Evaluation of the prognostic effectiveness of liver metastasis volume by volumetric measurement in colorectal cancer.

Aim: To evaluate the relationship between liver metastasis volume and survival in colorectal cancer patients using the volumetric measurement method.Methods: 114 colorectal cancer patients with isolated liver metastases were included in the study. Liver tumor volume, total liver volume were calculated from the patients images at the time of diagnosis. Vitrea 7.14 imaging software was used for liver volume analysis and volume analysis of each metastasis.Results: Median overall survival(OS) in the group with tumor volume <42 ml3 was 30.98 months In the group with tumor volume ≥42 ml3, median OS was 16.36 months (p: 0.001). In patients who underwent metastasectomy, the median OS in the group with a tumor volume <42 ml3 was 52.3 months, the median OS in the group with a tumor volume ≥42 ml3 was 22.2 months. In patients who did not undergo metastasectomy, the median OS in the <42 ml3 group was 20.23 months, the median OS in the ≥42 ml3 group was 15.63 months.Conclusion: In our study, we found that liver metastasis volume was prognostic for OS. It is argued that tumor volume measurement by volumetric measurement is a widely used method in the decision for metastasectomy in liver metastatic colorectal cancer patients.

[Box: see text].

Multivariate joint frailty model for the analysis of nonlinear tumor kinetics and dynamic predictions of death.

The Response Evaluation Criteria in Solid Tumors are used as standard guidelines for the clinical evaluation of cancer treatments. The assessment is based on the anatomical tumor burden: change in size of target lesions and evolution of nontarget lesions (NTL). Despite unquestionable advantages of this standard tool, Response Evaluation Criteria in Solid Tumors are subject to some limitations such as categorization of continuous tumor size or negligence of its longitudinal trajectory. In particular, it is of interest to capture its nonlinear shape and model it simultaneously with recurrent progressions of NTL and overall survival. We propose a multivariate nonlinear mechanistic joint frailty model for longitudinal data, recurrent events, and a terminal event. In the model, the tumor size trajectory is described using an ordinary differential equation that accounts for the natural growth and treatment-induced decline. We perform a simulation study to validate the method and apply the model to a phase III clinical trial in colorectal cancer. In the results of the analysis, we determine on which component, tumor size, NTL, or death the treatment acts mostly and perform dynamic predictions of death. We compare the model with other models that consider parametric functions or splines for the tumor size trajectory in terms of goodness of fit and predictive accuracy.

Joint model for left-censored longitudinal data, recurrent events and terminal event: Predictive abilities of tumor burden for cancer evolution with application to the FFCD 2000-05 trial.

In oncology, the international WHO and RECIST criteria have allowed the standardization of tumor response evaluation in order to identify the time of disease progression. These semi-quantitative measurements are often used as endpoints in phase II and phase III trials to study the efficacy of new therapies. However, through categorization of the continuous tumor size, information can be lost and they can be challenged by recently developed methods of modeling biomarkers in a longitudinal way. Thus, it is of interest to compare the predictive ability of cancer progressions based on categorical criteria and quantitative measures of tumor size (left-censored due to detection limit problems) and/or appearance of new lesions on overall survival. We propose a joint model for a simultaneous analysis of three types of data: a longitudinal marker, recurrent events, and a terminal event. The model allows to determine in a randomized clinical trial on which particular component treatment acts mostly. A simulation study is performed and shows that the proposed trivariate model is appropriate for practical use. We propose statistical tools that evaluate predictive accuracy for joint models to compare our model to models based on categorical criteria and their components. We apply the model to a randomized phase III clinical trial of metastatic colorectal cancer, conducted by the Fédération Francophone de Cancérologie Digestive (FFCD 2000-05 trial), which assigned 410 patients to two therapeutic strategies with multiple successive chemotherapy regimens.

An Investigation Into the Effect of Different Static Magnetic Fields of 1.5-T and 3.0-T MRI on the Measurement of Tumor Diameters in Breast Cancer.

