Treatment response classification of liver metastatic disease evaluated on imaging. Are RECIST unidimensional measurements accurate?

Appropriate use of morphological imaging for assessing treatment response and disease progression of neuroendocrine tumors

Neuroendocrine tumors (NETs) are relatively rare neoplasms displaying heterogeneous clinical behavior, ranging from indolent to aggressive forms. Patients diagnosed with NETs usually receive a varied array of treatments, including somatostatin analogs, locoregional treatments (ablation, intra-arterial therapy), cytotoxic chemotherapy, peptide receptor radionuclide therapy (PRRT), and targeted therapies. To maximize therapeutic efficacy while limiting toxicity (both physical and economic), there is a need for accurate and reliable tools to monitor disease evolution and progression and to assess the effectiveness of these treatments. Imaging morphological methods, primarily relying on computed tomography (CT) and magnetic resonance imaging (MRI), are indispensable modalities for the initial evaluation and continuous monitoring of patients with NETs, therefore playing a pivotal role in gauging the response to treatment. The primary goal of assessing tumor response is to anticipate and weigh the benefits of treatments, especially in terms of survival gain. The World Health Organization took the pioneering step of introducing assessment criteria based on cross-sectional imaging. This initial proposal standardized the measurement of lesion sizes, laying the groundwork for subsequent criteria. The Response Evaluation Criteria in Solid Tumors (RECIST) subsequently refined and enhanced these standards, swiftly gaining acceptance within the oncology community. New treatments were progressively introduced, targeting specific features of NETs (such as tumor vascularization or expression of specific receptors), and achieving significant qualitative changes within tumors, although associated with minimal or paradoxical effects on tumor size. Several alternative criteria, adapted from those used in other cancer types and focusing on tumor viability, the slow growth of NETs, or refining the existing size-based RECIST criteria, have been proposed in NETs. This review article aims to describe and discuss the optimal utilization of CT and MRI for assessing the response of NETs to treatment; it provides a comprehensive overview of established and emerging criteria for evaluating tumor response, along with comparative analyses. Molecular imaging will not be addressed here and is covered in a dedicated article within this special issue.

Comparison of quantitative volumetric analysis and linear measurement for predicting the survival of Barcelona Clinic Liver Cancer 0- and A stage hepatocellular carcinoma after radiofrequency ablation

PURPOSE

The prognostic role of the tumor volume in patients with hepatocellular carcinoma (HCC) at the Barcelona Clinic Liver Cancer (BCLC) 0 and A stages remains unclear. This study aims to compare the volumetric measurement with linear measurement in early HCC burden profile and clarify the optimal cut-off value of the tumor volume.

METHODS

The consecutive patients diagnosed with HCC who underwent initial and curative-intent radiofrequency ablation (RFA) were included retrospectively. The segmentation was performed semi-automatically, and enhanced tumor volume (ETV) as well as total tumor volume (TTV) were obtained. The patients were categorized into high- and low-tumor burden groups according to various cutoff values derived from commonly used diameter values, X-tile software, and decision-tree analysis. The inter- and intra-reviewer agreements were measured using the intra-class correlation coefficient. Univariate and multivariate time-to-event Cox regression analyses were performed to identify the prognostic factors of overall survival.

RESULTS

A total of 73 patients with 81 lesions were analyzed in the whole cohort with a median follow-up of 31.0 (interquartile range: 16.0–36.3). In tumor segmentation, excellent consistency was observed in intra- and inter-reviewer assessments. There was a strong correlation between diameter-derived spherical volume and ETV as well as ETV and TTV. As opposed to all linear candidates and 4,188 mm3 (sphere equivalent to 2 cm in diameter), ETV >14,137 mm3 (sphere equivalent to 3 cm in diameter) or 23,000 mm3 (sphere equivalent to 3.5 cm in diameter) was identified as an independent risk factor of survival. Considering the value of hazard ratio and convenience to use, when ETV was at 23,000 mm3, it was regarded as the optimal volumetric cut-off value in differentiating survival risk.

CONCLUSION

The volumetric measurement outperforms linear measurement on tumor burden evaluation for survival stratification in patients at BCLC 0 and A stages HCC after RFA.

Saliency-based 3D convolutional neural network for categorising common focal liver lesions on multisequence MRI

Background

The imaging features of focal liver lesions (FLLs) are diverse and complex. Diagnosing FLLs with imaging alone remains challenging. We developed and validated an interpretable deep learning model for the classification of seven categories of FLLs on multisequence MRI and compared the differential diagnosis between the proposed model and radiologists.

Methods

In all, 557 lesions examined by multisequence MRI were utilised in this retrospective study and divided into training–validation (n = 444) and test (n = 113) datasets. The area under the receiver operating characteristic curve (AUC) was calculated to evaluate the performance of the model. The accuracy and confusion matrix of the model and individual radiologists were compared. Saliency maps were generated to highlight the activation region based on the model perspective.

Results

The AUC of the two- and seven-way classifications of the model were 0.969 (95% CI 0.944–0.994) and from 0.919 (95% CI 0.857–0.980) to 0.999 (95% CI 0.996–1.000), respectively. The model accuracy (79.6%) of the seven-way classification was higher than that of the radiology residents (66.4%, p = 0.035) and general radiologists (73.5%, p = 0.346) but lower than that of the academic radiologists (85.4%, p = 0.291). Confusion matrices showed the sources of diagnostic errors for the model and individual radiologists for each disease. Saliency maps detected the activation regions associated with each predicted class.

Conclusion

This interpretable deep learning model showed high diagnostic performance in the differentiation of FLLs on multisequence MRI. The analysis principle contributing to the predictions can be explained via saliency maps.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13244-021-01117-z.

Tumor Doubling Time Using CT Volumetric Segmentation in Metastatic Adrenocortical Carcinoma

Adrenocortical carcinoma (ACC) is a rare malignancy with an overall unfavorable prognosis. Clinicians treating patients with ACC have noted accelerated growth in metastatic liver lesions that requires rapid intervention compared to other metastatic locations. This study measured and compared the growth rates of metastatic ACC lesions in the lungs, liver, and lymph nodes using volumetric segmentation. A total of 12 patients with metastatic ACC (six male; six female) were selected based on their medical history. Computer tomography (CT) exams were retrospectively reviewed and a sampling of ≤5 metastatic lesions per organ were selected for evaluation. Lesions in the liver, lung, and lymph nodes were measured and evaluated by volumetric segmentation. Statistical analyses were performed to compare the volumetric growth rates of the lesions in each organ system. In this cohort, 5/12 had liver lesions, 7/12 had lung lesions, and 5/12 had lymph node lesions. A total of 92 lesions were evaluated and segmented for lesion volumetry. The volume doubling time per organ system was 27 days in the liver, 90 days in the lungs, and 95 days in the lymph nodes. In this series of 12 patients with metastatic ACC, liver lesions showed a faster growth rate than lung or lymph node lesions.

