Automated evaluation of masseter muscle volume: deep learning prognostic approach in oral cancer

BACKGROUND

Sarcopenia has been identified as a potential negative prognostic factor in cancer patients. In this study, our objective was to investigate the relationship between the assessment method for sarcopenia using the masseter muscle volume measured on computed tomography (CT) images and the life expectancy of patients with oral cancer. We also developed a learning model using deep learning to automatically extract the masseter muscle volume and investigated its association with the life expectancy of oral cancer patients.

METHODS

To develop the learning model for masseter muscle volume, we used manually extracted data from CT images of 277 patients. We established the association between manually extracted masseter muscle volume and the life expectancy of oral cancer patients. Additionally, we compared the correlation between the groups of manual and automatic extraction in the masseter muscle volume learning model.

RESULTS

Our findings revealed a significant association between manually extracted masseter muscle volume on CT images and the life expectancy of patients with oral cancer. Notably, the manual and automatic extraction groups in the masseter muscle volume learning model showed a high correlation. Furthermore, the masseter muscle volume automatically extracted using the developed learning model exhibited a strong association with life expectancy.

CONCLUSIONS

The sarcopenia assessment method is useful for predicting the life expectancy of patients with oral cancer. In the future, it is crucial to validate and analyze various factors within the oral surgery field, extending beyond cancer patients.

Efficacy, mechanism, and safety of melatonin-loaded on thermosensitive nanogels for rabbit VX2 tumor embolization: A novel design

Transarterial chemoembolization (TACE) has been widely used for hepatocellular carcinoma. Reducing hypoxia in the tumor microenvironment after TACE remains a challenge as tumor progression is common in post-TACE patients due to the hypoxic tumor microenvironment. In this study, melatonin loaded on p(N-isopropyl-acrylamide-co-butyl methylacrylate) (PIB-M) was used for tumor embolism. Two types of human hepatoma cell lines were used to explore the mechanism by which melatonin prevents the growth and metastasis of cancer cells in vitro. A VX2 rabbit tumor model was used to evaluate the efficacy, mechanism, and safety of PIB-M in vivo. We found that under hypoxic condition, melatonin could inhibit tumor cell proliferation and migration by targeting hypoxia inducible factor-1α (HIF-1α) and vascular endothelial growth factor A (VEGF-A) in vitro. In vivo, PIB-M inhibited tumor growth and metastasis in rabbit VX2 tumors by promoting apoptosis of tumor cells and targeting related angiogenic proteins and vascular permeability proteins. A high concentration of melatonin in the PIB-M group could be maintained in tumor tissue for 72 h after embolization. The liver and kidney functions were most damaged on the first day but recovered to normal on the seventh day after embolization in the PIB-M group. This novel method may open avenues for reduction of tumor growth and metastasis after TACE and is efficacy and safety, which may be used for treatment for other solid tumors and clinical translation.

RECIST 1.1 Target Lesion Categorical Response in Metastatic Renal Cell Carcinoma: A Comparison of Conventional versus Volumetric Assessment

Purpose To investigate Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST 1.1) approximations of target lesion tumor burden by comparing categorical treatment response according to conventional RECIST versus actual tumor volume measurements of RECIST target lesions. Materials and Methods This is a retrospective cohort study of individuals with metastatic renal cell carcinoma enrolled in a clinical trial (from 2003 to 2017) and includes individuals who underwent baseline and at least one follow-up chest, abdominal, and pelvic CT study and with at least one target lesion. Target lesion volume was assessed by (a) Vmodel, a spherical model of conventional RECIST 1.1, which was extrapolated from RECIST diameter, and (b) Vactual, manually contoured volume. Volumetric responses were determined by the sum of target lesion volumes (Vmodel-sum TL and Vactual-sum TL, respectively). Categorical volumetric thresholds were extrapolated from RECIST. McNemar tests were used to compare categorical volume responses. Results Target lesions were assessed at baseline (638 participants), week 9 (593 participants), and week 17 (508 participants). Vmodel-sum TL classified more participants as having progressive disease (PD), compared with Vactual-sum TL at week 9 (52 vs 31 participants) and week 17 (57 vs 39 participants), with significant overall response discordance (P < .001). At week 9, 25 (48%) of 52 participants labeled with PD by Vmodel-sum TL were classified as having stable disease by Vactual-sum TL. Conclusion A model of RECIST 1.1 based on a single diameter measurement more frequently classified PD compared with response assessment by actual measured tumor volume. Keywords: Urinary, Kidney, Metastases, Oncology, Tumor Response, Volume Analysis, Outcomes Analysis ClinicalTrials.gov registration no. NCT01865747 © RSNA, 2023 Supplemental material is available for this article.

