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Payan N, Presles B, Coutant C, Desmoulins I, Ladoire S, Beltjens F, Brunotte F, Vrigneaud JM, Cochet A. Respective contribution of baseline clinical data, tumour metabolism and tumour blood-flow in predicting pCR after neoadjuvant chemotherapy in HER2 and Triple Negative breast cancer. EJNMMI Res 2024; 14:60. [PMID: 38965124 PMCID: PMC11224181 DOI: 10.1186/s13550-024-01115-4] [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: 02/27/2024] [Accepted: 05/28/2024] [Indexed: 07/06/2024] Open
Abstract
BACKGROUND The aim of this study is to investigate the added value of combining tumour blood flow (BF) and metabolism parameters, including texture features, with clinical parameters to predict, at baseline, the pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in patients with newly diagnosed breast cancer (BC). METHODS One hundred and twenty-eight BC patients underwent a 18F-FDG PET/CT before any treatment. Tumour BF and metabolism parameters were extracted from first-pass dynamic and delayed PET images, respectively. Standard and texture features were extracted from BF and metabolic images. Prediction of pCR was performed using logistic regression, random forest and support vector classification algorithms. Models were built using clinical (C), clinical and metabolic (C+M) and clinical, metabolic and tumour BF (C+M+BF) information combined. Algorithms were trained on 80% of the dataset and tested on the remaining 20%. Univariate and multivariate features selections were carried out on the training dataset. A total of 50 shuffle splits were performed. The analysis was carried out on the whole dataset (HER2 and Triple Negative (TN)), and separately in HER2 (N=76) and TN (N=52) tumours. RESULTS In the whole dataset, the highest classification performances were observed for C+M models, significantly (p-value<0.01) higher than C models and better than C+M+BF models (mean balanced accuracy of 0.66, 0.61, and 0.64 respectively). For HER2 tumours, equal performances were noted for C and C+M models, with performances higher than C+M+BF models (mean balanced accuracy of 0.64, and 0.61 respectively). Regarding TN tumours, the best classification results were reported for C+M models, with better performances than C and C+M+BF models but not significantly (mean balanced accuracy of 0.65, 0.63, and 0.62 respectively). CONCLUSION Baseline clinical data combined with global and texture tumour metabolism parameters assessed by 18F-FDG PET/CT provide a better prediction of pCR after NAC in patients with BC compared to clinical parameters alone for TN, and HER2 and TN tumours together. In contrast, adding BF parameters to the models did not improve prediction, regardless of the tumour subgroup analysed.
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Affiliation(s)
- Neree Payan
- Department of Nuclear Medicine, Georges-François Leclerc Cancer Centre, Dijon, France.
- IFTIM, ICMUB Laboratory, UMR CNRS 6302, University of Burgundy, Dijon, France.
| | - Benoit Presles
- IFTIM, ICMUB Laboratory, UMR CNRS 6302, University of Burgundy, Dijon, France
| | - Charles Coutant
- Department of Medical Oncology, Georges-François Leclerc Cancer Centre, Dijon, France
| | - Isabelle Desmoulins
- Department of Medical Oncology, Georges-François Leclerc Cancer Centre, Dijon, France
| | - Sylvain Ladoire
- Department of Medical Oncology, Georges-François Leclerc Cancer Centre, Dijon, France
| | - Françoise Beltjens
- Department of Tumor Biology and Pathology, Georges-François Leclerc Cancer Centre, Dijon, France
| | - François Brunotte
- IFTIM, ICMUB Laboratory, UMR CNRS 6302, University of Burgundy, Dijon, France
| | - Jean-Marc Vrigneaud
- Department of Nuclear Medicine, Georges-François Leclerc Cancer Centre, Dijon, France
- IFTIM, ICMUB Laboratory, UMR CNRS 6302, University of Burgundy, Dijon, France
| | - Alexandre Cochet
- Department of Nuclear Medicine, Georges-François Leclerc Cancer Centre, Dijon, France
- IFTIM, ICMUB Laboratory, UMR CNRS 6302, University of Burgundy, Dijon, France
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Kupik O, Tuncel M, Özgen Kıratlı P, Akpınar MG, Altundağ K, Başaran Demirkazık F, Erbaş B. Value of Dynamic 18F-FDG PET/CT in Predicting the Success of Neoadjuvant Chemotherapy in Patients with Locally Advanced Breast Cancer: A Prospective Study. Mol Imaging Radionucl Ther 2023; 32:94-102. [PMID: 37337702 PMCID: PMC10284189 DOI: 10.4274/mirt.galenos.2022.97658] [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: 08/29/2022] [Accepted: 12/18/2022] [Indexed: 06/21/2023] Open
Abstract