Variability of quantitative measurements of metastatic liver lesions: a multi-radiation-dose-level and multi-reader comparison

PURPOSE

To evaluate the variability of quantitative measurements of metastatic liver lesions by using a multi-radiation-dose-level and multi-reader comparison.

METHODS

Twenty-three study subjects (mean age, 60 years) with 39 liver lesions who underwent a single-energy dual-source contrast-enhanced staging CT between June 2015 and December 2015 were included. CT data were reconstructed with seven different radiation dose levels (ranging from 25 to 100%) on the basis of a single CT acquisition. Four radiologists independently performed manual tumor measurements and two radiologists performed semi-automated tumor measurements. Interobserver, intraobserver, and interdose sources of variability for longest diameter and volumetric measurements were estimated and compared using Wilcoxon rank-sum tests and intraclass correlation coefficients.

RESULTS

Inter- and intraobserver variabilities for manual measurements of the longest diameter were higher compared to semi-automated measurements (p < 0.001 for overall). Inter- and intraobserver variabilities of volume measurements were higher compared to the longest diameter measurement (p < 0.001 for overall). Quantitative measurements were statistically different at < 50% radiation dose levels for semi-automated measurements of the longest diameter, and at 25% radiation dose level for volumetric measurements. The variability related to radiation dose was not significantly different from the inter- and intraobserver variability for the measurements of the longest diameter.

CONCLUSION

The variability related to radiation dose is comparable to the inter- and intraobserver variability for measurements of the longest diameter. Caution should be warranted in reducing radiation dose level below 50% of a conventional CT protocol due to the potentially detrimental impact on the assessment of lesion response in the liver.

Evaluation of liver tumour response by imaging

The goal of assessing tumour response on imaging is to identify patients who are likely to benefit - or not - from anticancer treatment, especially in relation to survival. The World Health Organization was the first to develop assessment criteria. This early score, which assessed tumour burden by standardising lesion size measurements, laid the groundwork for many of the criteria that followed. This was then improved by the Response Evaluation Criteria in Solid Tumours (RECIST) which was quickly adopted by the oncology community. At the same time, many interventional oncology treatments were developed to target specific features of liver tumours that result in significant changes in tumours but have little effect on tumour size. New criteria focusing on the viable part of tumours were therefore designed to provide more appropriate feedback to guide patient management. Targeted therapy has resulted in a breakthrough that challenges conventional response criteria due to the non-linear relationship between response and tumour size, requiring the development of methods that emphasize the appearance of tumours. More recently, research into functional and quantitative imaging has created new opportunities in liver imaging. These results have suggested that certain parameters could serve as early predictors of response or could predict later tumour response at baseline. These approaches have now been extended by machine learning and deep learning. This clinical review focuses on the progress made in the evaluation of liver tumours on imaging, discussing the rationale for this approach, addressing challenges and controversies in the field, and suggesting possible future developments.

An observational study to justify and plan a future phase III randomized controlled trial of metformin in improving overall survival in patients with inoperable pancreatic cancer without liver metastases

PURPOSE

Metformin has plausible direct and indirect anti-cancer properties against pancreatic adenocarcinoma cells. However, metformin may only be efficacious in patients with inoperable pancreatic ductal adenocarcinoma (PDAC) without liver metastases. Absorption may be decreased by gastrointestinal symptoms and proton pump inhibitors (PPIs). We aimed to justify and inform a future phase III trial of metformin versus placebo on survival in inoperable PDAC by documenting prevalence of patients meeting eligibility criteria, gastrointestinal symptoms and PPI use.

METHODS

Patient notes with PDAC were reviewed at a large teaching hospital over 2 years. Study variables were obtained from multiple sources of information.

RESULTS

141 participants were identified (51.8% female), of which 37.6% were not prescribed metformin at diagnosis and had no radiological hepatic metastases. Characteristics were similar between non-metformin and metformin users. In eligible patients, 65.2% reported nausea and vomiting and 46.2% were prescribed PPIs.

CONCLUSION

Approximately, a third of all patients with inoperable PDAC are eligible for a future trial of metformin, allowing an estimate of the number of hospitals required for recruitment. Nausea and vomiting are common and should be managed effectively to prevent trial dropouts. PPI use is frequent and their influence on metformin's pharmacodynamic actions needs to be clarified.

Deep Learning for Automated Segmentation of Liver Lesions at CT in Patients with Colorectal Cancer Liver Metastases

Purpose

To evaluate the performance, agreement, and efficiency of a fully convolutional network (FCN) for liver lesion detection and segmentation at CT examinations in patients with colorectal liver metastases (CLMs).

Materials and Methods

This retrospective study evaluated an automated method using an FCN that was trained, validated, and tested with 115, 15, and 26 contrast material-enhanced CT examinations containing 261, 22, and 105 lesions, respectively. Manual detection and segmentation by a radiologist was the reference standard. Performance of fully automated and user-corrected segmentations was compared with that of manual segmentations. The interuser agreement and interaction time of manual and user-corrected segmentations were assessed. Analyses included sensitivity and positive predictive value of detection, segmentation accuracy, Cohen κ, Bland-Altman analyses, and analysis of variance.

Results

In the test cohort, for lesion size smaller than 10 mm (n = 30), 10-20 mm (n = 35), and larger than 20 mm (n = 40), the detection sensitivity of the automated method was 10%, 71%, and 85%; positive predictive value was 25%, 83%, and 94%; Dice similarity coefficient was 0.14, 0.53, and 0.68; maximum symmetric surface distance was 5.2, 6.0, and 10.4 mm; and average symmetric surface distance was 2.7, 1.7, and 2.8 mm, respectively. For manual and user-corrected segmentation, κ values were 0.42 (95% confidence interval: 0.24, 0.63) and 0.52 (95% confidence interval: 0.36, 0.72); normalized interreader agreement for lesion volume was -0.10 ± 0.07 (95% confidence interval) and -0.10 ± 0.08; and mean interaction time was 7.7 minutes ± 2.4 (standard deviation) and 4.8 minutes ± 2.1 (P < .001), respectively.

Conclusion

Automated detection and segmentation of CLM by using deep learning with convolutional neural networks, when manually corrected, improved efficiency but did not substantially change agreement on volumetric measurements.© RSNA, 2019Supplemental material is available for this article.

