital Mainz, Mainz, Germany
| | - Michael Mix
- Department of Nuclear Medicine, Faculty of Medicine, Medical Center, University of Freiburg, Freiburg, Germany
| | - Nils H Nicolay
- Department of Radiation Oncology, Faculty of Medicine, University Medical Center Freiburg, Freiburg, Germany
- German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany
| | - Maximilian Niyazi
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
| | - Christoph Pöttgen
- Department of Radiation Oncology, West German Cancer Centre, University of Duisburg-Essen, Essen, Germany
| | - Claus M Rödel
- German Cancer Consortium (DKTK), Partner Site Frankfurt, and German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Radiotherapy and Oncology, Goethe-University Frankfurt, Frankfurt, Germany
| | - Imke Schatka
- Department of Nuclear Medicine, Charité-Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany
| | | | - Andrei S Todica
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Wolfgang Weber
- Department of Nuclear Medicine, Technical University of Munich (TUM), Klinikum rechts der Isar, Munich, Germany
| | - Simone Wegen
- Department of Radiation Oncology, Cyberknife and Radiotherapy, Medical Faculty, University Hospital Cologne, Cologne, Germany
| | - Thomas Wiegel
- Department of Radiation Oncology, Ulm University Hospital, Ulm, Germany
| | - Constantinos Zamboglou
- Department of Radiation Oncology, Faculty of Medicine, University Medical Center Freiburg, Freiburg, Germany
- German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany
| | - Daniel Zips
- German Cancer Consortium (DKTK), Partner Site Tübingen, and German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Radiation Oncology, University of Tübingen, Tübingen, Germany
| | - Klaus Zöphel
- OncoRay-National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany
- National Center for Tumor Diseases (NCT), Partner Site Dresden, Germany: German Cancer Research Center (DKFZ), Heidelberg, Germany, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany, Helmholtz Association/Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany
- German Cancer Consortium (DKTK), Partner Site Dresden, and German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Nuclear Medicine, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
- Department of Nuclear Medicine, Klinikum Chemnitz gGmbH, Chemnitz, Germany
| | - Sebastian Zschaeck
- Department of Radiation Oncology, Charité-Universitätsmedizin Berlin, Charité-Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany
| | - Daniela Thorwarth
- German Cancer Consortium (DKTK), Partner Site Tübingen, and German Cancer Research Center (DKFZ), Heidelberg, Germany
- Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Tübingen, Germany
| | - Esther G C Troost
- Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.
- OncoRay-National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany.
- National Center for Tumor Diseases (NCT), Partner Site Dresden, Germany: German Cancer Research Center (DKFZ), Heidelberg, Germany, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany, Helmholtz Association/Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany.
- German Cancer Consortium (DKTK), Partner Site Dresden, and German Cancer Research Center (DKFZ), Heidelberg, Germany.
- Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiooncology-OncoRay, Dresden, Germany.
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Lapa C, Nestle U, Albert NL, Baues C, Beer A, Buck A, Budach V, Bütof R, Combs SE, Derlin T, Eiber M, Fendler WP, Furth C, Gani C, Gkika E, Grosu AL, Henkenberens C, Ilhan H, Löck S, Marnitz-Schulze S, Miederer M, Mix M, Nicolay NH, Niyazi M, Pöttgen C, Rödel CM, Schatka I, Schwarzenboeck SM, Todica AS, Weber W, Wegen S, Wiegel T, Zamboglou C, Zips D, Zöphel K, Zschaeck S, Thorwarth D, Troost EGC. Value of PET imaging for radiation therapy. Nuklearmedizin 2021; 60:326-343. [PMID: 34261141 DOI: 10.1055/a-1525-7029] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
This comprehensive review written by experts in their field gives an overview on the current status of incorporating positron emission tomography (PET) into radiation treatment planning. Moreover, it highlights ongoing studies for treatment individualisation and per-treatment tumour response monitoring for various primary tumours. Novel tracers and image analysis methods are discussed. The authors believe this contribution to be of crucial value for experts in the field as well as for policy makers deciding on the reimbursement of this powerful imaging modality.