Objectives This prospective study was planned to compare the predictive value of dynamic 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) in locally advanced breast cancer patients (LABC) receiving neoadjuvant chemotherapy (NAC). Methods Twenty seven patients with LABC [median age: 47, (26-66)] underwent a dynamic 18F-FDG PET study at baseline, and after 2-3 cycles of (NAC) were included (interim). Maximum standardized uptake value (SUVmax) values and SUV ratios for the 2nd, 5th, 10th, and 30th minutes and dynamic curve slope (SL) values and SL ratios were measured using 18F-FDG dynamic data. In addition, the values of SUVmean (2minSUVmean), SULpeak (2minSULpeak), metabolic volume (2minVol), and total lesion glycolysis (2minTLG) were measured for the first 2 min. Percent changes between baseline and interim studies were calculated and compared with the pathological results as the pathological complete response (PCR) or the pathological non-complete response (non-PCR). Receiver operating characteristic curves were obtained to calculate the area under the curve to predict PCR. Optimal threshold values were calculated to discriminate between PCR and non-PCR groups. Results Baseline study SUV 30 (p=0.044), SUV 30/2 (p=0.041), SUV 30/5 (p=0.049), SUV 30/10 (p=0.021), SL 30/2 (p=0.029) and SL 30/5 (p=0.027) values were statistically significant different between PCR and non-PCR groups. The percentage changes of 2minVol between PCR and non-PCR groups were statistically significant. For the threshold value of -67.6% change in 2minVol, the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 87.2%, 77.8%, 63.6%, 93.3%, and 80.7%, respectively (area under the curve: 0.826, p=0.009). Conclusion Semiquantitative parameters for dynamic 18F-FDG PET can predict PCR. % changes in 2minVol can identify non-responding patients better than other parameters.
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Affiliation(s)
- Osman Kupik
- Muğla Training and Research Hospital, Clinic of Nuclear Medicine, Muğla, Turkey
| | - Murat Tuncel
- Hacettepe University Faculty of Medicine, Department of Nuclear Medicine, Ankara Turkey
| | - Pınar Özgen Kıratlı
- Hacettepe University Faculty of Medicine, Department of Nuclear Medicine, Ankara Turkey
| | | | | | | | - Belkıs Erbaş
- Hacettepe University Faculty of Medicine, Department of Nuclear Medicine, Ankara Turkey
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Xu X, Sun X, Ma L, Zhang H, Ji W, Xia X, Lan X. 18F-FDG PET/CT radiomics signature and clinical parameters predict progression-free survival in breast cancer patients: A preliminary study. Front Oncol 2023; 13:1149791. [PMID: 36969043 PMCID: PMC10036789 DOI: 10.3389/fonc.2023.1149791] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Accepted: 02/20/2023] [Indexed: 03/12/2023] Open
Abstract
IntroductionThis study aimed to investigate the feasibility of predicting progression-free survival (PFS) in breast cancer patients using pretreatment 18F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) radiomics signature and clinical parameters.MethodsBreast cancer patients who underwent 18F-FDG PET/CT imaging before treatment from January 2012 to December 2020 were eligible for study inclusion. Eighty-seven patients were randomly divided into training (n = 61) and internal test sets (n = 26) and an additional 25 patients were used as the external validation set. Clinical parameters, including age, tumor size, molecularsubtype, clinical TNM stage, and laboratory findings were collected. Radiomics features were extracted from preoperative PET/CT images. Least absolute shrinkage and selection operators were applied to shrink feature size and build a predictive radiomics signature. Univariate and multivariate Cox proportional hazards models and Kaplan-Meier analysis were used to assess the association of rad-score and clinical parameter with PFS. Nomograms were constructed to visualize survival prediction. C-index and calibration curve were used to evaluate nomogram performance.ResultsEleven radiomics features were selected to generate rad-score. The clinical model comprised three parameters: clinical M stage, CA125, and pathological N stage. Rad-score and clinical-model were significantly associated with PFS in the training set (P< 0.01) but not the test set. The integrated clinical-radiomics (ICR) model was significantly associated with PFS in both the training and test sets (P< 0.01). The ICR model nomogram had a significantly higher C-index than the clinical model and rad-score in the training and test sets. The C-index of the ICR model in the external validation set was 0.754 (95% confidence interval, 0.726–0.812). PFS significantly differed between the low- and high-risk groups stratified by the nomogram (P = 0.009). The calibration curve indicated the ICR model provided the greatest clinical benefit.ConclusionThe ICR model, which combined clinical parameters and preoperative 18F-FDG PET/CT imaging, was able to independently predict PFS in breast cancer patients and was superior to the clinical model alone and rad-score alone.