Volumetric analysis at abdominal CT: oncologic and non-oncologic applications

Volumetric analysis is an objective three-dimensional assessment of a lesion or organ that may more accurately depict the burden of complex objects compared to traditional linear size measurement. Small changes in linear size are amplified by corresponding changes in volume, which could have significant clinical implications. Though early methods of calculating volumes were time-consuming and laborious, multiple software platforms are now available with varying degrees of user-software interaction ranging from manual to fully automated. For the assessment of primary malignancy and metastatic disease, volumetric measurements have shown utility in the evaluation of disease burden prior to and following therapy in a variety of cancers. Additionally, volume can be useful in treatment planning prior to resection or locoregional therapies, particularly for hepatic tumours. The utility of CT volumetry in a wide spectrum of non-oncologic pathology has also been described. While clear advantages exist in certain applications, some data have shown that volume is not always the superior method of size assessment and the associated labor intensity may not be worthwhile. Further, lack of uniformity among software platforms is a challenge to widespread implementation. This review will discuss CT volumetry and its potential oncologic and non-oncologic applications in abdominal imaging, as well as advantages and limitations to this quantitative technique.

Validity of RECIST Version 1.1 for Response Assessment in Metastatic Cancer: A Prospective, Multireader Study

Purpose To determine the relationship between target lesion selection with use of Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 and classification of therapeutic response in patients with metastatic cancer undergoing systemic cytotoxic and/or targeted therapies. Materials and Methods This prospective multireader study was conducted between July 2015 and July 2017. Three hundred sixteen consecutive participants with metastatic cancer underwent 932 CT examinations to monitor systemic treatment. CT studies were independently read by three radiologists. Readers identified a maximum of five lesions total (and a maximum of two lesions per organ). Dedicated oncology tumor response software was used. The Fleiss κ statistic was used to analyze interreader agreement in the assignment of individual response classes (complete response, partial response, progressive disease, or stable disease) and in the differentiation between progressive and nonprogressive disease. Results Readers selected the same set of target lesions in 128 of the 316 participants (41%) and selected a different set in 188 (59%). When target lesion selection was concordant, agreement was high (assignment of treatment response category: κ = 0.97; 95% confidence interval [CI]: 0.91, 1.0; differentiation between progressive and nonprogressive disease: κ = 0.98; 95% CI: 0.90, 1.0). When target lesion selection was discordant, agreement was significantly reduced (assignment of treatment response category: κ = 0.58; 95% CI: 0.54, 0.62; differentiation between progressive and nonprogressive disease: κ = 0.6; 95% CI: 0.59, 0.70). With concordant target lesion selection, readers agreed regarding diagnosis of progression in 97.7% of participants (95% CI: 95.4%, 100.0%); with discordant target lesion selection, readers agreed in only 55.3% (95% CI: 47.9%, 62.6%) (P < .01). Conclusion In patients with metastatic cancer undergoing systemic treatment, different cancer sites may appear similarly suitable and thus likely to be selected as target lesions but may yield inconsistent or even conflicting results with Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1. This indicates that the current, limited set of target lesions in RECIST 1.1 may not reflect overall tumor load or response to therapy. © RSNA, 2018 See also the editorial by Sosna in this issue.

Combined Volumetric and Density Analyses of Contrast-Enhanced CT Imaging to Assess Drug Therapy Response in Gastroenteropancreatic Neuroendocrine Diffuse Liver Metastasis

OBJECTIVE

We propose a computer-aided method to assess response to drug treatment, using CT imaging-based volumetric and density measures in patients with gastroenteropancreatic neuroendocrine tumors (GEP-NETs) and diffuse liver metastases.

METHODS

Twenty-five patients with GEP-NETs with diffuse liver metastases were enrolled. Pre- and posttreatment CT examinations were retrospectively analyzed. Total tumor volume (volume) and mean volumetric tumor density (density) were calculated based on tumor segmentation on CT images. The maximum axial diameter (tumor size) for each target tumor was measured on pre- and posttreatment CT images according to Response Evaluation Criteria In Solid Tumors (RECIST). Progression-free survival (PFS) for each patient was measured and recorded.

RESULTS

Correlation analysis showed inverse correlation between change of volume and density (Δ(V + D)), change of volume (ΔV), and change of tumor size (ΔS) with PFS (r = -0.653, P=0.001; r = -0.617, P=0.003; r = -0.548, P=0.01, respectively). There was no linear correlation between ΔD and PFS (r = -0.226, P=0.325).

CONCLUSION

The changes of volume and density derived from CT images of all lesions showed a good correlation with PFS and may help assess treatment response.

Imaging evaluation of sorafenib for treatment of advanced hepatocellular carcinoma

Sorafenib, which is a novel targeted agent, plays an important role in treating advanced hepatocellular carcinoma (HCC) through its antiangiogenic and antiproliferative effects. However, conventional morphology-based radiographic evaluation systems may underestimate the efficacy of sorafenib in HCC due to a lack of apparent tumor shrinkage or altered tumor morphology in many cases. This calls for the development of more accurate imaging methods for evaluating sorafenib. The introduction of tumor burden measurements based on viability and other evolving imaging approaches for assessing therapeutic effects are promising for overcoming some of the limitations of the morphology-based criteria. In this review, we summarize various imaging methods that are used to assess treatment responses of advanced HCC to sorafenib. Imaging markers predictive of prognosis in advanced HCC after treatment with sorafenib are also included and discussed.

Volumetric Versus Unidimensional Measures of Metastatic Colorectal Cancer in Assessing Disease Response

INTRODUCTION

The purpose of this study was to compare unidimensional (1D/linear) and volumetric (3D) measures of metastatic colorectal cancer (mCRC) at computed tomography (CT) for predicting clinical outcome.

PATIENTS AND METHODS

Analysis of CT images in 105 patients (mean age, 59 years; range, 25-81 years; 45 women, 60 men) receiving treatment for mCRC was performed. Both unidimensional and volumetric measures were obtained on index lesions at 3 time points (baseline/midpoint/post-therapy; mean interval, 4.1 months; median, 3.7 months) by 3 readers using a semi-automated technique. Measurements were summed and compared using best overall response across the 3 time points. Patient response was categorized based on Response Evaluation Criteria In Solid Tumors (RECIST) 1.1 thresholds for unidimensional and volume measures (CR, complete response; PR, partial response; SD, stable disease; PD, progressive disease). Survival data was correlated (mean follow-up, 19.9 ± 17.1 months; median, 14.7 months). Intra/interobserver variability and reproducibility of 1D and 3D measures was assessed. Cox survival and Kaplan-Meier models were constructed and compared.

RESULTS

Cox models and Kaplan-Meier curves for unidimensional versus volumetric assessment were very similar in appearance. Both 1D and 3D measurements effectively separated PD from the SD/PR groups, but neither separated SD from PR well. Volumetric measures showed comparable intra/interobserver variability on Bland-Altman analysis to unidimensional measures across readers using a semi-automated measurement technique. Metastatic site (lung, liver, node, other) did not seem to impact measurement reproducibility.

CONCLUSIONS

Although CT volumetric assessment of metastatic colorectal cancer is fairly reproducible by reader and site using a semi-automated technique, the ability to stratify progressive disease from other disease response categories in terms of survival was similar to unidimensional measurement.