Objective This study aimed to determine whether differences in the static field strength of 1.5-T and 3.0-T MRI systems affect the diagnostic results of tumor size measurement in breast cancer and to compare them with the results of tumor size in surgical pathology diagnosis. Methods We adopted a retrospective and case-control study design. We included patients with a suspected or confirmed diagnosis of breast cancer who underwent breast MRI at our hospital between January 2017 and March 2023. Diffusion-weighted imaging (DWI), gadolinium-enhanced T1-weighted (Gd-T1WI) MRI, and tumor size from surgical pathology were compared via a significance difference test and correlation analysis between the two groups. In this study, the maximum diameters of the tumor obtained by DWI and Gd-T1WI on 1.5-T and 3.0-T MRI systems were divided by the maximum diameter from surgical pathology diagnosis to arrive at the tumor ratio index. Results A total of 36 patients met the selection criteria: 15 for the 1.5-T system and 21 for the 3.0-T system; all of them were female. The mean ratio of pathological tumor length to diameter measured by MRI for each system showed no significant difference between the groups (p=0.653). For the 1.5-T MRI system, the ratio of tumor length diameter by DWI to that by pathology was 1.042 ±0.361, and the ratio of tumor length diameter by Gd-T1WI to that by pathology was 1.107 ±0.314, with no significant difference observed between ratios (p=0.345). The correlation coefficient between them was r=0.730 (p=0.002). For the 3.0-T MRI system, the ratio of tumor length diameter by DWI to that by pathology was 0.893 ±0.197, while the ratio of tumor length diameter by Gd-T1WI to that by pathology was 1.062 ±0.177, with a significant difference between the two (p<0.001). The correlation coefficient between the two groups was 0.695 (p<0.001). Conclusions While there was no significant difference in the ratios of tumor length diameter measured by 1.5-T Gd-T1WI and DWI compared to pathology, there was a significant difference in the ratios of tumor length diameter measured by 3.0-T DWI and Gd-T1WI compared to pathology. Hence, only 3.0-T DWI can lead to a potential underestimation of tumor length.

Evaluation of Intratumoral Response Heterogeneity in Metastatic Colorectal Cancer and Its Impact on Patient Overall Survival: Findings from 10,551 Patients in the ARCAD Database.

Metastatic colorectal cancer (mCRC) is a heterogeneous disease that can evoke discordant responses to therapy among different lesions in individual patients. The Response Evaluation Criteria in Solid Tumors (RECIST) criteria do not take into consideration response heterogeneity. We explored and developed lesion-based measurement response criteria to evaluate their prognostic effect on overall survival (OS). PATIENTS AND METHODS: Patients enrolled in 17 first-line clinical trials, who had mCRC with ≥ 2 lesions at baseline, and a restaging scan by 12 weeks were included. For each patient, lesions were categorized as a progressing lesion (PL: > 20% increase in the longest diameter (LD)), responding lesion (RL: > 30% decrease in LD), or stable lesion (SL: neither PL nor RL) based on the 12-week scan. Lesion-based response criteria were defined for each patient as follows: PL only, SL only, RL only, and varied responses (mixture of RL, SL, and PL). Lesion-based response criteria and OS were correlated using stratified multivariable Cox models. The concordance between OS and classifications was measured using the C statistic. RESULTS: Among 10,551 patients with mCRC from 17 first-line studies, varied responses were noted in 51.6% of patients, among whom, 3.3% had RL/PL at 12 weeks. Among patients with RL/SL, 52% had stable disease (SD) by RECIST 1.1, and they had a longer OS (median OS (mOS) = 19.9 months) than those with SL only (mOS = 16.8 months, HR (95% CI) = 0.81 (0.76, 0.85), p < 0.001), although a shorter OS than those with RL only (mOS = 25.8 months, HR (95% CI) = 1.42 (1.32, 1.53), p < 0.001). Among patients with SL/PL, 74% had SD by RECIST 1.1, and they had a longer OS (mOS = 9.0 months) than those with PL only (mOS = 8.0 months, HR (95% CI) = 0.75 (0.57, 0.98), p = 0.040), yet a shorter OS than those with SL only (mOS = 16.8 months, HR (95% CI) = 1.98 (1.80, 2.18), p < 0.001). These associations were consistent across treatment regimen subgroups. The lesion-based response criteria showed slightly higher concordance than RECIST 1.1, although it was not statistically significant. CONCLUSION: Varied responses at first restaging are common among patients receiving first-line therapy for mCRC. Our lesion-based measurement criteria allowed for better mortality discrimination, which could potentially be informative for treatment decision-making and influence patient outcomes.