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Affiliation(s)
- Xiaojun Xu
- Department of Nuclear Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China
- Key Laboratory of Biological Targeted Therapy of the Ministry of Education, Wuhan, China
| | - Xun Sun
- Department of Nuclear Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China
- Key Laboratory of Biological Targeted Therapy of the Ministry of Education, Wuhan, China
| | - Ling Ma
- He Kang Corporate Management (SH) Co. Ltd, Shanghai, China
| | - Huangqi Zhang
- Department of Radiology, Affiliated Taizhou Hospital of Wenzhou Medical University, Taizhou, Zhejiang, China
| | - Wenbin Ji
- Department of Radiology, Affiliated Taizhou Hospital of Wenzhou Medical University, Taizhou, Zhejiang, China
| | - Xiaotian Xia
- Department of Nuclear Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China
- Key Laboratory of Biological Targeted Therapy of the Ministry of Education, Wuhan, China
- *Correspondence: Xiaotian Xia, ; Xiaoli Lan,
| | - Xiaoli Lan
- Department of Nuclear Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China
- Key Laboratory of Biological Targeted Therapy of the Ministry of Education, Wuhan, China
- *Correspondence: Xiaotian Xia, ; Xiaoli Lan,
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de Mooij CM, Ploumen RAW, Nelemans PJ, Mottaghy FM, Smidt ML, van Nijnatten TJA. The influence of receptor expression and clinical subtypes on baseline [18F]FDG uptake in breast cancer: systematic review and meta-analysis. EJNMMI Res 2023; 13:5. [PMID: 36689007 PMCID: PMC9871105 DOI: 10.1186/s13550-023-00953-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 01/11/2023] [Indexed: 01/24/2023] Open
Abstract
BACKGROUND To quantify the relationship between [18F]FDG uptake of the primary tumour measured by PET-imaging with immunohistochemical (IHC) expression of ER, PR, HER2, Ki-67, and clinical subtypes based on these markers in breast cancer patients. METHODS PubMed and Embase were searched for studies that compared SUVmax between breast cancer patients negative and positive for IHC expression of ER, PR, HER2, Ki-67, and clinical subtypes based on these markers. Two reviewers independently screened the studies and extracted the data. Standardized mean differences (SMD) and 95% confidence intervals (CIs) were estimated by using DerSimonian-Laird random-effects models. P values less than or equal to 5% indicated statistically significant results. RESULTS Fifty studies were included in the final analysis. SUVmax is significantly higher in ER-negative (31 studies, SMD 0.66, 0.56-0.77, P < 0.0001), PR-negative (30 studies, SMD 0.56; 0.40-0.71, P < 0.0001), HER2-positive (32 studies, SMD - 0.29, - 0.49 to - 0.10, P = 0.0043) or Ki-67-positive (19 studies, SMD - 0.77; - 0.93 to - 0.61, P < 0.0001) primary tumours compared to their counterparts. The majority of clinical subtypes were either luminal A (LA), luminal B (LB), HER2-positive or triple negative breast cancer (TNBC). LA is associated with significantly lower SUVmax compared to LB (11 studies, SMD - 0.49, - 0.68 to - 0.31, P = 0.0001), HER2-positive (15 studies, SMD - 0.91, - 1.21 to - 0.61, P < 0.0001) and TNBC (17 studies, SMD - 1.21, - 1.57 to - 0.85, P < 0.0001); and LB showed significantly lower uptake compared to TNBC (10 studies, SMD - 0.77, - 1.05 to - 0.49, P = 0.0002). Differences in SUVmax between LB and HER2-positive (9 studies, SMD - 0.32, - 0.88 to 0.24, P = 0.2244), and HER2-positive and TNBC (17 studies, SMD - 0.29, - 0.61 to 0.02, P = 0.0667) are not significant. CONCLUSION Primary tumour SUVmax is significantly higher in ER-negative, PR-negative, HER2-positive and Ki-67-positive breast cancer patients. Luminal tumours have the lowest and TNBC tumours the highest SUVmax. HER2 overexpression has an intermediate effect.
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Affiliation(s)
- Cornelis M de Mooij
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Centre+, P.O. Box 5800, 6202 AZ, Maastricht, The Netherlands.
