Response Analysis of Non-Hodgkin Lymphoma Using Magnetic Resonance Imaging-Based Volumes

Objective: The aim of this study was to determine the volume of non-Hodgkin lymphomas (NHLs) using semiautomatic segmentation and to correlate these results with clinical findings, treatment, and prognosis in patients with B-cell-type NHL. Methods: For this study, 29 patients with NHL underwent magnetic resonance imaging at 5 time points after onset of disease. Volumetric analysis of the tumors was accomplished with semiautomatic segmentation by the Anatomatic software. Results: The median tumor volumes from the first to the fifth examination were 468, 256, 90, 38, and 33 cm3. Good correlation with 1-dimensional and 2-dimensional measures, used as standard methods in response categorization, was found. Surprisingly, volume reductions in excess of 239 cm3 after only 1 week of chemotherapy decreased the survival probability. Conclusions: Volume measurements seem to be highly informative for prognosis in the very early stages of treatment for patients with NHL.

[1]  R. Reznek,et al.  CT assessment of tumour response to treatment: comparison of linear, cross-sectional and volumetric measures of tumour size. , 2000, The British journal of radiology.

[2]  Stephen J. Wigmore,et al.  Liver Volumetry Plug and Play: Do It Yourself with ImageJ , 2007, World Journal of Surgery.

[3]  M. van Glabbeke,et al.  New guidelines to evaluate the response to treatment in solid tumors , 2000, Journal of the National Cancer Institute.

[4]  E. Ozyar,et al.  Waldeyer’s Ring Lymphomas: Treatment Results and Prognostic Factors , 2003, American journal of clinical oncology.

[5]  L. Shulman,et al.  Mediastinal Large Cell Lymphoma: Prognostic Significance ofCT Findings at Presentation and after Treatment , 1998, Oncology.

[6]  G. Lucignani.  How early? ASAP: molecular and functional imaging! , 2007, European Journal of Nuclear Medicine and Molecular Imaging.

[7]  Vergleich uni- und bidimensionaler Messverfahren zur Beurteilung des Therapieansprechens bei der Behandlung solider Tumoren , 2007, Der Radiologe.

[8]  R. Hicks,et al.  Overview of early response assessment in lymphoma with FDG-PET , 2007, Cancer imaging : the official publication of the International Cancer Imaging Society.

[9]  J. Malmivuo,et al.  Semi-automatic tool for segmentation and volumetric analysis of medical images , 1998, Medical and Biological Engineering and Computing.

[10]  P Dastidar,et al.  Applicability of semi-automatic segmentation for volumetric analysis of brain lesions. , 1998, Journal of medical engineering & technology.

[11]  E. Halpern,et al.  CT tumor measurement for therapeutic response assessment: comparison of unidimensional, bidimensional, and volumetric techniques initial observations. , 2002, Radiology.

[12]  Maximilien Vermandel,et al.  Automatic segmentation of pelvic structures from magnetic resonance images for prostate cancer radiotherapy. , 2007, International journal of radiation oncology, biology, physics.

[13]  E. McFadden,et al.  Toxicity and response criteria of the Eastern Cooperative Oncology Group , 1982, American journal of clinical oncology.

[14]  M Van Glabbeke,et al.  New guidelines to evaluate the response to treatment in solid tumors. European Organization for Research and Treatment of Cancer, National Cancer Institute of the United States, National Cancer Institute of Canada. , 2000, Journal of the National Cancer Institute.

[15]  S. Siegel,et al.  Nonparametric Statistics for the Behavioral Sciences , 2022, The SAGE Encyclopedia of Research Design.

[16]  R. Velthuizen,et al.  Technical aspects and evaluation methodology for the application of two automated brain MRI tumor segmentation methods in radiation therapy planning. , 2006, Magnetic resonance imaging.

[17]  E. Eisenhauer,et al.  RECIST revisited: a review of validation studies on tumour assessment. , 2006, European journal of cancer.

[18]  Bram van Ginneken,et al.  Supervised Probabilistic Segmentation of Pulmonary Nodules in CT Scans , 2006, MICCAI.

[19]  H. B. Mann,et al.  On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other , 1947 .

[20]  S. Tucker,et al.  Central lymphatic irradiation for stage I-III follicular lymphoma: report from a single-institutional prospective study. , 2001, International journal of radiation oncology, biology, physics.

[21]  Lawrence H Schwartz,et al.  A statistical simulation study finds discordance between WHO criteria and RECIST guideline. , 2004, Journal of clinical epidemiology.

[22]  R. Velthuizen,et al.  Brain tumor target volume determination for radiation treatment planning through automated MRI segmentation. , 2004, International journal of radiation oncology, biology, physics.

[23]  R. Tsang,et al.  Low-grade non-hodgkin lymphomas. , 2007, Seminars in radiation oncology.

[24]  A. Miller,et al.  Reporting results of cancer treatment , 1981, Cancer.

[25]  H. Kauczor,et al.  [Follow-up CT measurement of liver malignoma according to RECIST and WHO vs. volumetry]. , 2007, RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin.

[26]  M Werner-Wasik,et al.  Assessment of lung cancer response after nonoperative therapy: tumor diameter, bidimensional product, and volume. A serial CT scan-based study. , 2001, International journal of radiation oncology, biology, physics.

[27]  L. Specht.  2-[18F]fluoro-2-deoxyglucose positron-emission tomography in staging, response evaluation, and treatment planning of lymphomas. , 2007, Seminars in radiation oncology.

[28]  A. Ng,et al.  Diffuse large B-cell lymphoma. , 2007, Seminars in radiation oncology.

[29]  M Schwaiger,et al.  Positron emission tomography in non-Hodgkin's lymphoma: assessment of chemotherapy with fluorodeoxyglucose. , 1998, Blood.

[30]  P. Gobbi,et al.  Image-aided estimate of tumor burden in Hodgkin's disease: evidence of its primary prognostic importance. , 2001, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[31]  E. Hauth,et al.  [Comparison of unidimensional and bidimensional measurement to assess therapeutic response in the treatment of solid tumors]. , 2007, Der Radiologe.

[32]  S. Skates,et al.  Three-dimensional volumetric assessment of response to treatment: stage I and II diffuse large cell lymphoma of the mediastinum. , 1988, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[33]  M van Herk,et al.  Definition of the prostate in CT and MRI: a multi-observer study. , 1999, International journal of radiation oncology, biology, physics.

[34]  K. Foon,et al.  The expanding role of rituximab and radioimmunotherapy in the treatment of B-cell lymphomas , 2007, Expert opinion on biological therapy.

[35]  S. Tucker,et al.  Stage III follicular lymphoma: long-term follow-up and patterns of failure. , 2003, International journal of radiation oncology, biology, physics.

[36]  M. Rodríguez.  Computed tomography, magnetic resonance imaging and positron emission tomography in non-Hodgkin's lymphoma. , 1998, Acta radiologica. Supplementum.

[37]  J. Leonard,et al.  FDG‐PET after 1 cycle of therapy predicts outcome in diffuse large cell lymphoma and classic Hodgkin disease , 2006, Cancer.

[38]  L. Specht.  Tumour burden as the main indicator of prognosis in Hodgkin's disease. , 1992, European journal of cancer.