New concepts in embolotherapy of HCC

Hepatocellular carcinoma (HCC) is the second most common cause of cancer-related deaths worldwide with rapidly growing incidence rates in the USA and Europe. Despite improving surveillance programs, most patients are diagnosed at intermediate to advanced stages and are no longer amenable to curative therapies, such as ablation, surgical resection and liver transplantation. For such patients, catheter-based image-guided embolotherapies such as transarterial chemoembolization (TACE) represent the standard of care and mainstay therapy, as recommended and endorsed by a variety of national guidelines and staging systems. The main benefit of these therapies is explained by the preferentially arterial blood supply of liver tumors, which allows to deliver the anticancer therapy directly to the tumor-feeding artery while sparing the healthy hepatic tissue mainly supplied by the portal vein. The tool box of an interventional oncologist contains several different variants of transarterial treatment modalities. Ever since the first TACE more than 30 years ago, these techniques have been progressively refined, both with respect to drug delivery materials and with respect to angiographic micro-catheter and image-guidance technology, thus substantially improving therapeutic outcomes of HCC. This review will summarize the fundamental principles, technical and clinical data on the application of different embolotherapies, such as bland transarterial embolization, Lipiodol-based conventional transarterial chemoembolization as well as TACE with drug-eluting beads (DEB-TACE). Clinical data on ⁹⁰Yttrium radioembolization as an emerging alternative, mostly applied for niche indications such as HCC with portal vein invasion, will be discussed. Furthermore, we will summarize the principle of HCC staging, patient allocation and response assessment in the setting of HCC embolotherapy. In addition, we will evaluate the role of cone-beam computed tomography as a novel intra-procedural image-guidance technology. Finally, this review will touch on new technical developments such as radiopaque, imageable DEBs and the rationale and role of combined systemic and locoregional therapies, mostly in combination with Sorafenib.

Diagnostic accuracy of contemporary multidetector computed tomography (MDCT) for the detection of lumbar disc herniation

OBJECTIVES

To evaluate the diagnostic accuracy of multidetector CT (MDCT) for detection of lumbar disc herniation with MRI as standard of reference.

METHODS

Patients with low back pain underwent indicated MDCT (128-row MDCT, helical pitch), 60 patients with iterative reconstruction (IR) and 67 patients with filtered back projection (FBP). Lumbar spine MRI (1.5 T) was performed within 1 month. Signal-to-noise ratios (SNR) of cerebrospinal fluid (CSF), annulus fibrosus (AF) and the spinal cord (SC) were determined for all modalities. Two readers independently rated image quality (IQ), diagnostic confidence and accuracy in the diagnosis of lumbar disc herniation using MRI as standard of reference. Inter-reader correlation was assessed with weighted κ.

RESULTS

Sensitivity, specificity, precision and accuracy of MDCT for disc protrusion were 98.8%, 96.5%, 97.1%, 97.8% (disc level), 97.7%, 92.9%, 98.6%, 96.9% (patient level). SNR of IR was significantly higher than FBP. IQ was significantly better in IR owing to visually reduced noise and improved delineation of the discs. κ (>0.90) was excellent for both algorithms.

CONCLUSION

MDCT of the lumbar spine yields high diagnostic accuracy for detection of lumbar disc herniation. IR improves image quality so that the provided diagnostic accuracy is principally equivalent to MRI.

KEY POINTS

• MDCT is an accurate alternative to MRI in disc herniation diagnosis. • By IR enhanced image quality improves MDCT diagnostic confidence similar to MRI. • Advances in CT technology contribute to improved diagnostic performance in lumbar spine imaging.

Imaging Biomarkers of Tumor Response in Neuroendocrine Liver Metastases Treated with Transarterial Chemoembolization: Can Enhancing Tumor Burden of the Whole Liver Help Predict Patient Survival?

Purpose To investigate whether whole-liver enhancing tumor burden [ETB] can serve as an imaging biomarker and help predict survival better than World Health Organization (WHO), Response Evaluation Criteria in Solid Tumors (RECIST), modified RECIST (mRECIST), and European Association for the Study of the Liver (EASL) methods in patients with multifocal, bilobar neuroendocrine liver metastases (NELM) after the first transarterial chemoembolization (TACE) procedure. Materials and Methods This HIPAA-compliant, institutional review board-approved retrospective study included 51 patients (mean age, 57.8 years ± 13.2; range, 13.5-85.8 years) with multifocal, bilobar NELM treated with TACE. The largest area (WHO), longest diameter (RECIST), longest enhancing diameter (mRECIST), largest enhancing area (EASL), and largest enhancing volume (ETB) were measured at baseline and after the first TACE on contrast material-enhanced magnetic resonance images. With three-dimensional software, ETB was measured as more than 2 standard deviations the signal intensity of a region of interest in normal liver. Response was assessed with WHO, RECIST, mRECIST, and EASL methods according to their respective criteria. For ETB response, a decrease in enhancement of at least 30%, 50%, and 65% was analyzed by using the Akaike information criterion. Survival analysis included Kaplan-Meier curves and Cox regressions. Results Treatment response occurred in 5.9% (WHO criteria), 2.0% (RECIST), 25.5% (mRECIST), and 23.5% (EASL criteria) of patients. With 30%, 50%, and 65% cutoffs, ETB response was seen in 60.8%, 39.2%, and 21.6% of patients, respectively, and was the only biomarker associated with a survival difference between responders and nonresponders (45.0 months vs 10.0 months, 84.3 months vs 16.7 months, and 85.2 months vs 21.2 months, respectively; P < .01 for all). The 50% cutoff provided the best survival model (hazard ratio [HR]: 0.2; 95% confidence interval [CI]: 0.1, 0.4). At multivariate analysis, ETB response was an independent predictor of survival (HR: 0.2; 95% CI: 0.1, 0.6). Conclusion Volumetric ETB is an early treatment response biomarker and surrogate for survival in patients with multifocal, bilobar NELM after the first TACE procedure. ^© RSNA, 2016.

CT texture analysis in colorectal liver metastases: A better way than size and volume measurements to assess response to chemotherapy?

BACKGROUND

Response Evaluation Criteria In Solid Tumors (RECIST) are known to have limitations in assessing the response of colorectal liver metastases (CRLMs) to chemotherapy.

OBJECTIVE

The objective of this article is to compare CT texture analysis to RECIST-based size measurements and tumor volumetry for response assessment of CRLMs to chemotherapy.