- Department of Surgery, Maastricht University Medical Centre+, Maastricht, The Netherlands.
- GROW - School for Oncology and Reproduction, Maastricht University Medical Centre+, Maastricht, The Netherlands.
| | - Roxanne A W Ploumen
- Department of Surgery, Maastricht University Medical Centre+, Maastricht, The Netherlands
- GROW - School for Oncology and Reproduction, Maastricht University Medical Centre+, Maastricht, The Netherlands
| | - Patty J Nelemans
- Department of Epidemiology, Maastricht University Medical Centre+, Maastricht, The Netherlands
| | - Felix M Mottaghy
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Centre+, P.O. Box 5800, 6202 AZ, Maastricht, The Netherlands
- GROW - School for Oncology and Reproduction, Maastricht University Medical Centre+, Maastricht, The Netherlands
- Department of Nuclear Medicine, University Hospital RWTH Aachen University, Aachen, Germany
| | - Marjolein L Smidt
- Department of Surgery, Maastricht University Medical Centre+, Maastricht, The Netherlands
- GROW - School for Oncology and Reproduction, Maastricht University Medical Centre+, Maastricht, The Netherlands
| | - Thiemo J A van Nijnatten
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Centre+, P.O. Box 5800, 6202 AZ, Maastricht, The Netherlands
- GROW - School for Oncology and Reproduction, Maastricht University Medical Centre+, Maastricht, The Netherlands
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Morland D, Triumbari EKA, Boldrini L, Gatta R, Pizzuto D, Annunziata S. Radiomics in Oncological PET Imaging: A Systematic Review—Part 1, Supradiaphragmatic Cancers. Diagnostics (Basel) 2022; 12:diagnostics12061329. [PMID: 35741138 PMCID: PMC9221970 DOI: 10.3390/diagnostics12061329] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 05/25/2022] [Accepted: 05/26/2022] [Indexed: 12/10/2022] Open
Abstract
Radiomics is an upcoming field in nuclear oncology, both promising and technically challenging. To summarize the already undertaken work on supradiaphragmatic neoplasia and assess its quality, we performed a literature search in the PubMed database up to 18 February 2022. Inclusion criteria were: studies based on human data; at least one specified tumor type; supradiaphragmatic malignancy; performing radiomics on PET imaging. Exclusion criteria were: studies only based on phantom or animal data; technical articles without a clinically oriented question; fewer than 30 patients in the training cohort. A review database containing PMID, year of publication, cancer type, and quality criteria (number of patients, retrospective or prospective nature, independent validation cohort) was constructed. A total of 220 studies met the inclusion criteria. Among them, 119 (54.1%) studies included more than 100 patients, 21 studies (9.5%) were based on prospectively acquired data, and 91 (41.4%) used an independent validation set. Most studies focused on prognostic and treatment response objectives. Because the textural parameters and methods employed are very different from one article to another, it is complicated to aggregate and compare articles. New contributions and radiomics guidelines tend to help improving quality of the reported studies over the years.
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Affiliation(s)
- David Morland
- Nuclear Medicine Unit, TracerGLab, Department of Radiology, Radiotherapy and Hematology, Fondazione Policlinico Universitario A. Gemelli, IRCCS, 00168 Rome, Italy; (E.K.A.T.); (D.P.); (S.A.)
- Service de Médecine Nucléaire, Institut Godinot, 51100 Reims, France
- Laboratoire de Biophysique, UFR de Médecine, Université de Reims Champagne-Ardenne, 51100 Reims, France
- CReSTIC (Centre de Recherche en Sciences et Technologies de l’Information et de la Communication), EA 3804, Université de Reims Champagne-Ardenne, 51100 Reims, France
- Correspondence:
| | - Elizabeth Katherine Anna Triumbari
- Nuclear Medicine Unit, TracerGLab, Department of Radiology, Radiotherapy and Hematology, Fondazione Policlinico Universitario A. Gemelli, IRCCS, 00168 Rome, Italy; (E.K.A.T.); (D.P.); (S.A.)
| | - Luca Boldrini
- Radiotherapy Unit, Radiomics, Department of Radiology, Radiotherapy and Hematology, Fondazione Policlinico Universitario A. Gemelli, IRCCS, 00168 Rome, Italy; (L.B.); (R.G.)
| | - Roberto Gatta
- Radiotherapy Unit, Radiomics, Department of Radiology, Radiotherapy and Hematology, Fondazione Policlinico Universitario A. Gemelli, IRCCS, 00168 Rome, Italy; (L.B.); (R.G.)