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Affiliation(s)
- Constantin Lapa
- Nuclear Medicine, Medical Faculty, University of Augsburg, Augsburg, Germany
| | - Ursula Nestle
- Department of Radiation Oncology, Faculty of Medicine, University Medical Center Freiburg, Freiburg, Germany.,German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany.,Department of Radiation Oncology, Kliniken Maria Hilf, Mönchengladbach, Germany
| | - Nathalie L Albert
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Christian Baues
- Department of Radiation Oncology, Cyberknife and Radiotherapy, Medical Faculty, University Hospital Cologne, Cologne, Germany
| | - Ambros Beer
- Department of Nuclear Medicine, Ulm University Hospital, Ulm, Germany
| | - Andreas Buck
- Department of Nuclear Medicine, University Hospital Würzburg, Würzburg, Germany
| | - Volker Budach
- Department of Radiation Oncology, Charité-Universitätsmedizin Berlin, Campus Virchow-Klinikum, Berlin, Germany
| | - Rebecca Bütof
- Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.,OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany
| | - Stephanie E Combs
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany.,Department of Radiation Oncology, Technical University of Munich (TUM), Klinikum rechts der Isar, Munich, Germany.,Department of Radiation Sciences (DRS), Institute of Radiation Medicine (IRM), Neuherberg, Germany
| | - Thorsten Derlin
- Department of Nuclear Medicine, Hannover Medical School, Germany
| | - Matthias Eiber
- Department of Nuclear Medicine, Technical University of Munich (TUM), Klinikum rechts der Isar, Munich, Germany
| | - Wolfgang P Fendler
- Department of Nuclear Medicine, University of Duisburg-Essen and German Cancer Consortium (DKTK)-University Hospital Essen, Essen, Germany
| | - Christian Furth
- Department of Nuclear Medicine, Charité-Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany
| | - Cihan Gani
- German Cancer Consortium (DKTK), Partner Site Tübingen, and German Cancer Research Center (DKFZ), Heidelberg, Germany.,Department of Radiation Oncology, University of Tübingen, Tübingen, Germany
| | - Eleni Gkika
- Department of Radiation Oncology, Faculty of Medicine, University Medical Center Freiburg, Freiburg, Germany
| | - Anca L Grosu
- Department of Radiation Oncology, Faculty of Medicine, University Medical Center Freiburg, Freiburg, Germany.,German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany
| | | | - Harun Ilhan
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Steffen Löck
- Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.,OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany
| | - Simone Marnitz-Schulze
- Department of Radiation Oncology, Cyberknife and Radiotherapy, Medical Faculty, University Hospital Cologne, Cologne, Germany
| | - Matthias Miederer
- Department of Nuclear Medicine, University Hospital Mainz, Mainz, Germany
| | - Michael Mix
- Department of Nuclear Medicine, Faculty of Medicine, Medical Center, University of Freiburg, Freiburg, Germany
| | - Nils H Nicolay
- Department of Radiation Oncology, Faculty of Medicine, University Medical Center Freiburg, Freiburg, Germany.,German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany
| | - Maximilian Niyazi
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany.,German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
| | - Christoph Pöttgen
- Department of Radiation Oncology, West German Cancer Centre, University of Duisburg-Essen, Essen, Germany
| | - Claus M Rödel
- German Cancer Consortium (DKTK), Partner Site Frankfurt, and German Cancer Research Center (DKFZ), Heidelberg, Germany.,Department of Radiotherapy and Oncology, Goethe University Frankfurt, Frankfurt, Germany
| | - Imke Schatka
- Department of Nuclear Medicine, Charité-Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany
| | | | - Andrei S Todica
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Wolfgang Weber
- Department of Nuclear Medicine, Technical University of Munich (TUM), Klinikum rechts der Isar, Munich, Germany
| | - Simone Wegen
- Department of Radiation Oncology, Cyberknife and Radiotherapy, Medical Faculty, University Hospital Cologne, Cologne, Germany
| | - Thomas Wiegel
- Department of Radiation Oncology, Ulm University Hospital, Ulm, Germany
| | - Constantinos Zamboglou
- Department of Radiation Oncology, Faculty of Medicine, University Medical Center Freiburg, Freiburg, Germany.,German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany
| | - Daniel Zips
- German Cancer Consortium (DKTK), Partner Site Tübingen, and German Cancer Research Center (DKFZ), Heidelberg, Germany.,Department of Radiation Oncology, University of Tübingen, Tübingen, Germany
| | - Klaus Zöphel
- OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany.,National Center for Tumor Diseases (NCT), Partner Site Dresden, Germany: German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany; Helmholtz Association/Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany.,German Cancer Consortium (DKTK), Partner Site Dresden, and German Cancer Research Center (DKFZ), Heidelberg, Germany.,Department of Nuclear Medicine, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.,Department of Nuclear Medicine, Klinikum Chemnitz gGmbH, Chemnitz, Germany
| | - Sebastian Zschaeck
- Department of Radiation Oncology, Charité-Universitätsmedizin Berlin, Charité-Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany
| | - Daniela Thorwarth
- German Cancer Consortium (DKTK), Partner Site Tübingen, and German Cancer Research Center (DKFZ), Heidelberg, Germany.,Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Tübingen, Germany
| | - Esther G C Troost
- Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.,OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany.,National Center for Tumor Diseases (NCT), Partner Site Dresden, Germany: German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany; Helmholtz Association/Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany.,German Cancer Consortium (DKTK), Partner Site Dresden, and German Cancer Research Center (DKFZ), Heidelberg, Germany.,Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiooncology - OncoRay, Dresden, Germany
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Martínez A, Infante JR, Quirós J, Rayo JI, Serrano J, Moreno M, Jiménez P, Cobo A, Baena A. Baseline 18F-FDG PET/CT quantitative parameters as prognostic factors in esophageal squamous cell cancer. Rev Esp Med Nucl Imagen Mol 2021; 41:S2253-654X(21)00107-4. [PMID: 34088649 DOI: 10.1016/j.remn.2021.03.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Revised: 03/18/2021] [Accepted: 03/18/2021] [Indexed: 11/20/2022]
Abstract
AIM To determine the utility of 18F-FDG PET/CT quantitative parameters as prognostic factors for the response to neoadjuvant treatment, progression-free survival (PFS) and cancer-specific survival (CSS) in patients with esophageal squamous cell carcinoma (SCC). MATERIAL AND METHODS Thirty patients (29 men) diagnosed with SCC were retrospectively evaluated over a 6-year interval. Metabolic parameters were determined: maximum SUV (SUVmax), mean SUV (SUVmed), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) from baseline PET/CT study. After treatment with chemotherapy and/or radiotherapy, response to treatment and patient survival were assessed. The comparison of parameters between groups of responders and non-responders was carried out using a Mann-Whitney U test. ROC curves and the Kaplan-Meier method were used for analysis of prognostic factors and survival curves. RESULTS The average follow-up was 22.4months, with 22 recurrence-progressions and 25 deads. Significant differences were demonstrated between responders and non-responders with respect to tumor size, MTV and TLG. Survival analysis found significant differences for SCE and CSS depending on these three parameters. CONCLUSION Metabolic parameters MTV and TLG, and tumor size were prognostic factors for neoadjuvant treatment response, PFS, and CSS in patients diagnosed with SCC. Neither SUVmax nor SUVmed were predictive for any of the evaluation criteria. Results could help to personalize patient treatment.