METHODS

Twenty-one patients with CRLMs underwent CT pre- and post-chemotherapy. Texture parameters mean intensity (M), entropy (E) and uniformity (U) were assessed for the largest metastatic lesion using different filter values (0.0 = no/0.5 = fine/1.5 = medium/2.5 = coarse filtration). Total volume (cm(3)) of all metastatic lesions and the largest size of one to two lesions (according to RECIST 1.1) were determined. Potential predictive parameters to differentiate good responders (n = 9; histological TRG 1-2) from poor responders (n = 12; TRG 3-5) were identified by univariable logistic regression analysis and subsequently tested in multivariable logistic regression analysis. Diagnostic odds ratios were recorded.

RESULTS

The best predictive texture parameters were Δuniformity and Δentropy (without filtration). Odds ratios for Δuniformity and Δentropy in the multivariable analyses were 0.95 and 1.34, respectively. Pre- and post-treatment texture parameters, as well as the various size and volume measures, were not significant predictors. Odds ratios for Δsize and Δvolume in the univariable logistic regression were 1.08 and 1.05, respectively.

CONCLUSIONS

Relative differences in CT texture occurring after treatment hold promise to assess the pathologic response to chemotherapy in patients with CRLMs and may be better predictors of response than changes in lesion size or volume.

Comparison of Existing Response Criteria in Patients with Hepatocellular Carcinoma Treated with Transarterial Chemoembolization Using a 3D Quantitative Approach

PURPOSE

To compare currently available non-three-dimensional methods (Response Evaluation Criteria in Solid Tumors [RECIST], European Association for Study of the Liver [EASL], modified RECIST [mRECIST[) with three-dimensional (3D) quantitative methods of the index tumor as early response markers in predicting patient survival after initial transcatheter arterial chemoembolization (TACE).

MATERIALS AND METHODS

This was a retrospective single-institution HIPAA-compliant and institutional review board-approved study. From November 2001 to November 2008, 491 consecutive patients underwent intraarterial therapy for liver cancer with either conventional TACE or TACE with drug-eluting beads. A diagnosis of hepatocellular carcinoma (HCC) was made in 290 of these patients. The response of the index tumor on pre- and post-TACE magnetic resonance images was assessed retrospectively in 78 treatment-naïve patients with HCC (63 male; mean age, 63 years ± 11 [standard deviation]). Each response assessment method (RECIST, mRECIST, EASL, and 3D methods of volumetric RECIST [vRECIST] and quantitative EASL [qEASL]) was used to classify patients as responders or nonresponders by following standard guidelines for the uni- and bidimensional measurements and by using the formula for a sphere for the 3D measurements. The Kaplan-Meier method with the log-rank test was performed for each method to evaluate its ability to help predict survival of responders and nonresponders. Uni- and multivariate Cox proportional hazard ratio models were used to identify covariates that had significant association with survival.

RESULTS

The uni- and bidimensional measurements of RECIST (hazard ratio, 0.6; 95% confidence interval [CI]: 0.3, 1.0; P = .09), mRECIST (hazard ratio, 0.6; 95% CI: 0.6, 1.0; P = .05), and EASL (hazard ratio, 1.1; 95% CI: 0.6, 2.2; P = .75) did not show a significant difference in survival between responders and nonresponders, whereas vRECIST (hazard ratio, 0.6; 95% CI: 0.3, 1.0; P = .04), qEASL (Vol) (hazard ratio, 0.5; 95% CI: 0.3, 0.9; P = .02), and qEASL (%) (hazard ratio, 0.3; 95% CI: 0.15, 0.60; P < .001) did show a significant difference between these groups.

CONCLUSION

The 3D-based imaging biomarkers qEASL and vRECIST were tumor response criteria that could be used to predict patient survival early after initial TACE and enabled clear identification of nonresponders.

Intraprocedural 3D Quantification of Lipiodol Deposition on Cone-Beam CT Predicts Tumor Response After Transarterial Chemoembolization in Patients with Hepatocellular Carcinoma

PURPOSE

To evaluate whether intraprocedural 3D quantification of Lipiodol deposition on cone-beam computed tomography (CBCT) can predict tumor response on follow-up contrast-enhanced magnetic resonance imaging (CE-MRI) in patients with hepatocellular carcinoma (HCC) treated with conventional transarterial chemoembolization (cTACE).

MATERIALS AND METHODS

This IRB approved, retrospective analysis included 36 patients with 51 HCC target lesions, who underwent cTACE with CBCT. CE-MRI was acquired at baseline and 1 month after cTACE. Overall tumor volumes as well as intratumoral Lipiodol volumes on CBCT were measured and compared with the overall and necrotic (non-enhancing) tumor volumes on CE-MRI using the paired student's t test. Tumor response on CE-MRI was assessed using modified response evaluation criteria in solid tumors (mRECIST). A linear regression model was used to correlate tumor volumes, Lipiodol volumes, and the percentage of Lipiodol deposition on CBCT with the corresponding parameters on CE-MRI. Nonparametric spearman rank-order correlation and trend test were used to correlate the percentage of Lipiodol deposition in the tumor with tumor response.

RESULT

A strong correlation between overall tumor volumes on CBCT and CE-MRI was observed (R(2) = 0.986). In addition, a strong correlation was obtained between the volume of Lipiodol deposition on CBCT and tumor necrosis (in cm(3)) on CE-MRI (R(2) = 0.960), and between the percentage of Lipiodol deposition and tumor necrosis (R(2) = 0.979). Importantly, the extent of Lipiodol deposition (in percentage of total tumor volume) correlated strongly with tumor response on CE-MRI (Spearman rho = 0.84, p < 0.001).

CONCLUSIONS

Intraprocedural 3D quantification of Lipiodol deposition on CBCT can be used to predict tumor response on follow-up CE-MRI.

Tumor growth kinetics versus RECIST to assess response to locoregional therapy in breast cancer liver metastases

RATIONALE AND OBJECTIVES

The aim of our study was to evaluate changes in growth kinetics of breast cancer liver metastasis in response to locoregional therapy and compare them to Response Evaluation Criteria in Solid Tumors (RECIST).

MATERIALS AND METHODS

This Health Insurance Portability and Accountability Act-compliant retrospective study was Institutional Review Board approved. Thirty-four chemorefractory breast cancer liver metastases from 21 patients treated with yttrium-90 ((90)Y) were evaluated. Pre- and posttreatment computed tomography (CT) scans were used to calculate tumor growth kinetics. The growth parameter analyzed was reciprocal of doubling time (RDT). RDT range for stable disease (SD) was defined by the measurement error rate. A negative RDT below the SD range defined response and was categorized as either partial response (PR) or complete response, whereas a positive RDT value above the SD range indicated progressive disease (PD). Comparison was made to tumor response classification according to percentage change in the lesion's maximal diameter per RECIST. Lin's concordance correlation coefficient, Bland-Altman plot, Wilcoxon signed rank test, and Student t test were used for analysis. Significance was set at 0.05.