- Department of Clinical and Experimental Sciences, University of Brescia, 25121 Brescia, Italy
- Department of Oncology, Lausanne University Hospital, 1011 Lausanne, Switzerland
| | - Daniele Pizzuto
- Nuclear Medicine Unit, TracerGLab, Department of Radiology, Radiotherapy and Hematology, Fondazione Policlinico Universitario A. Gemelli, IRCCS, 00168 Rome, Italy; (E.K.A.T.); (D.P.); (S.A.)
| | - Salvatore Annunziata
- Nuclear Medicine Unit, TracerGLab, Department of Radiology, Radiotherapy and Hematology, Fondazione Policlinico Universitario A. Gemelli, IRCCS, 00168 Rome, Italy; (E.K.A.T.); (D.P.); (S.A.)
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Maiborodin I, Mansurova A, Chernyavskiy A, Romanov A, Voitcitctkii V, Kedrova A, Tarkhov A, Chernyshova A, Krasil’nikov S. Cancer Angiogenesis and Opportunity of Influence on Tumor by Changing Vascularization. J Pers Med 2022; 12:jpm12030327. [PMID: 35330327 PMCID: PMC8954734 DOI: 10.3390/jpm12030327] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Revised: 02/18/2022] [Accepted: 02/18/2022] [Indexed: 12/19/2022] Open
Abstract
Based on the study of recent scientific literature devoted to neovascularization and angiogenesis in malignant neoplasms, it was concluded that there are many publications on each of the problems of tumor angiogenesis and vascularization. The formation of blood vessels in a tumor and certain aspects of the prognostic value of the severity of vascularization in almost all forms of cancer are considered. Special attention is paid to the peculiarities of angiogenesis in tumors of the female reproductive system. A large number of vessels in the tumor often indicates a poor prognosis. The influence of various factors on the initiation of angiogenesis and the process itself, as well as the possibility of suppressing such signals to slow down the formation of blood vessels and thus the development of the tumor are widely studied. The results of pharmacological suppression of tumor vessel formation demonstrate a good clinical outcome but one accompanied by a large number of severe adverse side effects. Such a significant amount of studies on each of the problems of tumor vascularization indicates the increasing importance of this area of oncology. At the same time, only a very small number of works are devoted to the study of the differences in angiogenesis and number of vessels between different parts of the tumor, as well as between the primary tumor node and its metastases. The refinement of the results is still to be done. It was noted that the expression of proangiogenic factors in metastases is usually higher than in the source of metastasis, and the expression in lymphogenous metastases is higher than in hematogenous ones.
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Affiliation(s)
- Igor Maiborodin
- The E. Meshalkin National Medical Research Center, Ministry of Health of Russia, 30055 Novosibirsk, Russia; (A.M.); (A.C.); (A.R.); (V.V.); (A.K.); (A.T.); (S.K.)
- Correspondence:
| | - Alfija Mansurova
- The E. Meshalkin National Medical Research Center, Ministry of Health of Russia, 30055 Novosibirsk, Russia; (A.M.); (A.C.); (A.R.); (V.V.); (A.K.); (A.T.); (S.K.)
| | - Alexander Chernyavskiy
- The E. Meshalkin National Medical Research Center, Ministry of Health of Russia, 30055 Novosibirsk, Russia; (A.M.); (A.C.); (A.R.); (V.V.); (A.K.); (A.T.); (S.K.)
| | - Alexander Romanov
- The E. Meshalkin National Medical Research Center, Ministry of Health of Russia, 30055 Novosibirsk, Russia; (A.M.); (A.C.); (A.R.); (V.V.); (A.K.); (A.T.); (S.K.)
| | - Vladimir Voitcitctkii
- The E. Meshalkin National Medical Research Center, Ministry of Health of Russia, 30055 Novosibirsk, Russia; (A.M.); (A.C.); (A.R.); (V.V.); (A.K.); (A.T.); (S.K.)
| | - Anna Kedrova
- The E. Meshalkin National Medical Research Center, Ministry of Health of Russia, 30055 Novosibirsk, Russia; (A.M.); (A.C.); (A.R.); (V.V.); (A.K.); (A.T.); (S.K.)
| | - Alexander Tarkhov
- The E. Meshalkin National Medical Research Center, Ministry of Health of Russia, 30055 Novosibirsk, Russia; (A.M.); (A.C.); (A.R.); (V.V.); (A.K.); (A.T.); (S.K.)
| | - Alena Chernyshova
- Tomsk National Research Medical Center, Cancer Research Institute, Russian Academy of Sciences, 634009 Tomsk, Russia;
| | - Sergey Krasil’nikov
- The E. Meshalkin National Medical Research Center, Ministry of Health of Russia, 30055 Novosibirsk, Russia; (A.M.); (A.C.); (A.R.); (V.V.); (A.K.); (A.T.); (S.K.)
