Selective internal radiation therapy (SIRT) before partial hepatectomy or radiofrequency destruction for treatment of hepatocellular carcinoma in cirrhotic patients: a feasibility and safety pilot study.

BACKGROUND/PURPOSE: Preoperative selective internal radiation therapy (SIRT) may improve the results of partial hepatectomy (PH) or radiofrequency destruction (RF) for hepatocellular carcinoma (HCC) in patients with cirrhosis. The aim of this study was to evaluate the feasibility and safety of this combined approach. METHODS: Patients with cirrhosis and HCC selected for PH or RF were prospectively included and systematically proposed for preoperative SIRT. Feasibility and safety of SIRT and post-SIRT PH or RF were assessed. RESULTS: Thirty patients were included. SIRT was contraindicated in seven, due to lack of access to tumour artery or to hepato-pulmonary shunts. SIRT was performed in 23 patients without significant complications. Post-SIRT, surgery was refuted in seven patients, due to tumour progression or the patient's deteriorating condition. After surgery, major complications were observed in 2/16 patients (12.5%) and one patient died 52 days post-surgery. A major tumour pathological response was seen in most patients who underwent surgery after SIRT. CONCLUSIONS: On intention-to-treat basis, the overall feasibility of combining preoperative SIRT and surgery was limited. Preoperative SIRT did not increase expected operative morbidity, but post-SIRT, a third of patients were refuted for surgery. Accurate selection criteria and potential long-term oncological benefit of this approach remains to be determined. ClinicalTrials.gov NCT01686880.

Comparison of PET metabolic indices for the early assessment of tumour response in metastatic colorectal cancer patients treated by polychemotherapy.

PURPOSE: To compare the performance of eight metabolic indices for the early assessment of tumour response in patients with metastatic colorectal cancer (mCRC) treated with chemotherapy. METHODS: Forty patients with advanced mCRC underwent two FDG PET/CT scans, at baseline and on day 14 after chemotherapy initiation. For each lesion, eight metabolic indices were calculated: four standardized uptake values (SUV) without correction for the partial volume effect (PVE), two SUV with correction for PVE, a metabolic volume (MV) and a total lesion glycolysis (TLG). The relative change in each index between the two scans was calculated for each lesion. Lesions were also classified as responding and nonresponding lesions using the Response Evaluation Criteria In Solid Tumours (RECIST) 1.0 measured by contrast-enhanced CT at baseline and 6-8 weeks after starting therapy. Bland-Altman analyses were performed to compare the various indices. Based on the RECIST classification, ROC analyses were used to determine how accurately the indices predicted lesion response to therapy later seen with RECIST. RESULTS: RECIST showed 27 responding and 74 nonresponding lesions. Bland-Altman analyses showed that the four SUV indices uncorrected for PVE could not be used interchangeably, nor could the two SUV corrected for PVE. The areas under the ROC curves (AUC) were not significantly different between the SUV indices not corrected for PVE. The mean SUV change in a lesion better predicted lesion response without than with PVE correction. The AUC was significantly higher for SUV uncorrected for PVE than for the MV, but change in MV provided some information regarding the lesion response to therapy (AUC >0.5). CONCLUSION: In these mCRC patients, all SUV uncorrected for PVE accurately predicted the tumour response on day 14 after starting therapy as assessed 4 to 6 weeks later (i.e. 6 to 8 weeks after therapy initiation) using the RECIST criteria. Neither correcting SUV for PVE nor measuring TLG improved the assessment of tumour response compared to SUV uncorrected for PVE. The change in MV was the least accurate index for predicting tumour response.

Tumor texture analysis in 18F-FDG PET: relationships between texture parameters, histogram indices, standardized uptake values, metabolic volumes, and total lesion glycolysis.

UNLABELLED: Texture indices are of growing interest for tumor characterization in (18)F-FDG PET. Yet, on the basis of results published in the literature so far, it is unclear which indices should be used, what they represent, and how they relate to conventional indices such as standardized uptake values (SUVs), metabolic volume (MV), and total lesion glycolysis (TLG). We investigated in detail 31 texture indices, 5 first-order statistics (histogram indices) derived from the gray-level histogram of the tumor region, and their relationship with SUV, MV, and TLG in 3 different tumor types. METHODS: Three patient groups corresponding to 3 cancer types at baseline were studied independently: patients with metastatic colorectal cancer (72 lesions), non-small cell lung cancer (24 lesions), and breast cancer (54 lesions). Thirty-one texture indices were studied in addition to SUVs, MV, and TLG, and 5 indices extracted from histogram analysis were also investigated. The relationships between indices were studied as well as the robustness of the various texture indices with respect to the parameters involved in the calculation method (sampling schemes and tumor volume of interest). RESULTS: Regardless of the patient group, many indices were highly correlated (Pearson correlation coefficient |r| ≥ 0.80), making it desirable to focus on only a few uncorrelated indices. Three histogram indices were highly correlated with SUVs (|r| ≥ 0.84). Four texture indices were highly correlated with MV, and none was highly correlated with SUVs (|r| ≤ 0.55). The resampling formula used to calculate texture indices had a substantial impact, and resampling using at least 32 discrete values should be used for texture indices calculation. The texture indices change as a function of the segmentation method was higher than that of peak and maximum SUVs but less than mean SUV for 5 texture indices and was larger than that of MV for 14 texture indices and for the 5 histogram indices. All these results were extremely consistent across the 3 tumor types and explained many of the observations reported in the literature so far. CONCLUSION: None of the histogram indices and only 17 of 31 texture indices were robust with respect to the tumor-segmentation method. An appropriate resampling formula with at least 32 gray levels should be used to avoid introducing a misleading relationship between texture indices and SUV. Some texture indices are highly correlated or strongly correlate with MV whatever the tumor type. Such correlation should be accounted for when interpreting the usefulness of texture indices for tumor characterization, which might call for systematic multivariate analyses.