RESULTS

RDT range for SD ranged from -0.46 to +2.17. Six lesions with PR based on RECIST showed PR based on their volumetric growth rate (mean RDT of -17.3 ± 2.6). Similarly, one lesion with PD according to RECIST was categorized as PD based on its growth kinetics (RDT of 10.2). However, 14 (51.85%) lesions classified as SD by RECIST had PR according to growth kinetics (mean RDT of -7.8), six (22.22%) lesions were categorized as SD (mean RDT of 0.8), whereas seven (25.93%) lesions showed PD (mean RDT of 4.5). Growth kinetic parameters were significantly different for lesions with PR when compared to lesions with PD (P < .0001).

CONCLUSIONS

In patients with breast cancer liver metastases undergoing locoregional therapy, RECIST categorization may not be an accurate reflection of treatment response.

Radiologic-pathologic analysis of contrast-enhanced and diffusion-weighted MR imaging in patients with HCC after TACE: diagnostic accuracy of 3D quantitative image analysis

PURPOSE

To evaluate the diagnostic performance of three-dimensional ( 3D three-dimensional ) quantitative enhancement-based and diffusion-weighted volumetric magnetic resonance (MR) imaging assessment of hepatocellular carcinoma ( HCC hepatocellular carcinoma ) lesions in determining the extent of pathologic tumor necrosis after transarterial chemoembolization ( TACE transarterial chemoembolization ).

MATERIALS AND METHODS

This institutional review board-approved retrospective study included 17 patients with HCC hepatocellular carcinoma who underwent TACE transarterial chemoembolization before surgery. Semiautomatic 3D three-dimensional volumetric segmentation of target lesions was performed at the last MR examination before orthotopic liver transplantation or surgical resection. The amount of necrotic tumor tissue on contrast material-enhanced arterial phase MR images and the amount of diffusion-restricted tumor tissue on apparent diffusion coefficient ( ADC apparent diffusion coefficient ) maps were expressed as a percentage of the total tumor volume. Visual assessment of the extent of tumor necrosis and tumor response according to European Association for the Study of the Liver ( EASL European Association for the Study of the Liver ) criteria was performed. Pathologic tumor necrosis was quantified by using slide-by-slide segmentation. Correlation analysis was performed to evaluate the predictive values of the radiologic techniques.

RESULTS

At histopathologic examination, the mean percentage of tumor necrosis was 70% (range, 10%-100%). Both 3D three-dimensional quantitative techniques demonstrated a strong correlation with tumor necrosis at pathologic examination (R(2) = 0.9657 and R(2) = 0.9662 for quantitative EASL European Association for the Study of the Liver and quantitative ADC apparent diffusion coefficient , respectively) and a strong intermethod agreement (R(2) = 0.9585). Both methods showed a significantly lower discrepancy with pathologically measured necrosis (residual standard error [ RSE residual standard error ] = 6.38 and 6.33 for quantitative EASL European Association for the Study of the Liver and quantitative ADC apparent diffusion coefficient , respectively), when compared with non- 3D three-dimensional techniques ( RSE residual standard error = 12.18 for visual assessment).

CONCLUSION

This radiologic-pathologic correlation study demonstrates the diagnostic accuracy of 3D three-dimensional quantitative MR imaging techniques in identifying pathologically measured tumor necrosis in HCC hepatocellular carcinoma lesions treated with TACE transarterial chemoembolization .

Manual contouring based volumetric evaluation for colorectal cancer with liver limited metastases: a comparison with RECIST

BACKGROUND

To compare response evaluation criteria in solid tumours (RECIST) and volumetric evaluation (VE) for colorectal cancer with liver-limited metastasis.

PATIENTS AND METHODS

VE of liver metastases was performed by manual contouring before and after chemotherapy on 45 pairs of computed tomography (CT) images in 36 patients who suffered from metastatic colorectal cancer (mCRC) with liver metastasis only. Cohen kappa was used to compare the agreement between VE and RECIST. Pearson correlation was performed for their comparison after cubic root transformation of the aggregate tumor volumes. Logistic regression was done to identify clinical and radiographic factors to account for the difference which may be predictive in overall response (OR).

RESULTS

There were 16 partial response (PR), 23 stable disease (SD) and 6 progressive disease (PD) cases with VE, and 14 PR, 23 SD and 8 PD with RECIST. VE demonstrated good agreement with RECIST (κ=0.779). Discordant objective responses were noted in 6 pairs of comparisons (13.3%). Pearson correlation also showed excellent correlation between VE and RECIST (r2=0.966, p<0.001). Subgroup analysis showed that VE was in slightly better agreement with RECIST for enlarging lesions than for shrinking lesions (r2=0.935 and r2=0.780 respectively). No factor was found predictive of the difference in OR between VE and RECIST.

CONCLUSIONS

VE exhibited good agreement with RECIST. It might be more useful than RECIST in evaluation shrinking lesions in cases of numerous and conglomerate liver metastases.

Functional imaging biomarkers for assessing response to treatment in liver and lung metastases

Management of patients with metastatic cancer and development of new treatments rely on imaging to provide non-invasive biomarkers of tumour response and progression. The widely used size-based criteria have increasingly become inadequate where early measures of response are required to avoid toxicity of ineffective treatments, as biological, physiologic, and molecular modifications in tumours occur before changes in gross tumour size. A multiparametric approach with the current range of imaging techniques allows functional aspects of tumours to be simultaneously interrogated. Appropriate use of these imaging techniques and their timing in relation to the treatment schedule, particularly in the context of clinical trials, is fundamental. There is a lack of consensus regarding which imaging parameters are most informative for a particular disease site and the best time to image so that, despite an increasing body of literature, open questions on these aspects remain. In addition, standardization of these new parameters is required. This review summarizes the published literature over the last decade on functional and molecular imaging techniques in assessing treatment response in liver and lung metastases.

Comparison of response evaluation criteria in solid tumors with volumetric measurements for estimation of tumor burden in pancreatic adenocarcinoma and hepatocellular carcinoma

BACKGROUND

Response evaluation criteria in solid tumors (RECIST) is the accepted method for determining tumor progression. However, RECIST may not estimate disease burden accurately because the axial plane often does not produce the actual longest diameter. Volumetric measurements may be an alternative to better determine tumor size. Our aim was to compare volumetric measurements with RECIST in pancreatic ductal adenocarcinomas (PDA) and hepatocellular carcinomas (HCC).

METHODS

RECIST and volumetric measurements were determined in 9 patients with metastatic PDA and 17 patients with HCC who subsequently underwent liver transplantation. Gross pathologic measurements after hepatectomy also were analyzed for volumes.