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Abstract
Integration of ecological and evolutionary features has begun to understand the interplay of tumor heterogeneity, microenvironment, and metastatic potential. Developing a theoretical framework is intrinsic to deciphering tumors' tremendous spatial and longitudinal genetic variation patterns in patients. Here, we propose that tumors can be considered evolutionary island-like ecosystems, that is, isolated systems that undergo evolutionary and spatiotemporal dynamic processes that shape tumor microenvironments and drive the migration of cancer cells. We examine attributes of insular systems and causes of insularity, such as physical distance and connectivity. These properties modulate migration rates of cancer cells through processes causing spatial and temporal isolation of the organs and tissues functioning as a supply of cancer cells for new colonizations. We discuss hypotheses, predictions, and limitations of tumors as islands analogy. We present emerging evidence of tumor insularity in different cancer types and discuss their relevance to the islands model. We suggest that the engagement of tumor insularity into conceptual and mathematical models holds promise to illuminate cancer evolution, tumor heterogeneity, and metastatic potential of cells.
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Affiliation(s)
- Antonia Chroni
- Institute for Genomics and Evolutionary Medicine, Temple University, USA
- Department of Biology, Temple University, USA
| | - Sudhir Kumar
- Institute for Genomics and Evolutionary Medicine, Temple University, USA
- Department of Biology, Temple University, USA
- Center for Excellence in Genomic Medicine Research, King Abdulaziz University, Jeddah, Saudi Arabia
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Ma NQ, Lv HY, Bi J, Yu FX, Huang XM. Scoring system for gallbladder polyps based on the cross-sectional area and patient characteristics. Asian J Surg 2021; 45:332-338. [PMID: 34147329 DOI: 10.1016/j.asjsur.2021.05.048] [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: 01/27/2021] [Revised: 05/14/2021] [Accepted: 05/31/2021] [Indexed: 11/02/2022] Open
Abstract
BACKGROUND Current management guidelines for gallbladder polyps (GBPs) focus on a diameter more than 1 cm as an indication for cholecystectomy. Since most GBPs are not malignant, unnecessary cholecystectomies can lead to unnecessary complications and costs. We developed a score to identify true polyps focusing on their cross-sectional area (CSA). METHODS We retrospectively analyzed the demographic, clinical, laboratory, and sonographic characteristics of 522 patients with GBPs who had undergone cholecystectomy at our hospital between January 2010 and July 2020 (reference group). We used univariate analysis to compare these parameters between 88 true polyps and 434 pseudopolyps and multivariate logistic regression analysis to identify parameters to include in our scoring model. Receiver operating characteristics and area under the curve were used to identify cut-off values. The model was tested on a validation group of 98 patients. RESULTS In the multivariate analysis, a CSA >123 mm2, positive blood flow signal, age >55.5 years, alanine aminotransferase (ALT) levels > 50 U/L, and an ALT/aspartate aminotransferase ratio > 0.77 were significantly associated with true polyps (odds ratio 6.528, 2.377, 2.617, 2.445, and -0.372, respectively). A prediction model based on cut-off values was used to distinguish a low-risk and high-risk GBP group; true polyps accounted for 6.54% and 58.72%, respectively (p < 0.001). In the low-risk and high-risk validation groups, true polyps comprised 12.35% and 82.35%, respectively (p < 0.001). CONCLUSIONS Our scoring system shows high accuracy and specificity in identifying true polyps and helps determine the need for surgical resection.
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Affiliation(s)
- Nai-Qing Ma
- Department of Hepatological Surgery, The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Hao-Yang Lv
- Department of Hepatological Surgery, The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Jiayang Bi
- Department of Hepatological Surgery, The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Fu-Xiang Yu
- Department of Hepatological Surgery, The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China.
| | - Xia-Ming Huang
- Department of Hepatological Surgery, The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China.