Drug-based therapy for advanced adenoid cystic carcinoma: Current landscape and challenges based on an overview of registered clinical trials

Adenoid cystic carcinoma (ACC) has a significant patient-population in need of effective systemic therapy, as no drug is currently approved by the FDA for its management. We critically reviewed ACC-clinical trials (CT) registered on the ClinicalTrials.gov website using "ACC" under condition or disease. Trials specifically designed to test a drug-based therapy for ACC (n = 33) were analyzed with most being one-arm phase II trials enrolling advanced, recurrent/metastatic, incurable ACC cases. Site restriction, maximum ECOG status, and period of disease progression varied as inclusion criteria. Small-molecule inhibitors were those most commonly investigated with Apatinib, Axitinib and Lenvatinib showing the best results in association with rigid enrollment criteria. The overall median time to progression remains modest and more efforts are urgently needed in this field. CTs designed to test drugs that act on key pathways associated with ACC aggressiveness are being conducted and represent a promising pathway if efficacy is proved.

Mmp12 Is Upregulated by in utero Second-Hand Smoke Exposures and Is a Key Factor Contributing to Aggravated Lung Responses in Adult Emphysema, Asthma, and Lung Cancer Mouse Models

Matrix metalloproteinase-12 (Mmp12) is upregulated by cigarette smoke (CS) and plays a critical role in extracellular matrix remodeling, a key mechanism involved in physiological repair processes, and in the pathogenesis of emphysema, asthma, and lung cancer. While cigarette smoking is associated with the development of chronic obstructive pulmonary diseases (COPD) and lung cancer, in utero exposures to CS and second-hand smoke (SHS) are associated with asthma development in the offspring. SHS is an indoor air pollutant that causes known adverse health effects; however, the mechanisms by which in utero SHS exposures predispose to adult lung diseases, including COPD, asthma, and lung cancer, are poorly understood. In this study, we tested the hypothesis that in utero SHS exposure aggravates adult-induced emphysema, asthma, and lung cancer.

Methods: Pregnant BALB/c mice were exposed from gestational days 6–19 to either 3 or 10mg/m³ of SHS or filtered air. At 10, 11, 16, or 17weeks of age, female offspring were treated with either saline for controls, elastase to induce emphysema, house-dust mite (HDM) to initiate asthma, or urethane to promote lung cancer. At sacrifice, specific disease-related lung responses including lung function, inflammation, gene, and protein expression were assessed.

Results: In the elastase-induced emphysema model, in utero SHS-exposed mice had significantly enlarged airspaces and up-regulated expression of Mmp12 (10.3-fold compared to air-elastase controls). In the HDM-induced asthma model, in utero exposures to SHS produced eosinophilic lung inflammation and potentiated Mmp12 gene expression (5.7-fold compared to air-HDM controls). In the lung cancer model, in utero exposures to SHS significantly increased the number of intrapulmonary metastases at 58weeks of age and up-regulated Mmp12 (9.3-fold compared to air-urethane controls). In all lung disease models, Mmp12 upregulation was supported at the protein level.

Conclusion: Our findings revealed that in utero SHS exposures exacerbate lung responses to adult-induced emphysema, asthma, and lung cancer. Our data show that MMP12 is up-regulated at the gene and protein levels in three distinct adult lung disease models following in utero SHS exposures, suggesting that MMP12 is central to in utero SHS-aggravated lung responses.

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.