Which evaluation criteria of the short-term efficacy can better reflect the long-term outcomes for patients with nasopharyngeal carcinoma?

PURPOSE: To compare the consistency of one-dimensional Response Evaluation Criteria in Solid Tumors (1D-RECIST), two-dimensional WHO criteria (2D-WHO), and three-dimensional (3D) measurement for therapeutic response assessment of nasopharyngeal carcinoma (NPC). MATERIALS AND METHODS: Retrospective data of 288 newly diagnosed NPC patients were reviewed. Tumor size was assessed on magnetic resonance imaging (MRI) according to the 1D-RECIST, 2D-WHO, and 3D measurement criteria. Agreement between tumor responses was assessed using unweighted k statistics. The receiver operating characteristic (ROC) curve was used to determine the optimal cut-off point of the PTV. The Kaplan-Meier method and Cox regression were used for the survival analysis. RESULTS: The optimal cut-off point of the PTV for progression-free survival (PFS) was 29.6%. Agreement with PTV measurement was better for 1D measurement than for 2D and 3D measurements (kappa values of 0.646, 0.537, and 0.577 for 1D, 2D, and 3D measurements, respectively; P < 0.05). The area under the curve of the 1D measurement (AUC=0.596) was similar to that of the PTV measurement (AUC=0.621). Compared with 2D and 3D measurements, 1D measurement is superior for predicting prognosis in NPC (C-index of 0.672, 0.663, and 0.646 were for 1D, 2D, and 3D measurements, respectively; P < 0.005). Survival analysis showed that patients with non-responders had worse prognosis (P < 0.05). CONCLUSIONS: The 1D measurement more closely agreed with the PTV measurement than the 2D and 3D measurements for predicting therapeutic responses in NPC. Therefore, we recommend using the less time-consuming 1D-RECIST criteria in routine clinical practice.

Imaging in pleural mesothelioma: A review of the 15th International Conference of the International Mesothelioma Interest Group.

Imaging of mesothelioma plays a role in all aspects of patient management, including disease detection, staging, evaluation of treatment options, response assessment, pre-surgical evaluation, and surveillance. Imaging in this disease impacts a wide range of disciplines throughout the healthcare enterprise. Researchers and clinician-scientists are developing state-of-the-art techniques to extract more of the information contained within these medical images and to utilize it for more sophisticated tasks; moreover, image-acquisition technology is advancing the inherent capabilities of these images. This paper summarizes the imaging-based topics presented orally at the 2021 International Conference of the International Mesothelioma Interest Group (iMig), which was held virtually from May 7-9, 2021. These topics include an update on the mesothelioma staging system, novel molecular targets to guide therapy in mesothelioma, special considerations and potential pitfalls in imaging mesothelioma in the immunotherapy setting, tumor measurement strategies and their correlation with patient survival, tumor volume measurement in MRI and CT, CT-based texture analysis for differentiation of histologic subtype, diffusion-weighted MRI for the assessment of biphasic mesothelioma, and the prognostic significance of skeletal muscle loss with chemotherapy.

Modeling tumor measurement data to predict overall survival (OS) in cancer clinical trials.