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Xie Y, Zhao J, Zhang P. A multicompartment model for intratumor tissue-specific analysis of DCE-MRI using non-negative matrix factorization. Med Phys 2021; 48:2400-2411. [PMID: 33608885 DOI: 10.1002/mp.14793] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Revised: 12/22/2020] [Accepted: 01/29/2021] [Indexed: 11/12/2022] Open
Abstract
PURPOSE A pharmacokinetic analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data is subject to inaccuracy and instability partly owing to the partial volume effect (PVE). We proposed a new multicompartment model for a tissue-specific pharmacokinetic analysis in DCE-MRI data to solve the PVE problem and to provide better kinetic parameter maps. METHODS We introduced an independent parameter named fractional volumes of tissue compartments in each DCE-MRI pixel to construct a new linear separable multicompartment model, which simultaneously estimates the pixel-wise time-concentration curves and fractional volumes without the need of the pure-pixel assumption. This simplified convex optimization model was solved using a special type of non-negative matrix factorization (NMF) algorithm called the minimum-volume constraint NMF (MVC-NMF). RESULTS To test the model, synthetic datasets were established based on the general pharmacokinetic parameters. On well-designed synthetic data, the proposed model reached lower bias and lower root mean square fitting error compared to the state-of-the-art algorithm in different noise levels. In addition, the real dataset from QIN-BREAST-DCE-MRI was analyzed, and we observed an improved pharmacokinetic parameter estimation to distinguish the treatment response to chemotherapy applied to breast cancer. CONCLUSION Our model improved the accuracy and stability of the tissue-specific estimation of the fractional volumes and kinetic parameters in DCE-MRI data, and improved the robustness to noise, providing more accurate kinetics for more precise prognosis and therapeutic response evaluation using DCE-MRI.
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Affiliation(s)
- Yuhai Xie
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Jun Zhao
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Puming Zhang
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
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A Systematic Review of PET Textural Analysis and Radiomics in Cancer. Diagnostics (Basel) 2021; 11:diagnostics11020380. [PMID: 33672285 PMCID: PMC7926413 DOI: 10.3390/diagnostics11020380] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Revised: 02/10/2021] [Accepted: 02/19/2021] [Indexed: 12/12/2022] Open
Abstract
Background: Although many works have supported the utility of PET radiomics, several authors have raised concerns over the robustness and replicability of the results. This study aimed to perform a systematic review on the topic of PET radiomics and the used methodologies. Methods: PubMed was searched up to 15 October 2020. Original research articles based on human data specifying at least one tumor type and PET image were included, excluding those that apply only first-order statistics and those including fewer than 20 patients. Each publication, cancer type, objective and several methodological parameters (number of patients and features, validation approach, among other things) were extracted. Results: A total of 290 studies were included. Lung (28%) and head and neck (24%) were the most studied cancers. The most common objective was prognosis/treatment response (46%), followed by diagnosis/staging (21%), tumor characterization (18%) and technical evaluations (15%). The average number of patients included was 114 (median = 71; range 20–1419), and the average number of high-order features calculated per study was 31 (median = 26, range 1–286). Conclusions: PET radiomics is a promising field, but the number of patients in most publications is insufficient, and very few papers perform in-depth validations. The role of standardization initiatives will be crucial in the upcoming years.
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Johnson GB, Harms HJ, Johnson DR, Jacobson MS. PET Imaging of Tumor Perfusion: A Potential Cancer Biomarker? Semin Nucl Med 2020; 50:549-561. [PMID: 33059824 DOI: 10.1053/j.semnuclmed.2020.07.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Perfusion, as measured by imaging, is considered a standard of care biomarker for the evaluation of many tumors. Measurements of tumor perfusion may be used in a number of ways, including improving the visual detection of lesions, differentiating malignant from benign findings, assessing aggressiveness of tumors, identifying ischemia and by extension hypoxia within tumors, and assessing treatment response. While most clinical perfusion imaging is currently performed with CT or MR, a number of methods for PET imaging of tumor perfusion have been described. The inert PET radiotracer 15O-water PET represents the recognized gold standard for absolute quantification of tissue perfusion in both normal tissue and a variety of pathological conditions including cancer. Other cancer PET perfusion imaging strategies include the use of radiotracers with high first-pass uptake, analogous to those used in cardiac perfusion PET. This strategy produces more visually pleasing high-contrast images that provide relative rather than absolute perfusion quantification. Lastly, multiple timepoint imaging of PET tracers such as 18F-FDG, are not specifically optimized for perfusion, but have advantages related to availability, convenience, and reimbursement. Multiple obstacles have thus far blocked the routine use of PET imaging for tumor perfusion, including tracer production and distribution, image processing, patient body coverage, clinical validation, regulatory approval and reimbursement, and finally feasible clinical workflows. Fortunately, these obstacles are being overcome, especially within larger imaging centers, opening the door for PET imaging of tumor perfusion to become standard clinical practice. In the foreseeable future, it is possible that whole-body PET perfusion imaging with 15O-water will be able to be performed in a single imaging session concurrent with standard PET imaging techniques such as 18F-FDG-PET. This approach could establish an efficient clinical workflow. The resultant ability to measure absolute tumor blood flow in combination with glycolysis will provide important complementary information to inform prognosis and clinical decisions.