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Affiliation(s)
- A Martínez
- Servicio de Medicina Nuclear, Hospital Universitario de Badajoz, Badajoz, España.
| | - J R Infante
- Servicio de Medicina Nuclear, Hospital Universitario de Badajoz, Badajoz, España
| | - J Quirós
- Servicio de Oncología Radioterápica, Hospital Universitario de Badajoz, Badajoz, España
| | - J I Rayo
- Servicio de Medicina Nuclear, Hospital Universitario de Badajoz, Badajoz, España
| | - J Serrano
- Servicio de Medicina Nuclear, Hospital Universitario de Badajoz, Badajoz, España
| | - M Moreno
- Servicio de Medicina Nuclear, Hospital Universitario de Badajoz, Badajoz, España
| | - P Jiménez
- Servicio de Medicina Nuclear, Hospital Universitario de Badajoz, Badajoz, España
| | - A Cobo
- Servicio de Medicina Nuclear, Hospital Universitario de Badajoz, Badajoz, España
| | - A Baena
- Servicio de Medicina Nuclear, Hospital Universitario de Badajoz, Badajoz, España
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41
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Roll W, Weckesser M, Seifert R, Bodei L, Rahbar K. Imaging and liquid biopsy in the prediction and evaluation of response to PRRT in neuroendocrine tumors: implications for patient management. Eur J Nucl Med Mol Imaging 2021; 48:4016-4027. [PMID: 33903926 PMCID: PMC8484222 DOI: 10.1007/s00259-021-05359-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Accepted: 04/05/2021] [Indexed: 12/16/2022]
Abstract
Purpose The aim of this narrative review is to give an overview on current and emerging imaging methods and liquid biopsy for prediction and evaluation of response to PRRT. Current limitations and new perspectives, including artificial intelligence, are discussed. Methods A literature review of PubMed/Medline was performed with representative keywords. The search included articles published online through August 31, 2020. All searches were restricted to English language manuscripts. Results Peptide radio receptor therapy (PRRT) is a prospectively evaluated and approved therapy option in neuroendocrine tumors (NETs). Different ligands targeting the somatostatin receptor (SSTR) are used as theranostic pairs for imaging NET and for PRRT. Response assessment in prospective trials often relies on the morphological RECIST 1.1 criteria, based on lesion size in CT or MRI. The role of SSTR-PET and quantitative uptake parameters and volumetric data is still not defined. Monoanalyte tumor marker chromogranin A has a limited value for response assessment after PRRT. New emerging liquid biopsy techniques are offering prediction of response to PRRT and prognostic value. Conclusions New response criteria for NET patients undergoing PRRT will comprise multiparametric hybrid imaging and blood-based multianalyte markers. This represents tumor biology and heterogeneity.
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Affiliation(s)
- Wolfgang Roll
- Department of Nuclear Medicine, University Hospital Muenster, Albert-Schweitzer-Campus 1, 48149, Münster, Germany.,West German Cancer Center, Muenster and Essen, Essen, Germany
| | - Matthias Weckesser
- Department of Nuclear Medicine, University Hospital Muenster, Albert-Schweitzer-Campus 1, 48149, Münster, Germany.,West German Cancer Center, Muenster and Essen, Essen, Germany
| | - Robert Seifert
- Department of Nuclear Medicine, University Hospital Muenster, Albert-Schweitzer-Campus 1, 48149, Münster, Germany.,West German Cancer Center, Muenster and Essen, Essen, Germany.,Department of Nuclear Medicine, University Hospital Essen, Essen, Germany
| | - Lisa Bodei
- Department of Nuclear Medicine, Radiology, Memorial Sloan Kettering Cancer Center, New York, USA
| | - Kambiz Rahbar
- Department of Nuclear Medicine, University Hospital Muenster, Albert-Schweitzer-Campus 1, 48149, Münster, Germany. .,West German Cancer Center, Muenster and Essen, Essen, Germany.