Carotenoid-Enriched Fractions From Spondias mombin Demonstrate HER2 ATP Kinase Domain Inhibition: Computational and In Vivo Animal Model of Breast Carcinoma Studies

Human epidermal growth factor 2 (HER2) is overexpressed in about 20% of breast cancer and is associated with a poor prognosis. We report in this study that carotenoid-enriched fractions from Spondias mombin demonstrate HER2 ATP kinase domain inhibition. HER2 breast carcinoma was modeled in female Wistar rats and authenticated via immunohistochemical studies. Inhibition of HER2 ATP kinase domain by the carotenoid-enriched fractions was investigated by molecular docking, atomistic simulation, and the expression of HER2 mRNA in HER2-positive breast carcinoma model in female Wistar rats. The therapeutic efficacy of the treatments (carotenoid-rich fractions) was determined by biochemical, tumor volume, and histopathological analysis. Immunohistochemical analysis revealed 7,12-dimethylbenz[a]anthracene (DMBA)-induced HER2-positive breast carcinoma. Phytoconstituents of the carotenoid-enriched fractions astaxanthin, 7,7′,8,8′-tetrahydro-β,β-carotene, beta-carotene-15,15′-epoxide, and lapatinib (standard drug) demonstrate inhibition of HER2 with docking scores of −3.0, −8.5, −11.5, and −10.6 kcal/mol, respectively; and during atomistic simulation, the compounds ruptured the canonical active-state K753/E770 salt-bridge interaction. The treatment similarly downregulated HER2 mRNA expression significantly at p < 0.05. It also upregulated the expression of p53 and p27 mRNAs significantly at p < 0.05 and reduced creatinine and urea concentrations in the serum at p < 0.05. The tumor volume was also significantly reduced when compared with that of the untreated group. Carotenoid-enriched fractions from S. mombin demonstrate anti-HER2 positive breast carcinoma potentials via HER2 ATP kinase domain inhibition.

Magnetic resonance biomarkers in radiation oncology: The report of AAPM Task Group 294

A magnetic resonance (MR) biologic marker (biomarker) is a measurable quantitative characteristic that is an indicator of normal biological and pathogenetic processes or a response to therapeutic intervention derived from the MR imaging process. There is significant potential for MR biomarkers to facilitate personalized approaches to cancer care through more precise disease targeting by quantifying normal versus pathologic tissue function as well as toxicity to both radiation and chemotherapy. Both of which have the potential to increase the therapeutic ratio and provide earlier, more accurate monitoring of treatment response. The ongoing integration of MR into routine clinical radiation therapy (RT) planning and the development of MR guided radiation therapy systems is providing new opportunities for MR biomarkers to personalize and improve clinical outcomes. Their appropriate use, however, must be based on knowledge of the physical origin of the biomarker signal, the relationship to the underlying biological processes, and their strengths and limitations. The purpose of this report is to provide an educational resource describing MR biomarkers, the techniques used to quantify them, their strengths and weakness within the context of their application to radiation oncology so as to ensure their appropriate use and application within this field.

CT Evaluation of Lymph Nodes That Merge or Split during the Course of a Clinical Trial: Limitations of RECIST 1.1

Purpose To compare Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 with volumetric measurement in the setting of target lymph nodes that split into two or more nodes or merge into one conglomerate node. Materials and Methods In this retrospective study, target lymph nodes were evaluated on CT scans from 166 patients with different types of cancer; 158 of the scans came from The Cancer Imaging Archive. Each target node was measured using RECIST 1.1 criteria before and after merging or splitting, followed by volumetric segmentation. To compare RECIST 1.1 with volume, a single-dimension hypothetical diameter (HD) was determined from the nodal volume. The nodes were divided into three groups: (a) one-target merged (one target node merged with other nodes); (b) two-target merged (two neighboring target nodes merged); and (c) split node (a conglomerate node cleaved into smaller fragments). Bland-Altman analysis and t test were applied to compare RECIST 1.1 with HD. On the basis of the RECIST 1.1 concept, we compared response category changes between RECIST 1.1 and HD. Results The data set consisted of 30 merged nodes (19 one-target merged and 11 two-target merged) and 20 split nodes (mean age for all 50 included patients, 50 years ± 7 [standard deviation]; 38 men). RECIST 1.1, volumetric, and HD measurements indicated an increase in size in all one-target merged nodes. While volume and HD indicated an increase in size for nodes in the two-target merged group, RECIST 1.1 showed a decrease in size in all two-target merged nodes. Although volume and HD demonstrated a decrease in size of all split nodes, RECIST 1.1 indicated an increase in size in 60% (12 of 20) of the nodes. Discrepancy of the response categories between RECIST 1.1 and HD was observed in 5% (one of 19) in one-target merged, 82% (nine of 11) in two-target merged, and 55% (11 of 20) in split nodes. Conclusion RECIST 1.1 does not optimally reflect size changes when lymph nodes merge or split. Keywords: CT, Lymphatic, Tumor Response Supplemental material is available for this article. © RSNA, 2021.