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Affiliation(s)
- Geoffrey B Johnson
- Department of Radiology, Mayo Clinic, Rochester, MNDepartment of Neurology, Mayo Clinic, Rochester, MN; Department of Immunology, Mayo Clinic, Rochester, MN.
| | - Hendrik J Harms
- Department of Surgical Sciences, Nuclear Medicine, PET and Radiology, Uppsala University, Uppsala Sweden
| | - Derek R Johnson
- Department of Radiology, Mayo Clinic, Rochester, MNDepartment of Neurology, Mayo Clinic, Rochester, MN
| | - Mark S Jacobson
- Department of Radiology, Mayo Clinic, Rochester, MNDepartment of Neurology, Mayo Clinic, Rochester, MN
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Liu XS, Yuan LL, Gao Y, Zhou LM, Yang JW, Pei ZJ. Overexpression of METTL3 associated with the metabolic status on 18F-FDG PET/CT in patients with Esophageal Carcinoma. J Cancer 2020; 11:4851-4860. [PMID: 32626532 PMCID: PMC7330681 DOI: 10.7150/jca.44754] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Accepted: 05/27/2020] [Indexed: 02/07/2023] Open
Abstract
Background: To investigate the expression of methyltransferase 3 (METTL3) and its relationship with 18F-FDG uptake in patients with esophageal carcinoma (ESCA). Materials and methods: This study analyzed the expression of METTL3 in ESCA and its relationship with clinicopathological features by The Cancer Genome Atlas (TCGA) database. Immunohistochemical staining was performed on 57 tumor tissues of ESCA patients who underwent PET/CT scan before surgery to evaluate the expression of METTL3, glucose transporter 1 (GLUT1), and hexokinase 2 (HK2) in tumor tissues and peritumoral tissues. Analyze the relationship between SUVmax with METTL3, HK2, and GLUT1 expression. Results: The expression of METTL3, GLUT1, and HK2 was significantly increased in ESCA tissues compared with normal tissues (p < 0.001). The expression of METTL3 was correlated with tumor size and histological differentiation (p < 0.05), and there was no significant difference between age, sex, pathological types, tumor staging, or lymph node metastasis (p > 0.05). The SUVmax was significantly higher in tumors with high METTL3 expression (17.822±6.249) compared to low METTL3 expression (9.573±5.082) (p < 0.001). There was a positive correlation between the SUVmax and METTL3 expression in ESCA (r2 = 0.647, p < 0.001). Multivariate analysis confirmed the association between SUVmax and METTL3 expression (p < 0.05). GLUT1 and HK2 expression in ESCA was positively correlated with 18F-FDG uptake and METTL3 status (p < 0.001). Conclusions: The high expression of METTL3 is related to the high SUVmax in ESCA, and METTL3 may increase 18F-FDG uptake by regulating GLUT1 and HK2.
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Affiliation(s)
- Xu-Sheng Liu
- Department of Nuclear Medicine and Institute of Anesthesiology and Pain, Taihe Hospital, Hubei University of Medicine, Shiyan, 44200, China
| | - Ling-Ling Yuan
- Department of Pathology, Taihe Hospital, Hubei University of Medicine, Shiyan, 442000, China
| | - Yan Gao
- Department of Nuclear Medicine and Institute of Anesthesiology and Pain, Taihe Hospital, Hubei University of Medicine, Shiyan, 44200, China
| | - Lu-Meng Zhou
- Department of Nuclear Medicine and Institute of Anesthesiology and Pain, Taihe Hospital, Hubei University of Medicine, Shiyan, 44200, China
| | - Jian-Wei Yang
- Department of Nuclear Medicine and Institute of Anesthesiology and Pain, Taihe Hospital, Hubei University of Medicine, Shiyan, 44200, China
| | - Zhi-Jun Pei
- Department of Nuclear Medicine and Institute of Anesthesiology and Pain, Taihe Hospital, Hubei University of Medicine, Shiyan, 44200, China.,Hubei Key Laboratory of WudangLocal Chinese Medicine Research, Shiyan, 442000, China.,Hubei Key Laboratory of Embryonic Stem Cell Research, Shiyan, 442000, China
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