Hepatocellular carcinoma enhancement on contrast-enhanced CT and MR imaging: response assessment after treatment with sorafenib: preliminary results

2013 ◽  
Vol 119 (4) ◽  
pp. 215-221 ◽  
Author(s):  
Giuseppe Salvaggio ◽  
Alessandro Furlan ◽  
Francesco Agnello ◽  
Giuseppe Cabibbo ◽  
Daniele Marin ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Mr Imaging ◽  
Response Assessment ◽  
Preliminary Results ◽  
Contrast Enhanced Ct ◽  
Contrast Enhanced ◽  
Enhanced Ct ◽  
Imaging Response

scholarly journals Delayed response to proton beam treatment of hepatocellular carcinoma

2020 ◽  
Vol 6 (1) ◽  
pp. 20180125
Author(s):  
Chee-Wai Cheng ◽  
Mitchell Machtay ◽  
Jennifer Dorth ◽  
Olga Sergeeva ◽  
Hangsheng Xia ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Ct Scan ◽  
Proton Beam ◽  
Arterial Phase ◽  
Delayed Response ◽  
Data Set ◽  
Contrast Enhanced Ct ◽  
Contrast Enhanced ◽  
Enhanced Ct ◽  
Imaging Response

Hepatocellular carcinoma (HCC) has become one of the leading causes of cancer death worldwide. There has been anecdotal report regarding the effectiveness of proton beam treatment for HCC. In this pre-clinical investigation, the woodchuck model of viral hepatitis infection-induced HCC was used for proton beam treatment experiment. The radiopaque fiducial markers that are biodegradable were injected around the tumor under ultrasound guidance to facilitate positioning in sequential treatments. An α cradle mode was used to ensure reproducibility of animal positioning on the treatment couch. A CT scan was performed first for contouring by a radiation oncologist. The CT data set with contours was then exported for dose planning. Three fractionations, each 750 CcGyE, were applied every other day with a Mevion S250 passive scattering proton therapy system. Multiphase contrast-enhanced CT scans were performed after the treatment and at later times for follow-ups. 3 weeks post-treatment, shrinking of the HCC nodule was detected and constituted to a partial response (30% reduction along the long axis). By week nine after treatment, the nodule disappeared during the arterial phase of multiphase contrast-enhanced CT scan. Pathological evaluation corroborated with this imaging response. A delayed, but complete imaging response to proton beam treatment applied to HCC was achieved with this unique and clinically relevant animal model of HCC.

Imaging of Solid Kidney Tumours in Children

1995 ◽  
Vol 36 (3) ◽  
pp. 254-260 ◽  
Author(s):  
C. Hugosson ◽  
R. Nyman ◽  
B. Jacobsson ◽  
H. Jorulf ◽  
K. Sackey ◽  
...  
Keyword(s):  
Mr Imaging ◽  
Clear Cell ◽  
Wilms Tumour ◽  
Rhabdoid Tumour ◽  
Contrast Enhanced Ct ◽  
Contrast Enhanced ◽  
Renal Tumours ◽  
Enhanced Ct ◽  
Mr Characteristics

Eighteen children aged 6 months to 12 years with 20 solid renal tumours; 13 Wilms' tumours (WT), 2 clear cell sarcomas of the kidney, 1 malignant rhabdoid tumour of the kidney and 2 cases of bilateral nephroblastomatosis with Wilms' tumour underwent evaluation with US, CT and MR imaging. Contrast-enhanced CT and non-enhanced MR were equally accurate in determining the size and origin of the tumour but were unreliable in separation of stages I, II and III. US could only accurately assess the size of the tumours. MR characteristics varied somewhat between WTs and non-WTs but contrast-enhanced MR imaging might be useful for separation of WTs from nephroblastomatosis.

Predictive model for microvascular invasion of hepatocellular carcinoma among candidates for either hepatectomy or liver transplantation.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 4079-4079
Author(s):  
Hidetoshi Nitta ◽  
Marc Antoine Allard ◽  
Mylene Sebagh ◽  
Gabriella Pittau ◽  
Oriana Ciacio ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Liver Transplantation ◽  
Predictive Model ◽  
Validation Cohort ◽  
Microvascular Invasion ◽  
Roc Curve Analysis ◽  
Training Cohort ◽  
Contrast Enhanced Ct ◽  
Contrast Enhanced ◽  
Enhanced Ct

4079 Background: Microvascular invasion (MVI) is the strongest prognostic factor following surgery of hepatocellular carcinoma (HCC). However, it is usually not available on the preoperative setting. A predictive model of MVI in patients scheduled for hepatic resection (HR) or liver transplantation (LT) would thus help guiding treatment strategy. The aim of this study was to develop a predictive model for MVI of HCC before either HR or LT. Methods: HCC patients who consecutively performed HR or LT from January 1994 to June 2016 at a single institution were subdivided into a training and validation cohort. Risk factors for MVI in the training cohort were used to develop a predictive model for MVI, to be validated in the validation cohort. The outcomes of the HR and LT patients with high or low MVI probability based on the model, were compared using propensity score matching (PSM). Cut-off values for continuous factors were determined based on ROC curve analysis. Results: A total of 910 patients (425 HR, 485 LT) were included in the training (n = 637) and validation (n = 273) cohorts. In the training cohort, multivariate analysis demonstrated that alpha-fetoprotein ≥100ng/ml ( p < 0.0001), largest tumor size ≥40mm ( p = 0.0002), non-boundary HCC type on contrast-enhanced CT ( p = 0.001), neutrophils-to-lymphocytes ratio ≥3.2 ( p = 0.002), aspartate aminotransferase ≥62U/l ( p = 0.02) were independently associated with MVI. Combinations of these 5 factors varied the MVI probability from 15.5% to 91.1%. This predictive model achieved a good c-index of 0.76 in the validation cohort. In PSM (109 HR, 109 LT), there was no difference in survival between HR and LT patients among the high MVI probability (≥50%) patients, (5y-OS; 46.3% vs 42.2%, p = 0.77, 5y-RFS; 54.0% vs 28.8%, p = 0.21). Among the low probability ( < 50%), survival was significantly decreased following HR compared with LT (5y-OS; 54.1% vs 78.8%, p = 0.007, 5y-RFS; 17.3% vs 86.1%, p< 0.0001). Conclusions: This model developed from preoperative data allows reliable prediction of MVI, and may thus help with preoperative decisions about the suitability of HR or LT in patients with HCC.

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