Evaluate the performance of four artificial intelligence-aided diagnostic systems in identifying and measuring four types of pulmonary nodules

PURPOSE

This study aims to evaluate the performance of four artificial intelligence-aided diagnostic systems in identifying and measuring four types of pulmonary nodules.

METHODS

Four types of nodules were implanted in a commercial lung phantom. The phantom was scanned with multislice spiral computed tomography, after which four systems (A, B, C, D) were used to identify the nodules and measure their volumes.

RESULTS

The relative volume error (RVE) of system A was the lowest for all nodules, except for small ground glass nodules (SGGNs). System C had the smallest RVE for SGGNs, -0.13 (-0.56, 0.00). In the Bland-Altman test, only systems A and C passed the consistency test, P = 0.40. In terms of precision, the miss rate (MR) of system C was 0.00% for small solid nodules (SSNs), ground glass nodules (GGNs), and solid nodules (SNs) but 4.17% for SGGNs. The comparable system D MRs for SGGNs, SSNs, and GGNs were 71.30%, 25.93%, and 47.22%, respectively, the highest among all the systems. Receiver operating characteristic curve analysis indicated that system A had the best performance in recognizing SSNs and GGNs, with areas under the curve of 0.91 and 0.68. System C had the best performance for SGGNs (AUC = 0.91).

CONCLUSION

Among four types nodules, SGGNs are the most difficult to recognize, indicating the need to improve higher accuracy and precision of artificial systems. System A most accurately measured nodule volume. System C was most precise in recognizing all four types of nodules, especially SGGN.

Tumor Volume Analysis as a Predictive Marker for Prolonged Survival in Anaplastic Lymphoma Kinase-rearranged Advanced Non-Small Cell Lung Cancer Patients Treated With Crizotinib

PURPOSE

Targeted inhibition of anaplastic lymphoma kinase (ALK) has been widely used for the treatment of advanced non-small cell lung cancer (NSCLC) with ALK rearrangements. We performed tumor volume analysis of ALK-rearranged advanced NSCLC treated with crizotinib to identify an early predictive marker for prolonged survival.

MATERIALS AND METHODS

Cases of 42 patients with ALK-rearranged advanced NSCLC (16 men, 26 women; median age: 55.7 y) treated with crizotinib as their first ALK-directed therapy were retrospectively studied. Tumor volume measurements of dominant lung lesions were performed on baseline computed tomography and follow-up computed tomography at 8 weeks of therapy. The relationships between the 8-week volume change (%) and overall survival (OS) were investigated.

RESULTS

The 8-week tumor volume change ranged from -99.3% to 117.5% (median: -57.7%). Using the 25th percentile of the 8-week volume change of -74%, 11 patients with >74% volume decrease at 8 weeks had a significantly longer OS compared with 31 patients with ≤74% decrease (median OS: 92.0 vs. 22.8 mo; P=0.0048). In multivariable analyses using Cox proportional hazards models, the 8-week volume decrease of >74% was significantly associated with longer OS (hazard ratio=0.14, 95% confidence interval: 0.03-0.59; Cox P=0.008) after adjusting for tumor stage (stage IV vs. recurrent NSCLC, hazard ratio=5.6, 95% confidence interval: 1.29-24.3; P=0.02).

CONCLUSIONS

The 8-week tumor volume decrease of >74% is significantly associated with longer OS in patients with ALK-rearranged NSCLC treated with crizotinib.

The Study of Tumor Volume as a Prognostic Factor in T Staging System for Non-Small Cell Lung Cancer: An Exploratory Study

Background:

This study aimed to evaluate T staging system for non-small cell lung cancer (NSCLC) using tumor volume (TV) and other prognostic factors.

Methods:

This study included 1309 cases. The TV and greatest tumor diameter (GTD) were semi-automatically measured. The receiver operating characteristic (ROC) curves of TV and GTD were used to predict survival. The regression analysis was used to describe the correlation between GTD and TV. Overall survival (OS) was analyzed using the Kaplan-Meier method. Cox’s proportional hazards regression model was applied for multivariate analysis.