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42
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The dynamics and prognostic value of FDG PET-metrics in weekly monitoring of (chemo)radiotherapy for NSCLC. Radiother Oncol 2021; 160:107-114. [PMID: 33872642 DOI: 10.1016/j.radonc.2021.04.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Revised: 02/03/2021] [Accepted: 04/08/2021] [Indexed: 12/25/2022]
Abstract
PURPOSE To test if the relative change in FDG-PET SUVmax over the course of treatment was associated with disease progression and overall survival. Additionally, the prognostic values of other first-order PET-metric changes were investigated. METHODS The study included 38 patients with stage II-III NSCLC, who underwent concurrent chemoradiotherapy. Patients received two pre-treatment FDG-PET scans and four during-treatment scans at weekly intervals. SUVmax was normalized to the start of treatment and analyzed using linear regression. Linear regression coefficients of other first order PET-metrics were grouped according to dissimilarity. Associations to patient outcome were analyzed using Cox hazard ratio. RESULTS Twenty-eight patients satisfied the criteria for analysis. All PET-metrics demonstrated a strong linear correlation with time during treatment [median R-range: -0.87: -0.97]. No strong associations (p > 0.10) were found for the relative slope of SUVmax to patient outcomes. Other first-order metrics did correlate with outcome but the single imaging time-point maximizing the association of PET response with outcome varied per PET metric and outcome parameter. CONCLUSION All investigated FDG PET metrics linearly decreased during treatment. Relative change in SUVmax was not associated to patient outcome while several other first order PET-metrics were related to patient outcome. A single optimal imaging time-point could not be identified.
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43
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Montes de Jesus F, Dierickx D, Vergote V, Noordzij W, Dierckx RAJO, Deroose CM, Glaudemans AWJM, Gheysens O, Kwee TC. Prognostic superiority of International Prognostic Index over [ 18F]FDG PET/CT volumetric parameters in post-transplant lymphoproliferative disorder. EJNMMI Res 2021; 11:29. [PMID: 33738643 PMCID: PMC7973341 DOI: 10.1186/s13550-021-00769-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Accepted: 03/03/2021] [Indexed: 11/19/2022] Open
Abstract
Background Post-transplant lymphoproliferative disorders (PTLDs) are a spectrum of hematological malignancies occurring after solid organ and hematopoietic stem cell transplantation. [18F]FDG PET/CT is routinely performed at PTLD diagnosis, allowing for both staging of the disease and quantification of volumetric parameters, such as whole-body metabolic tumor volume (MTV) and total lesion glycolysis (TLG). In this retrospective study, we aimed to determine the prognostic value of MTV and TLG in PTLD patients, together with other variables of interest, such as the International Prognostic Index (IPI), organ transplant type, EBV tumor status, time after transplant, albumin levels and PTLD morphology. Results A total of 88 patients were included. The 1-, 3-, 5- year overall survival rates were 67%, 58% and 43% respectively. Multivariable analysis indicated that a high IPI (HR: 1.56, 95% CI: 1.13–2.16) and an EBV-negative tumor (HR: 2.71, 95% CI: 1.38–5.32) were associated with poor overall survival. Patients with a kidney transplant had a longer overall survival than any other organ recipients (HR: 0.38 95% CI: 0.16–0.89). IPI was found to be the best predicting parameter of overall survival in our cohort. Whole-body MTV, TLG, time after transplant, hypoalbuminemia and PTLD morphology were not associated with overall survival. Conclusion [18F]FDG PET/CT whole-body volumetric quantitative parameters were not predictive of overall survival in PTLD. In our cohort, high IPI and an EBV-negative tumor were found to predictors of worse overall survival while kidney transplant patients had a longer overall survival compared to other organ transplant recipients
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Affiliation(s)
- F Montes de Jesus
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9700 RB, Groningen, The Netherlands.
| | - D Dierickx
- Department of Hematology, University Hospitals Leuven, Leuven, Belgium
| | - V Vergote
- Department of Hematology, University Hospitals Leuven, Leuven, Belgium
| | - W Noordzij
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9700 RB, Groningen, The Netherlands
| | - R A J O Dierckx
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9700 RB, Groningen, The Netherlands
| | - C M Deroose
- Department of Nuclear Medicine, University Hospitals Leuven, Leuven, Belgium
| | - A W J M Glaudemans
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9700 RB, Groningen, The Netherlands
| | - O Gheysens
- Department of Nuclear Medicine, Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - T C Kwee
- Department of Radiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
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van Sluis J, Yaqub M, Brouwers AH, Dierckx RAJO, Noordzij W, Boellaard R. Use of population input functions for reduced scan duration whole-body Patlak 18F-FDG PET imaging. EJNMMI Phys 2021; 8:11. [PMID: 33547518 PMCID: PMC7865035 DOI: 10.1186/s40658-021-00357-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Accepted: 01/22/2021] [Indexed: 11/10/2022] Open
Abstract
Abstract Whole-body Patlak images can be obtained from an acquisition of first 6 min of dynamic imaging over the heart to obtain the arterial input function (IF), followed by multiple whole-body sweeps up to 60 min pi. The use of a population-averaged IF (PIF) could exclude the first dynamic scan and minimize whole-body sweeps to 30–60 min pi. Here, the effects of (incorrect) PIFs on the accuracy of the proposed Patlak method were assessed. In addition, the extent of mitigating these biases through rescaling of the PIF to image-derived IF values at 30–60 min pi was evaluated. Methods Using a representative IF and rate constants from the literature, various tumour time-activity curves (TACs) were simulated. Variations included multiplication of the IF with a positive and negative gradual linear bias over 60 min of 5, 10, 15, 20, and 25% (generating TACs using an IF different from the PIF); use of rate constants (K1, k3, and both K1 and k2) multiplied by 2, 1.5, and 0.75; and addition of noise (μ = 0 and σ = 5, 10 and 15%). Subsequent Patlak analysis using the original IF (representing the PIF) was used to obtain the influx constant (Ki) for the differently simulated TACs. Next, the PIF was scaled towards the (simulated) IF value using the 30–60-min pi time interval, simulating scaling of the PIF to image-derived values. Influence of variabilities in IF and rate constants, and rescaling the PIF on bias in Ki was evaluated. Results Percentage bias in Ki observed using simulated modified IFs varied from − 16 to 16% depending on the simulated amplitude and direction of the IF modifications. Subsequent scaling of the PIF reduced these Ki biases in most cases (287 out of 290) to < 5%. Conclusions Simulations suggest that scaling of a (possibly incorrect) PIF to IF values seen in whole-body dynamic imaging from 30 to 60 min pi can provide accurate Ki estimates. Consequently, dynamic Patlak imaging protocols may be performed for 30–60 min pi making whole-body Patlak imaging clinically feasible.