RESULTS

Three-dimensional diameter in volumetric analysis was 38% and 36% higher than RECIST diameter in PDA and HCC, respectively (P < .01). However, RECIST yielded 78% and 23% larger estimated tumor volumes than volumetric analysis in PDA and HCC, respectively (P < .01). Gross pathologic volume in HCC showed a linear correlation with both volumetric analysis (r = .95; P < .01) and RECIST (r = .96; P < .01) but RECIST significantly overestimated gross pathologic volume by an average of 28% (P < .01) whereas volumetric analysis was similar to gross pathologic volume (P = .56). In categorizing treatment response in PDA, RECIST and volumetric analysis were in moderate agreement (κ = .49).

CONCLUSIONS

RECIST significantly may overestimate tumor burden compared with volumetric measurements in both PDA and HCC. Volumetric analysis may be the preferred method to detect tumor progression.

Uncertainties in RECIST as a measure of volume for lung nodules and liver tumors

PURPOSE

The authors wish to determine the extent to which the Response Evaluation Criteria in Solid Tumors (RECIST) and the criteria of the World Health Organization (WHO) can predict tumor volumes and changes in volume using clinical data.

METHODS

The data presented are a reanalysis of data acquired in other studies, including the public database from the Lung Image Database Consortium (LIDC) and from a study of liver tumors.

RESULTS

The principal result is that a given RECIST diameter predicts volume to a factor of 16 or 10 for the two data sets, respectively, by examining 95% prediction bounds and that changes in volume are predicted only little better: to within a factor of 7 for the liver data. The WHO criteria reduce the prediction bounds by a factor of 1.3 in all cases. Also, the RECIST threshold of 10 mm to measure a nodule corresponds to a transition zone width of a factor of more than 2 in volume for the nodules in the LIDC database.

CONCLUSIONS

While the RECIST diameter is certainly correlated with the volume, and similarly for changes in these quantities, the use of the diameter introduces additional variation assuming volume is the quantity of interest. Exactly how much this reduces the statistical power of clinical drug trials is a key open question for future research.

Size determination and response assessment of liver metastases with computed tomography--comparison of RECIST and volumetric algorithms

OBJECTIVE

To compare different three-dimensional volumetric algorithms (3D-algorithms) and RECIST for size measurement and response assessment in liver metastases from colorectal and pancreatic cancer.

METHODS

The volumes of a total of 102 liver metastases in 45 patients (pancreatic cancer, n=22; colon cancer, n=23) were estimated using three volumetric methods (seeded region growing method, slice-based segmentation, threshold-based segmentation) and the RECIST 1.1 method with volume calculation based on the largest axial diameter. Each measurement was performed three times by one observer. All four methods were applied to follow-up on 55 liver metastases in 29 patients undergoing systemic treatment (median follow-up, 3.5 months; range, 1-10 months). Analysis of variance (ANOVA) with post hoc tests was performed to analyze intraobserver variability and intermethod differences.

RESULTS

ANOVA showed significant higher volumes calculated according to the RECIST guideline compared to the other measurement methods (p<0.001) with relative differences ranging from 0.4% to 41.1%. Intraobserver variability was significantly higher (p<0.001) for RECIST and threshold based segmentation (3.6-32.8%) compared with slice segmentation (0.4-13.7%) and seeded region growing method (0.6-10.8%). In the follow-up study, the 3D-algorithms and the assessment following RECIST 1.1 showed a discordant classification of treatment response in 10-21% of the patients.

CONCLUSIONS

This study supports the use of volumetric measurement methods due to significant higher intraobserver reproducibility compared to RECIST. Substantial discrepancies in tumor response classification between RECIST and volumetric methods depending on applied thresholds confirm the requirement of a consensus concerning volumetric criteria for response assessment.

Radiologic assessment of response to therapy: comparison of RECIST Versions 1.1 and 1.0

Improvements in radiologic imaging technology and therapeutic options available for management of tumors have necessitated the revision of guidelines for the imaging-based assessment of tumor response to therapy. The purpose of this article is to familiarize radiologists with the modifications to the Response Evaluation Criteria in Solid Tumors (RECIST) that have been incorporated in the latest version of the guidelines, RECIST 1.1. The most important differences between this version and the previous one, RECIST 1.0, include reductions in the maximum number of lesions per patient and per organ that may be targeted for measurement, augmentation of the criteria defining progressive disease, additional guidelines for reporting findings of lesions that are too small to measure and for measuring lesions that appear to have fragmented or coalesced at follow-up imaging, new criteria for characterizing lymphadenopathy, new criteria for selecting bone lesions and cystic lesions as targets for measurement, and the inclusion of findings at positron emission tomography among the indicators of disease response.

Semi-automatic software increases CT measurement accuracy but not response classification of colorectal liver metastases after chemotherapy

OBJECTIVES

This study evaluates intra- and interobserver variability of automatic diameter and volume measurements of colorectal liver metastases (CRLM) before and after chemotherapy and its influence on response classification.

METHODS

Pre-and post-chemotherapy CT-scans of 33 patients with 138 CRLM were evaluated. Two observers measured all metastases three times on pre-and post-chemotherapy CT-scans, using three different techniques: manual diameter (MD), automatic diameter (AD) and automatic volume (AV). RECIST 1.0 criteria were used to define response classification. For each technique, we assessed intra- and interobserver reliability by determining the intraclass correlation coefficient (α-level 0.05). Intra-observer agreement was estimated by the variance coefficient (%). For inter-observer agreement the relative measurement error (%) was calculated using Bland-Altman analysis. In addition, we compared agreement in response classification by calculating kappa-scores (κ) and estimating proportions of discordance between methods (%).

RESULTS

Intra-observer variability was 6.05%, 4.28% and 12.72% for MD, AD and AV, respectively. Inter-observer variability was 4.23%, 2.02% and 14.86% for MD, AD and AV, respectively. Chemotherapy marginally affected these estimates. Agreement in response classification did not improve using AD or AV (MD κ=0.653, AD κ=0.548, AV κ=0.548) and substantial discordance between observers was observed with all three methods (MD 17.8%, AD 22.2%, AV 22.2%).

CONCLUSION

Semi-automatic software allows repeatable and reproducible measurement of both diameter and volume measurements of CRLM, but does not reduce variability in response classification.

MDCT necrosis quantification in the assessment of hepatocellular carcinoma response to yttrium 90 radioembolization therapy: comparison of two-dimensional and volumetric techniques

RATIONALE AND OBJECTIVES

The purpose of this study is to evaluate the reproducibility and agreement of tumor necrosis quantification performed by two-dimensional and volumetric methods in a cohort of patients with hepatocellular carcinoma (HCC) treated with yttrium-90 ((90)Y) radioembolization.

MATERIALS AND METHODS

Twenty-nine consecutive patients (21 men, 8 women; mean age 66.6 years; age range, 44-90 years) with HCC treated with (90)Y radioembolization that underwent liver multidetector computed tomography (MDCT) were included. Two independent radiologists evaluated the necrosis proportion of the lesions with two-dimensional (2D) measurements according to the European Association for the Study of the Liver guidelines, and with a volumetric method using a voxel-by-voxel analysis. Interobserver reproducibility for each method was assessed by using within-subject coefficients of variation (WSCV), intraclass correlation coefficients (ICC), and Lin's concordance correlation coefficients (LCC). Agreement between both methods was assessed by using the Bland-Altman plot and the paired t-test.