INTRODUCTION: Longitudinal tumor measurements (TM) are commonly recorded in cancer clinical trials of solid tumors. To define patient response to treatment, the Response Evaluation Criteria in Solid Tumors (RECIST) categorizes the otherwise continuous measurements, which results in substantial information loss. We investigated two modeling approaches to incorporate all available cycle-by-cycle (continuous) TM to predict overall survival (OS) and compare the predictive accuracy of these two approaches to RECIST. MATERIAL AND METHODS: Joint modeling (JM) for longitudinal TM and OS and two-stage modeling with potential time-varying coefficients were utilized to predict OS using data from three trials with cycle-by-cycle TM. The JM approach incorporates TM data collected throughout the course of the clinical trial. The two-stage modeling approach incorporates information from early assessments (before 12 weeks) to predict subsequent OS outcome. The predictive accuracy was quantified by c-indices. RESULTS: Data from 577, 337, and 126 patients were included for the analysis (from two stage IV colorectal cancer trials (N9741, N9841) and an advanced non-small cell lung cancer trial (N0026), respectively). Both the JM and two-stage modeling reached a similar conclusion, i.e. the baseline covariates (age, gender, and race) were mostly not predictive of OS (p-value > 0.05). Quantities derived from TM were strong predictors of OS in the two colorectal cancer trials (p < 0.001 for both association in JM and two-stage modeling parameters); but less so in the lung cancer trial (p = 0.053 for association in JM and p = 0.024 and 0.160 for two-stage modeling parameters). The c-indices from the two-stage modeling were higher than those from a model using RECIST (range: 0.611-0.633 versus 0.586-0.590). The dynamic c-indices from the JM were in the range of 0.627-0.683 indicating good predictive accuracy. CONCLUSION: Both modeling approaches provide highly interpretable and clinical meaningful results; the improved predictive performance compared with RECIST indicates the possibility of deriving better trial endpoints from these approaches.

Comparing the extent of breast cancer tumors through contrast-enhanced ultrasound vs B-mode, opposed with pathology: evergreen study.

BACKGROUND: To prove the efficacy of contrast-enhanced ultrasound (CEUS) in determining the extent of resection, more evidence about B-mode and CEUS as opposed to pathology is required. We compared maximum tumor width measured on B-mode/CEUS images with that determined pathologically. METHODS: In this retrospective multicenter study, 152 operable breast cancer patients who had undergone both B-mode and CEUS were analyzed. Maximum tumor width on B-mode and CEUS, and on the postoperative pathological examination (P), was measured by the participating investigators. In addition, maximum width was assessed in B-mode and CEUS image sets by independent reviewers blinded to all patient information. We analyzed differences in maximum width between CEUS, B-mode and P. RESULTS: The mean widths as measured by the participating investigators were 15 ± 7 mm (B-mode), 19 ± 8 mm (CEUS), and 17 ± 9 mm (P). The difference subtracted P from B-mode was - 3 ± 7 mm (p < 0.0001), and that from CEUS was 1 ± 6 mm (p = 0.0163). The mean widths as measured by the independent reviewers were 16 ± 7 mm (B-mode) and 18 ± 7 mm (CEUS). The difference subtracted P from B-mode was - 2 ± 8 mm (p = 0.0114), while that from CEUS was 1 ± 7 mm (p = 0.1921). CONCLUSIONS: Maximum lesion width measurement showed a tendency to increase in the order of B-mode, to P and CEUS. The difference in measurement between P and B-mode was significant, but there was no significant between CEUS and P. These results provide additional information of tendency patterns in measuring the maximum lesion width through enhancement on CEUS.

The role of volumetric method in the assessment of chemotherapy response and predicting survival in malignant pleural mesothelioma.

BACKGROUND: Malignant pleural mesothelioma (MPM) is a pleural tumor with high mortality rate and short-term survival expectancy after diagnosis. Assessment of the response to chemotherapy, which is the first choice in treatment of MPM, is important for the transition to alternative chemotherapy protocols and immunotherapy. There is no clarity in the response to chemotherapy treatment. OBJECTIVE: Our study aims to compare the assessment of chemotherapy response using the Modified Response Evaluation Criteria in Solid Tumors (mRECIST) criteria and volumetric measurements and to correlate with median survival. MATERIALS AND METHODS: Thirty-two patients (16 females and 16 males) were included in the study, and their ages ranged from 28 to 78 years. Chemotherapy response was determined by both mRECIST and volumetric approach. Tumor volume was measured by linear interpolation and semi-automatic segmentation. Log-rank multiple cutoff analysis was used to determine appropriate cutoff values of volumetric response criteria. RESULTS: According to both mRECIST and volumetric approach, median survival times in partial response, stable disease, and progressive disease groups were 24, 15, and 9 months, respectively. The survival times of the three groups were different (logrank: 17.76; P < 0.001) by mRECIST. The survival of the progressive disease group was shorter than that of the other groups (logrank: 18.91; P < 0.001) by volumetric approach. CONCLUSIONS: In the assessment of chemotherapy response, even though classifications obtained according to the mRECIST criteria and volumetric measurements are statistically compatible, we think that the measurement of the volumetric values will increase the standardization. In our study, threshold values for volumetric measurements were determined; however, these values should be supported by large-scale multicenter studies.