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Affiliation(s)
- Joyce van Sluis
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ, Groningen, The Netherlands.
| | - Maqsood Yaqub
- Department of Radiology and Nuclear Medicine, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Adrienne H Brouwers
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ, Groningen, The Netherlands
| | - Rudi A J O Dierckx
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ, Groningen, The Netherlands
| | - Walter Noordzij
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ, Groningen, The Netherlands
| | - Ronald Boellaard
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ, Groningen, The Netherlands.,Department of Radiology and Nuclear Medicine, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
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Montes de Jesus F, Vergote V, Noordzij W, Dierickx D, Dierckx R, Diepstra A, Tousseyn T, Gheysens O, Kwee T, Deroose C, Glaudemans A. Semi-Quantitative Characterization of Post-Transplant Lymphoproliferative Disorder Morphological Subtypes with [ 18F]FDG PET/CT. J Clin Med 2021; 10:jcm10020361. [PMID: 33477971 PMCID: PMC7835947 DOI: 10.3390/jcm10020361] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Revised: 01/08/2021] [Accepted: 01/14/2021] [Indexed: 01/22/2023] Open
Abstract
Background: Post-transplant lymphoproliferative disorder (PTLD) is a complication of organ transplantation classified according to the WHO as nondestructive, polymorphic, monomorphic, and classic Hodgkin Lymphoma subtypes. In this retrospective study, we investigated the potential of semi-quantitative 2-[18F]fluoro-2-deoxy-D-glucose ([18F]FDG) PET/computed tomography (CT)-based parameters to differentiate between the PTLD morphological subtypes. Methods: 96 patients with histopathologically confirmed PTLD and baseline [18F]FDG PET/CT between 2009 and 2019 were included. Extracted semi-quantitative measurements included: Maximum, peak, and mean standardized uptake value (SUVmax, SUVpeak, and SUVmean). Results: Median SUVs were highest for monomorphic PTLD followed by polymorphic and nondestructive subtypes. The median SUVpeak at the biopsy site was significantly higher in monomorphic PTLD (17.8, interquartile range (IQR):16) than in polymorphic subtypes (9.8, IQR:13.4) and nondestructive (4.1, IQR:6.1) (p = 0.04 and p ≤ 0.01, respectively). An SUVpeak ≥ 24.8 was always indicative of a monomorphic PTLD in our dataset. Nevertheless, there was a considerable overlap in SUV across the different morphologies. Conclusion: The median SUVpeak at the biopsy site was significantly higher in monomorphic PTLD than polymorphic and nondestructive subtypes. However, due to significant SUV overlap across the different subtypes, these values may only serve as an indication of PTLD morphology, and SUV-based parameters cannot replace histopathological classification.
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Affiliation(s)
- Filipe Montes de Jesus
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, 9700 RB Groningen, The Netherlands; (W.N.); (R.D.); (A.G.)
- Correspondence:
| | - Vibeke Vergote
- Department of Hematology, University Hospitals Leuven, 3000 Leuven, Belgium; (V.V.); (D.D.)
| | - Walter Noordzij
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, 9700 RB Groningen, The Netherlands; (W.N.); (R.D.); (A.G.)
| | - Daan Dierickx
- Department of Hematology, University Hospitals Leuven, 3000 Leuven, Belgium; (V.V.); (D.D.)
| | - Rudi Dierckx
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, 9700 RB Groningen, The Netherlands; (W.N.); (R.D.); (A.G.)
| | - Arjan Diepstra
- Department of Pathology and Medical Biology, University of Groningen, University Medical Center Groningen, 9700 RB Groningen, The Netherlands;
| | - Thomas Tousseyn
- Department of Pathology University Hospitals Leuven, 3000 Leuven, Belgium;
| | - Olivier Gheysens
- Department of Nuclear Medicine, Cliniques Universitaires Saint-Luc, 1200 Brussels, Belgium;
| | - Thomas Kwee
- Department of Radiology, University of Groningen, University Medical Center Groningen, 9700 RB Groningen, The Netherlands;
| | - Christophe Deroose
- Department of Nuclear Medicine, University Hospitals Leuven, 3000 Leuven, Belgium;
| | - Andor Glaudemans
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, 9700 RB Groningen, The Netherlands; (W.N.); (R.D.); (A.G.)