RESULTS

The volumetric method was more reproducible (WSCV = 27.8%; ICC = 0.914; LCC = 0.909) than the 2D (WSCV = 43.8%; ICC = 0.723; LCC = 0.841). There was a significant difference in the mean calculated necrosis proportions based on 2D and volumetric methods (P = .0129).

CONCLUSION

Voxel-by-voxel quantification of HCC necrosis is a more reproducible method than 2D analysis.

Evaluation of hepatocellular carcinoma size using two-dimensional and volumetric analysis: effect on liver transplantation eligibility

RATIONALE AND OBJECTIVES

Milan criteria recommends selection of candidates with hepatocellular carcinoma (HCC) for liver transplantation based on strict tumor size thresholds. The purpose of this study is to compare the effect of two-dimensional and three-dimensional tumor measurements on the selection of candidates for liver transplantation using Milan criteria.

MATERIALS AND METHODS

This retrospective Health Insurance Portability and Accountability Act-compliant study was approved by our institutional review board. Patient-informed consent was waived. Forty-five HCCs in 19 patients, evaluated with triphasic multidetector row computed tomography scans, were included in the analysis. The largest diameters in each two-dimensional orthogonal plane (Max2D) and within three-dimensional tumor boundaries (Max3D) were calculated for each lesion. Diameters were compared and the eligibility based on lesion size for liver transplantation was assessed.

RESULTS

The mean Max2D diameter of HCC was 3.2 ± 0.9 cm and the mean Max3D diameter was 3.5 ± 1.2 cm. There was a significant difference between the mean Max2D and Max3D diameters (P < .001). Among the 45 lesions, 22 of them (48.9%) were ineligible for transplantation according to Max2D diameter, whereas 29 of them (64.44%) were ineligible when Max3D diameter was applied (P < .001).

CONCLUSION

HCC diameter based on 3D measurements is significantly different than the conventional 2D measurements and may affect eligibility for liver transplantation.

Pulmonary tumor measurements from x-ray computed tomography in one, two, and three dimensions

RATIONALE AND OBJECTIVES

We evaluated the accuracy and reproducibility of three-dimensional (3D) measurements of lung phantoms and patient tumors from x-ray computed tomography (CT) and compared these to one-dimensional (1D) and two-dimensional (2D) measurements.

MATERIALS AND METHODS

CT images of three spherical and three irregularly shaped tumor phantoms were evaluated by three observers who performed five repeated measurements. Additionally, three observers manually segmented 29 patient lung tumors five times each. Follow-up imaging was performed for 23 tumors and response criteria were compared. For a single subject, imaging was performed on nine occasions over 2 years to evaluate multidimensional tumor response. To evaluate measurement accuracy, we compared imaging measurements to ground truth using analysis of variance. For estimates of precision, intraobserver and interobserver coefficients of variation and intraclass correlations (ICC) were used. Linear regression and Pearson correlations were used to evaluate agreement and tumor response was descriptively compared.

RESULTS

For spherical shaped phantoms, all measurements were highly accurate, but for irregularly shaped phantoms, only 3D measurements were in high agreement with ground truth measurements. All phantom and patient measurements showed high intra- and interobserver reproducibility (ICC >0.900). Over a 2-year period for a single patient, there was disagreement between tumor response classifications based on 3D measurements and those generated using 1D and 2D measurements.

CONCLUSION

Tumor volume measurements were highly reproducible and accurate for irregular, spherical phantoms and patient tumors with nonuniform dimensions. Response classifications obtained from multidimensional measurements suggest that 3D measurements provide higher sensitivity to tumor response.

Tumor volume measurement errors of RECIST studied with ellipsoids

PURPOSE

The authors investigate the extent to which Response Evaluation Criteria in Solid Tumors (RECIST) can predict tumor volumes in ideal geometric settings and using clinical data.

METHODS

The authors consider a hierarchy of models including uniaxial ellipsoids, general ellipsoids, and composites of ellipsoids, using both analytical and numerical techniques to show how well RECIST can predict tumor volumes in each case. The models have certain features that are compared to clinical data.

RESULTS

The principal conclusion is that a change in the reported RECIST value needs to be a factor of at least 1.2 to achieve a 95% confidence that one ellipsoid is larger than another assuming the ratio of maximum to minimum diameters is no more than 2, an assumption that is reasonable for some classes of tumors. There is a significant probability that RECIST will select a tumor other than the largest due to orientation effects of nonspherical tumors: in previously reported malignoma data, RECIST would have selected a tumor other than the largest in 9% of the cases. Also, the widely used spherical model connecting RECIST values for a single tumor to volumes overestimates these volumes.

CONCLUSIONS

RECIST imposes a limit on the ability to determine tumor volumes, which is greater than the limit imposed by modem medical computed tomography machines. It is also likely the RECIST limit is above natural biological variability of stable lesions. The authors recommend the study of such natural variability as a fruitful avenue for further study.

Morphological and functional MDCT: problem-solving tool and surrogate biomarker for hepatic disease clinical care and drug discovery in the era of personalized medicine

This article explains the significant role of morphological and functional multidetector computer tomography (MDCT) in combination with imaging postprocessing algorithms served as a problem-solving tool and noninvasive surrogate biomarker to effectively improve hepatic diseases characterization, detection, tumor staging and prognosis, therapy response assessment, and novel drug discovery programs, partial liver resection and transplantation, and MDCT-guided interventions in the era of personalized medicine. State-of-the-art MDCT depicts and quantifies hepatic disease over conventional CT for not only depicting lesion location, size, and extent but also detecting changes in tumor biologic behavior caused by therapy or tumor progression before morphologic changes. Color-encoded parameter display provides important functional information on blood flow, permeability, leakage space, and blood volume. Together with other relevant biomarkers and genomics, the imaging modality is being developed and validated as a biomarker to early response to novel, targeted anti-VEGF(R)/PDGFR or antivascular/angiogenesis agents as its parameters correlate with immunohistochemical surrogates of tumor angiogenesis and molecular features of malignancies. MDCT holds incremental value to World Health Organization response criteria and Response Evaluation Criteria in Solid Tumors in liver disease management. MDCT volumetric measurement of future remnant liver is the most important factor influencing the outcome of patients who underwent partial liver resection and transplantation. MDCT-guided interventional methods deliver personalized therapies locally in the human body. MDCT will hold more scientific impact when it is fused with other imaging probes to yield comprehensive information regarding changes in liver disease at different levels (anatomic, metabolic, molecular, histologic, and other levels).