Deep learning for semi-automated unidirectional measurement of lung tumor size in CT.

BACKGROUND: Performing Response Evaluation Criteria in Solid Tumor (RECISTS) measurement is a non-trivial task requiring much expertise and time. A deep learning-based algorithm has the potential to assist with rapid and consistent lesion measurement. PURPOSE: The aim of this study is to develop and evaluate deep learning (DL) algorithm for semi-automated unidirectional CT measurement of lung lesions. METHODS: This retrospective study included 1617 lung CT images from 8 publicly open datasets. A convolutional neural network was trained using 1373 training and validation images annotated by two radiologists. Performance of the DL algorithm was evaluated 244 test images annotated by one radiologist. DL algorithm's measurement consistency with human radiologist was evaluated using Intraclass Correlation Coefficient (ICC) and Bland-Altman plotting. Bonferroni's method was used to analyze difference in their diagnostic behavior, attributed by tumor characteristics. Statistical significance was set at p < 0.05. RESULTS: The DL algorithm yielded ICC score of 0.959 with human radiologist. Bland-Altman plotting suggested 240 (98.4 %) measurements realized within the upper and lower limits of agreement (LOA). Some measurements outside the LOA revealed difference in clinical reasoning between DL algorithm and human radiologist. Overall, the algorithm marginally overestimated the size of lesion by 2.97 % compared to human radiologists. Further investigation indicated tumor characteristics may be associated with the DL algorithm's diagnostic behavior of over or underestimating the lesion size compared to human radiologist. CONCLUSIONS: The DL algorithm for unidirectional measurement of lung tumor size demonstrated excellent agreement with human radiologist.

Missing tumor measurement (TM) data in the search for alternative TM-based endpoints in cancer clinical trials.

PURPOSE: Missing data commonly occur in cancer clinical trials (CCT) and may hinder the search for alternative trial endpoints. We consider reasons for missing tumor measurement (TM) data in CCT and how missing TM data are typically handled. We explore the potential impact of missing TM data on predictive ability of a set of TM-based endpoints. METHODS: Literature review identifies reasons for and approaches to handling missing TM data. Data from 3 actual clinical trials were used for illustration. A sensitivity analysis of the potential impact of missing TM data was performed by comparing overall survival (OS) predictive ability of alternative endpoints using observed and imputed data. RESULTS: Reasons for missing TM data in CCT are presented, based on the literature review and the three trials. Although missing TM data impacted individual objective status (e.g. 12-week status changed for 53% of patients in one imputation set), it surprisingly only minimally impacted endpoint predictive ability (e.g. median c-indices of 500 imputed datasets ranged from 0.566 to 0.570 for N9741, 0.592-0.616 for N9841, and 0.542-0.624 for N0026). CONCLUSION: By understanding the reasons for missingness, we can better anticipate them and minimize their occurrence. Our preliminary analysis suggests missing TM data may not impact endpoint predictive ability, but could impact objective response status classification; however these findings require further validation. With response status accepted as an important phase II endpoint in the development of new cancer therapies (including immunotherapy), we urge that in CCT complete TM data collection and adherence to protocol-defined disease evaluation as closely as possible be a priority.

Revised Modified Response Evaluation Criteria in Solid Tumors for Assessment of Response in Malignant Pleural Mesothelioma (Version 1.1).