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Casali M, Lauri C, Altini C, Bertagna F, Cassarino G, Cistaro A, Erba AP, Ferrari C, Mainolfi CG, Palucci A, Prandini N, Baldari S, Bartoli F, Bartolomei M, D’Antonio A, Dondi F, Gandolfo P, Giordano A, Laudicella R, Massollo M, Nieri A, Piccardo A, Vendramin L, Muratore F, Lavelli V, Albano D, Burroni L, Cuocolo A, Evangelista L, Lazzeri E, Quartuccio N, Rossi B, Rubini G, Sollini M, Versari A, Signore A. State of the art of 18F-FDG PET/CT application in inflammation and infection: a guide for image acquisition and interpretation. Clin Transl Imaging 2021; 9:299-339. [PMID: 34277510 PMCID: PMC8271312 DOI: 10.1007/s40336-021-00445-w] [Citation(s) in RCA: 58] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2021] [Accepted: 06/19/2021] [Indexed: 02/06/2023]
Abstract
AIM The diagnosis, severity and extent of a sterile inflammation or a septic infection could be challenging since there is not one single test able to achieve an accurate diagnosis. The clinical use of 18F-fluorodeoxyglucose ([18F]FDG) positron emission tomography/computed tomography (PET/CT) imaging in the assessment of inflammation and infection is increasing worldwide. The purpose of this paper is to achieve an Italian consensus document on [18F]FDG PET/CT or PET/MRI in inflammatory and infectious diseases, such as osteomyelitis (OM), prosthetic joint infections (PJI), infective endocarditis (IE), prosthetic valve endocarditis (PVE), cardiac implantable electronic device infections (CIEDI), systemic and cardiac sarcoidosis (SS/CS), diabetic foot (DF), fungal infections (FI), tuberculosis (TBC), fever and inflammation of unknown origin (FUO/IUO), pediatric infections (PI), inflammatory bowel diseases (IBD), spine infections (SI), vascular graft infections (VGI), large vessel vasculitis (LVV), retroperitoneal fibrosis (RF) and COVID-19 infections. METHODS In September 2020, the inflammatory and infectious diseases focus group (IIFG) of the Italian Association of Nuclear Medicine (AIMN) proposed to realize a procedural paper about the clinical applications of [18F]FDG PET/CT or PET/MRI in inflammatory and infectious diseases. The project was carried out thanks to the collaboration of 13 Italian nuclear medicine centers, with a consolidate experience in this field. With the endorsement of AIMN, IIFG contacted each center, and the pediatric diseases focus group (PDFC). IIFG provided for each team involved, a draft with essential information regarding the execution of [18F]FDG PET/CT or PET/MRI scan (i.e., indications, patient preparation, standard or specific acquisition modalities, interpretation criteria, reporting methods, pitfalls and artifacts), by limiting the literature research to the last 20 years. Moreover, some clinical cases were required from each center, to underline the teaching points. Time for the collection of each report was from October to December 2020. RESULTS Overall, we summarized 291 scientific papers and guidelines published between 1998 and 2021. Papers were divided in several sub-topics and summarized in the following paragraphs: clinical indications, image interpretation criteria, future perspectivess and new trends (for each single disease), while patient preparation, image acquisition, possible pitfalls and reporting modalities were described afterwards. Moreover, a specific section was dedicated to pediatric and PET/MRI indications. A collection of images was described for each indication. CONCLUSIONS Currently, [18F]FDG PET/CT in oncology is globally accepted and standardized in main diagnostic algorithms for neoplasms. In recent years, the ever-closer collaboration among different European associations has tried to overcome the absence of a standardization also in the field of inflammation and infections. The collaboration of several nuclear medicine centers with a long experience in this field, as well as among different AIMN focus groups represents a further attempt in this direction. We hope that this document will be the basis for a "common nuclear physicians' language" throughout all the country. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1007/s40336-021-00445-w.
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Affiliation(s)
- Massimiliano Casali
- Nuclear Medicine Unit, Azienda Unità Sanitaria Locale IRCCS, Reggio Emilia, Italy
| | - Chiara Lauri
- grid.7841.aNuclear Medicine Unit, Department of Medical-Surgical Sciences and of Translational Medicine, “Sapienza” University of Rome, Rome, Italy
| | - Corinna Altini
- grid.7644.10000 0001 0120 3326Nuclear Medicine Unit, Interdisciplinary Department of Medicine, University of Bari, Bari, Italy
| | - Francesco Bertagna
- grid.412725.7Nuclear Medicine, University of Brescia and Spedali Civili di Brescia, Brescia, Italy
| | - Gianluca Cassarino
- grid.5608.b0000 0004 1757 3470Nuclear Medicine Unit, Department of Medicine DIMED, University of Padova, Padova, Italy
| | | | - Anna Paola Erba
- grid.5395.a0000 0004 1757 3729Regional Center of Nuclear Medicine, Department of Translational Research and Advanced Technologies in Medicine, University of Pisa, Pisa, Italy
