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Treatment Monitoring by ¹⁸F-FDG PET/CT in Patients with Sarcomas: Interobserver Variability of Quantitative Parameters in Treatment-Induced Changes in Histopathologically Responding and Nonresponding Tumors

¹ Ahmanson Biological Imaging Division, Department of Molecular and Medical Pharmacology, University of California at Los Angeles, Los Angeles, California; ² Division of Surgical Oncology, Department of Surgery, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, California; and ³ Abteilung Nuklearmedizin, University of Freiburg, Freiburg, Germany

View larger version (37K): [in this window] [in a new window]   FIGURE 1.  ROI approach used for detecting SUVmax and SUVpeak within tumor (left thigh) and mean activity concentration in contralateral background region (right thigh). (A) Loosely fitting ROIs were placed manually around entire tumor on every axial image plane in which tumor tissue was visualized by abnormal 18F-FDG accumulation (arrow 1). (B) All ROIs were placed on multiple axial slices. Each ROI placed on axial images is represented by horizontal line. Within this set of ROIs, computer automatically identified SUVmax. To obtain SUVpeak, 15-mm ROI was manually placed around SUVmax (arrow 2). Then circular ROI was drawn in contralateral normal soft tissue on coronal PET/CT images to determine SUV of background region (arrow 3).

View larger version (79K): [in this window] [in a new window]   FIGURE 2.  (A) Dedifferentiated liposarcoma located in right lower abdomen (arrows). (B) For placement of ROI, 50% isocontour thresholding approach was used. (C) ROI from B was manually adjusted to better fit hypermetabolic region. (D) Tumor in coronal views. To ascertain identical ROI placement in baseline and follow-up studies, 2 CT images were fused (E). Baseline images in D are displayed in gray scale, whereas follow-up images are color-scaled. (F) ROI placement used in follow-up was identical to that used in baseline scan in C.

View larger version (15K): [in this window] [in a new window]   FIGURE 3.  Changes in tumor SUVmax, SUVpeak, and SUVmean are stratified for responders and nonresponders as defined by histopathology. Each data point represents mean of measurements of 2 observers.

View larger version (13K): [in this window] [in a new window]   FIGURE 4.  Bland–Altman plots exemplifying that differences between observers 1 and 2 were smaller for changes in SUVpeak (A) than for changes in SUVmean (B) and in TBR (C).

View larger version (9K): [in this window] [in a new window]   FIGURE 5.  VEC combining interobserver variability and ability to differentiate between treatment responders and nonresponders. High coefficient signifies robust and valid data. VEC was higher for changes in SUV than for absolute SUVs or TBR. Changes in parameters rather than their absolute values are preferable for assessing effectiveness of therapy.

View larger version (33K): [in this window] [in a new window]   FIGURE 6.  Images depicting treated, histopathologically responding malignant peripheral nerve sheath tumor located in right gluteal area. (A) Tumor on axial CT soft-tissue window (arrow 1). (B) ROI placement using 50% isocontour thresholding approach. This automatically defined contour includes tumor (arrow 1) and large area of normal tissues (bone marrow, arrow 2; bladder, arrow 3).