INTRODUCTION: Malignant pleural mesothelioma poses unique difficulties in tumor measurement and response assessment; however, robust and reproducible assessment of response is critically important in the conduct, interpretation, and reporting of clinical trials. METHODS: The current de facto standard for the assessment of mesothelioma tumor response, "modified RECIST" (Response Evaluation Criteria in Solid Tumors), was published in 2004 as a research paper. Practical application of the modified RECIST guidelines has suffered from varied interpretations, resulting in inaccuracies and inconsistencies in tumor response assessment across and within mesothelioma clinical trials. The presented "modified RECIST 1.1 for mesothelioma" response assessment guidelines provide a much-needed update that incorporates recommendations from RECIST 1.1 and approaches to other practical issues, including: (1) definition of minimally measurable disease; (2) definition of measurable lesions; (3) acceptable measurement location; (4) non-pleural disease considerations; (5) characterization of non-measurable pleural disease; (6) assessment of pathological lymph nodes; (7) establishing progressive disease; and (8) accommodations for bilateral pleural disease. RESULTS: These modified RECIST 1.1 guidelines for mesothelioma tumor response collate and apply research published since the development of modified RECIST, align modified RECIST with RECIST 1.1, address those aspects of tumor measurement that were neglected or not well characterized in the modified RECIST paper, and clarify ambiguous or difficult measurement issues that have been highlighted through the subsequent decade of clinical trials research. CONCLUSION: Adoption of the modified RECIST 1.1 guidelines for mesothelioma is recommended to harmonize the application of tumor measurement and response assessment across the next generation of clinical trials in this disease.

Unidimensional measurement may be superior to assess primary tumor response after neoadjuvant chemotherapy for nasopharyngeal carcinoma.

Application of current response evaluation criteria in solid tumors (RECIST 1.1) for assessment of irregularly shaped nasopharyngeal carcinoma (NPC) is a gray area with much ambiguity. Our aim was to compare unidimensional measurements (UDM) and bidimensional measurements (BDM) on magnetic resonance images in alternative planes for measurement of tumor response after neoadjuvant chemotherapy (NACT) in patients with locally advanced NPC. 59 patients with untreated non-metastatic NPC were prospectively enrolled. The size or change in size of the primary tumor and retropharyngeal nodes was assessed by UDM and BDM on axial and coronal planes before and after 2 cycles of NACT. Tumor volume was considered as the reference standard. Correlation between volume and diameter was analyzed using a general linear model. The degree of agreement and discordance of response classification based on different measures were evaluated with κ statistic and McNemar's test, respectively. Both axial UDM (RECIST 1.1) and axial BDM (WHO) showed a significant association with volumetric standard. However, the agreement of axial UDM with VM was better than that of axial BDM (κ value: 0.514 to 0.372). In addition, when increasing coronal planes to evaluate tumor response with UDM and BDM, an inferior agreement between coronal BDM and VM was still observed. Notably, coronal UDM showed the best consistency with volume (κ = 0.585). Hence, axial UDM showed better correlation with volumetric measurements than axial BDM. Since coronal UDM showed high correlation to VM, we suggest further research to assess its use for response assessment of NPC after NACT.

In vivo Efficacy Studies in Cell Line and Patient-derived Xenograft Mouse Models.

In vivo xenograft models derived from human cancer cells have been a gold standard for evaluating the genetic drivers of cancer and are valuable preclinical models for evaluating the efficacy of cancer therapeutics. Recently, patient-derived tumorgrafts from multiple tumor types have been developed and shown to more accurately recapitulate the molecular and histological heterogeneity of cancer. Here we detail the procedures for developing patient-derived xenograft models from breast cancer tissue, cell-based xenograft models, serial tumor transplantation, tumor measurement, and drug treatment.

Can circulating tumor DNA be used for direct and early stage cancer detection?

In the August 16th issue of Science Translational Medicine, Phallen et al propose a method for early cancer diagnosis by using circulating tumor DNA (1). One major advance of this paper includes optimized sequencing of cell-free/circulating tumor DNA (ctDNA) without knowledge of tumor mutations. Evaluation of 200 patients with colorectal, breast, lung and ovarian cancer revealed mutations in ctDNA in approx. 60-70% of all patients, including stage 1 and stage 2 disease. If this data can be reproduced in asymptomatic individuals, they will likely have a major impact on early cancer detection and patient outcomes. In this commentary, we examine the feasibility of this approach for detecting small, asymptomatic tumors, based on previously published empirical data.

Comparison of 1D, 2D, and 3D nodule sizing methods by radiologists for spherical and complex nodules on thoracic CT phantom images.