| | - Cristina Ferrari
- grid.7644.10000 0001 0120 3326Nuclear Medicine Unit, Interdisciplinary Department of Medicine, University of Bari, Bari, Italy
| | - Ciro Gabriele Mainolfi
- grid.4691.a0000 0001 0790 385XDepartment of Advanced Biomedical Sciences, University “Federico II”, Naples, Italy
| | - Andrea Palucci
- grid.415845.9Department of Nuclear Medicine, “Ospedali Riuniti di Torrette” Hospital, Ancona, Italy
| | - Napoleone Prandini
- grid.418324.80000 0004 1781 8749Nuclear Medicine Unit, Department of Diagnostic Imaging, Centro Diagnostico Italiano, Milan, Italy
| | - Sergio Baldari
- grid.10438.3e0000 0001 2178 8421Nuclear Medicine Unit, Department of Biomedical and Dental Sciences and of Morpho-Functional Imaging, University of Messina, Messina, Italy
| | - Francesco Bartoli
- grid.5395.a0000 0004 1757 3729Regional Center of Nuclear Medicine, Department of Translational Research and Advanced Technologies in Medicine, University of Pisa, Pisa, Italy
| | - Mirco Bartolomei
- grid.416315.4Nuclear Medicine Unit, Oncological Medical and Specialists Department, University Hospital of Ferrara, Ferrara, Italy
| | - Adriana D’Antonio
- grid.4691.a0000 0001 0790 385XDepartment of Advanced Biomedical Sciences, University “Federico II”, Naples, Italy
| | - Francesco Dondi
- grid.412725.7Nuclear Medicine, University of Brescia and Spedali Civili di Brescia, Brescia, Italy
| | - Patrizia Gandolfo
- grid.418324.80000 0004 1781 8749Nuclear Medicine Unit, Department of Diagnostic Imaging, Centro Diagnostico Italiano, Milan, Italy
| | - Alessia Giordano
- grid.4691.a0000 0001 0790 385XDepartment of Advanced Biomedical Sciences, University “Federico II”, Naples, Italy
| | - Riccardo Laudicella
- grid.10438.3e0000 0001 2178 8421Nuclear Medicine Unit, Department of Biomedical and Dental Sciences and of Morpho-Functional Imaging, University of Messina, Messina, Italy
| | | | - Alberto Nieri
- grid.416315.4Nuclear Medicine Unit, Oncological Medical and Specialists Department, University Hospital of Ferrara, Ferrara, Italy
| | | | - Laura Vendramin
- grid.5608.b0000 0004 1757 3470Nuclear Medicine Unit, Department of Medicine DIMED, University of Padova, Padova, Italy
| | - Francesco Muratore
- Rheumatology Unit, Azienda Unità Sanitaria Locale IRCCS, Reggio Emilia, Italy
| | - Valentina Lavelli
- grid.7644.10000 0001 0120 3326Nuclear Medicine Unit, Interdisciplinary Department of Medicine, University of Bari, Bari, Italy
| | - Domenico Albano
- grid.412725.7Nuclear Medicine, University of Brescia and Spedali Civili di Brescia, Brescia, Italy
| | - Luca Burroni
- grid.415845.9Department of Nuclear Medicine, “Ospedali Riuniti di Torrette” Hospital, Ancona, Italy
| | - Alberto Cuocolo
- grid.4691.a0000 0001 0790 385XDepartment of Advanced Biomedical Sciences, University “Federico II”, Naples, Italy
| | - Laura Evangelista
- grid.5608.b0000 0004 1757 3470Nuclear Medicine Unit, Department of Medicine DIMED, University of Padova, Padova, Italy
| | - Elena Lazzeri
- grid.5395.a0000 0004 1757 3729Regional Center of Nuclear Medicine, Department of Translational Research and Advanced Technologies in Medicine, University of Pisa, Pisa, Italy
| | - Natale Quartuccio
- grid.419995.9Nuclear Medicine Unit, A.R.N.A.S. Civico di Cristina and Benfratelli Hospitals, Palermo, Italy
| | - Brunella Rossi
- Nuclear Medicine Unit, Department of Services, ASUR MARCHE-AV5, Ascoli Piceno, Italy
| | - Giuseppe Rubini
- grid.7644.10000 0001 0120 3326Nuclear Medicine Unit, Interdisciplinary Department of Medicine, University of Bari, Bari, Italy
| | - Martina Sollini
- grid.417728.f0000 0004 1756 8807Humanitas Clinical and Research Center, IRCCS, Rozzano, Italy
| | - Annibale Versari
- Nuclear Medicine Unit, Azienda Unità Sanitaria Locale IRCCS, Reggio Emilia, Italy
| | - Alberto Signore
- grid.7841.aNuclear Medicine Unit, Department of Medical-Surgical Sciences and of Translational Medicine, “Sapienza” University of Rome, Rome, Italy
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Infante J, Cabrera J, Rayo J, Cruz C, Serrano J, Moreno M, Martínez A, Jiménez P, Cobo A. 18F-FDG PET/CT quantitative parameters as prognostic factors in localized and inoperable lung cancer. Rev Esp Med Nucl Imagen Mol 2020. [DOI: 10.1016/j.remnie.2020.09.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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48
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Sun Y, Sun Y, Qin Y, Zhang Y, Yuan H, Yang Z. ‘Virtual experience’ as an intervention before a positron emission tomography/CT scan may ease patients’ anxiety and improve image quality. J Med Imaging Radiat Oncol 2020; 64:641-648. [DOI: 10.1111/1754-9485.13078] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Revised: 05/11/2020] [Accepted: 05/28/2020] [Indexed: 11/30/2022]
Affiliation(s)
- Yuyun Sun
- Department of Nuclear Medicine Fudan University Shanghai Cancer Center Shanghai China
- Department of Oncology Shanghai Medical College Fudan University Shanghai China
- Center for Biomedical Imaging Fudan University Shanghai China
- Shanghai Engineering Research Center of Molecular Imaging Probes Shanghai China
| | - Yifei Sun
- Department of Nuclear Medicine Fudan University Shanghai Cancer Center Shanghai China
- Department of Oncology Shanghai Medical College Fudan University Shanghai China
- Center for Biomedical Imaging Fudan University Shanghai China
- Shanghai Engineering Research Center of Molecular Imaging Probes Shanghai China
| | - Yue Qin
- Department of Nuclear Medicine Fudan University Shanghai Cancer Center Shanghai China
- Department of Oncology Shanghai Medical College Fudan University Shanghai China
- Center for Biomedical Imaging Fudan University Shanghai China
- Shanghai Engineering Research Center of Molecular Imaging Probes Shanghai China
| | - Yingjian Zhang
- Department of Nuclear Medicine Fudan University Shanghai Cancer Center Shanghai China
- Department of Oncology Shanghai Medical College Fudan University Shanghai China
- Center for Biomedical Imaging Fudan University Shanghai China
- Shanghai Engineering Research Center of Molecular Imaging Probes Shanghai China
| | - Huiyu Yuan
- Department of Nuclear Medicine Fudan University Shanghai Cancer Center Shanghai China
- Department of Oncology Shanghai Medical College Fudan University Shanghai China
- Center for Biomedical Imaging Fudan University Shanghai China
- Shanghai Engineering Research Center of Molecular Imaging Probes Shanghai China
| | - Zhongyi Yang
- Department of Nuclear Medicine Fudan University Shanghai Cancer Center Shanghai China
- Department of Oncology Shanghai Medical College Fudan University Shanghai China
- Center for Biomedical Imaging Fudan University Shanghai China
- Shanghai Engineering Research Center of Molecular Imaging Probes Shanghai China
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Infante JR, Cabrera J, Rayo JI, Cruz C, Serrano J, Moreno M, Martínez A, Jiménez P, Cobo A. 18F-FDG PET/CT quantitative parameters as prognostic factor in localized and inoperable lung cancer. Rev Esp Med Nucl Imagen Mol 2020; 39:353-359. [PMID: 32605894 DOI: 10.1016/j.remn.2020.05.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2020] [Revised: 05/23/2020] [Accepted: 05/25/2020] [Indexed: 12/25/2022]
Abstract
AIM To assess the utility of 18F-FDG PET/CT quantitative parameters as prognostic factor in patients diagnosed with localized and inoperable lung cancer treated by stereotactic body radiotherapy (SBRT). MATERIAL AND METHODS Fifty patients (42 men) diagnosed in the last 7years with early-stage lung cancer and treated with SBRT alone were assessed by a prospective study. After PET/CT study, metabolic parameters maximum SUV (SUVmax), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were determined at different thresholds. The prognostic factors for overall survival (OS), cause-specific survival (CS) and disease-free survival (DFS) were analysed by Cox proportional hazards model and the survival analysis by Kaplan-Meier method. RESULTS The average follow-up was 39.6months, with 21 recurrences and 24 dead. Univariate analysis determined MTV30 and MTV40 as predictors for OS; MTV30, MTV40, TLG30 and TLG40 for CS, and MTV2, MTV30, MTV40, TLG2, TLG30 and TLG40 for DFS. Survival analysis found statistically significant differences for CS and DFS depending on tumor size and for DFS considering the cut-off values of MTV2 and TLG2 (threshold SUVmax=2). SUVmax, age and sex were not shown to be significant factors. CONCLUSION Pre-treatment quantitative assessment using metabolic parameters MTV2 and TLG2 as well as tumor size proved to be prognostic factors in patients diagnosed with localized and inoperable lung cancer treated by SBRT. Results could help to personalize treatment.
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Affiliation(s)
- J R Infante
- Servicio de Medicina Nuclear, Complejo Hospitalario Universitario de Badajoz, Badajoz, España.
| | - J Cabrera
- Servicio de Oncología Radioterápica, Complejo Hospitalario Universitario de Badajoz, Badajoz, España
| | - J I Rayo
- Servicio de Medicina Nuclear, Complejo Hospitalario Universitario de Badajoz, Badajoz, España
| | - C Cruz
- Servicio de Oncología Radioterápica, Hospital Punta de Europa, Algeciras, Cádiz, España
| | - J Serrano
- Servicio de Medicina Nuclear, Complejo Hospitalario Universitario de Badajoz, Badajoz, España
| | - M Moreno
- Servicio de Medicina Nuclear, Complejo Hospitalario Universitario de Badajoz, Badajoz, España
| | - A Martínez
- Servicio de Medicina Nuclear, Complejo Hospitalario Universitario de Badajoz, Badajoz, España
| | - P Jiménez
- Servicio de Medicina Nuclear, Complejo Hospitalario Universitario de Badajoz, Badajoz, España
| | - A Cobo
- Servicio de Medicina Nuclear, Complejo Hospitalario Universitario de Badajoz, Badajoz, España
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50
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Beheshti M, Manafi-Farid R, Rezaee A, Langsteger W. PET/CT and PET/MRI, Normal Variations, and Artifacts. Clin Nucl Med 2020. [DOI: 10.1007/978-3-030-39457-8_17] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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