RATIONALE AND OBJECTIVES: To estimate and statistically compare the bias and variance of radiologists measuring the size of spherical and complex synthetic nodules. MATERIALS AND METHODS: This study did not require the institutional review board approval. Six radiologists estimated the size of 10 synthetic nodules embedded within an anthropomorphic thorax phantom from computed tomography scans at 0.8- and 5-mm slice thicknesses. The readers measured the nodule size using unidimensional (1D) longest in-slice dimension, bidimensional (2D) area from longest in-slice and longest perpendicular dimension, and three-dimensional (3D) semiautomated volume. Intercomparisons of bias (difference between average and true size) and variance among methods were performed after converting the 2D and 3D estimates to a compatible 1D scale. RESULTS: The relative biases of radiologists with the 3D tool were -1.8%, -0.4%, -0.7%, -0.4%, and -1.6% for 10-mm spherical, 20-mm spherical, 20-mm elliptical, 10-mm lobulated, and 10-mm spiculated nodules compared to 1.4%, -0.1%, -26.5%, -7.8%, and -39.8% for 1D. The three-dimensional measurements were significantly less biased than 1D for elliptical, lobulated, and spiculated nodules. The relative standard deviations for 3D were 7.5%, 3.9%, 3.6%, 9.7%, and 8.3% compared to 5.7%, 2.6%, 20.3%, 5.3%, and 16.4% for 1D. Unidimensional sizing was significantly less variable than 3D for the lobulated nodule and significantly more variable for the ellipsoid and spiculated nodules. Three-dimensional bias and variability were smaller for thin 0.8-mm slice data compared to thick 5.0-mm data. CONCLUSIONS: The study shows that radiologist-controlled 3D volumetric lesion sizing can not only achieve smaller bias but also achieve similar or smaller variability compared to 1D sizing, especially for complex lesion shapes.

Tumor response assessment by measuring the single largest lesion per organ in patients with advanced non-small cell lung cancer.

BACKGROUND: The criterion of two target lesions per organ in the RECIST 1.1 is an arbitrary one, not being supported by any objective evidence. We compared tumor responses, respectively, using the RECIST 1.1 (measuring two target lesions per organ) and modified RECIST 1.1 (measuring the single largest lesion in each organ) in patients with advanced non-small cell lung cancer (NSCLC). MATERIALS AND METHODS: We reviewed medical records of patients with advanced NSCLC who received a first-line chemotherapy between January 2004 and December 2013 and compared tumor responses according to the two criteria using computed tomography. RESULTS: A total of 64 patients who had at least two target lesions in any organ according to the RECIST 1.1 were included in the study. The differences in the percentage changes of the sum of tumor measurements between the RECIST 1.1 and mRECIST 1.1 were all within 10%. Thirty-three patients (51.6%) showed an increase in the absolute value of the percentage change when adopting the mRECIST 1.1, instead of the RECIST 1.1. The tumor responses showed high concordance between the two criteria (k=0.899). Only three patients (4.7%) showed disagreement of the responses between the RECIST 1.1 and mRECIST 1.1. The overall response rates (20.3% vs. 20.3%) and disease control rates (89.1% vs. 90.6%) of first-line chemotherapy were not significantly different between the two criteria. CONCLUSION: The modified RECIST 1.1 was comparable to the original RECIST 1.1 in the response assessment of patients with advanced NSCLC. Our result suggests that it may be possible to measure the single largest target lesion per organ for evaluation of the best tumor response.

Accuracy of an automated breast volume ultrasound system for assessment of the pre-operative extent of pure ductal carcinoma in situ: comparison with a conventional handheld ultrasound examination.

The goal of the study described here was to compare the accuracy of an automated breast volume scanner (ABVS) with that of hand-held ultrasound (HHUS) in assessing the pre-operative extent of pure ductal carcinoma in situ (DCIS). This prospective study consisted of 33 patients with histopathologically proven pure DCIS who received conventional HHUS and ABVS examinations. The discrepancy and correlation coefficients were calculated to assess differences in sizes determined by imaging and histopathologic examination. Mean age was 51.8 y. Mean lesion size as assessed with the ABVS did not differ significantly from that determined by histopathology. Lesion size was adequately estimated, under-estimated or over-estimated with the ABVS in 64%, 15% and 21% of patients, and with HHUS in 42%, 15% and 42%, respectively (p < 0.05). The coefficient of correlation between histopathologic and ABVS measurements was higher than that between histopathologic and HHUS measurements. The ABVS appears to assess the extent of the lesion better than HHUS and can provide more accurate information pre-operatively.