Results:

Using the OS in pN0M0 patients (997 cases), we obtained 4 optimal cutoff values and divided all cases into 5 TV groups (V1: TV ≤ 2.80 cm³; V2: TV > 2.80–6.40 cm³; V3: TV > 6.40–12.9 cm³; V4: TV > 12.9–55.01 cm³; V5: TV > 55.01 cm³) with significant OS (P < 0.001). Multivariate analysis showed that age, visceral pleural invasion (VPI), and all TV cutoff points were independent factors of OS (P < 0.05). For V3 and V4 groups, the OS in patients without VPI was better than that in patients with VPI. Using the values of TV, VPI, and N stages, we classified all cases into 5 stages from I to V depending on the OS. The OS in I, II, III, IV, and V stages were 71.3%, 65.5%, 59.8%, 47.7%, and 35.1% respectively (P < 0.001).

Conclusions:

We proposed a new T staging system using TV as the main prognostic descriptor in NSCLC patients, which may provide a better comprehensive clinical value than GTD in clinical applications.

Tumor volume dynamics and tumor growth rate in ALK-rearranged advanced non-small-cell lung cancer treated with crizotinib

Purpose

The purpose of the study is to investigate volumetric tumor burden dynamics and tumor growth rates in ALK-rearranged advanced NSCLC patients during crizotinib monotherapy.

Methods

The study included 44 ALK-rearranged advanced NSCLC patients treated with crizotinib monotherapy as their initial ALK-directed therapy, who had at least one measurable lung lesion and at least two follow-up CT scans, and experienced tumor volume increase while on crizotinib. The tumor volume (in mm³) of the dominant lung lesion was measured on serial CT scans during therapy for analysis of tumor growth rates after the volume nadir.

Results

A total of 231 volume measurements from the nadir to the end of crizotinib therapy or the last follow-up in 44 patients were analyzed in a linear mixed-effects model, fitting time (in months since baseline) as a random effect. When measured from the volume nadir, the tumor growth rate of the logarithm of tumor volume (log_eV) was 0.04/month (SE = 0.012, P = 0.0011) in the unadjusted model. When adjusted for the baseline volume (log_eV₀), the growth rate was again 0.04/month (SE = 0.011, P = 0.0004). When adjusted for clinical variables and log_eV₀, the growth rate was 0.045/month (SE = 0.012, P = 0.0002), indicating that the tumor growth rate after nadir in this cohort remains very close to 0.04/month regardless of log_eV₀ or clinical factors.

Conclusions

Tumor volume growth rate after nadir in ALK-rearranged NSCLC patients treated with crizotinib was obtained, providing objective reference values that can inform physicians when deciding to keep their patients on ALK directed therapy with slowly progressing lung cancer.

Enhanced Detection of Treatment Effects on Metastatic Colorectal Cancer with Volumetric CT Measurements for Tumor Burden Growth Rate Evaluation

PURPOSE

Mathematical models combined with new imaging technologies could improve clinical oncology studies. To improve detection of therapeutic effect in patients with cancer, we assessed volumetric measurement of target lesions to estimate the rates of exponential tumor growth and regression as treatment is administered.

EXPERIMENTAL DESIGN

Two completed phase III trials were studied (988 patients) of aflibercept or panitumumab added to standard chemotherapy for advanced colorectal cancer. Retrospectively, radiologists performed semiautomated measurements of all metastatic lesions on CT images. Using exponential growth modeling, tumor regression (d) and growth (g) rates were estimated for each patient's unidimensional and volumetric measurements.

RESULTS

Exponential growth modeling of volumetric measurements detected different empiric mechanisms of effect for each drug: panitumumab marginally augmented the decay rate [tumor half-life; d [IQR]: 36.5 days (56.3, 29.0)] of chemotherapy [d: 44.5 days (67.2, 32.1), two-sided Wilcoxon P = 0.016], whereas aflibercept more significantly slowed the growth rate [doubling time; g = 300.8 days (154.0, 572.3)] compared with chemotherapy alone [g = 155.9 days (82.2, 347.0), P ≤ 0.0001]. An association of g with overall survival (OS) was observed. Simulating clinical trials using volumetric or unidimensional tumor measurements, fewer patients were required to detect a treatment effect using a volumetric measurement-based strategy (32-60 patients) than for unidimensional measurement-based strategies (124-184 patients).

CONCLUSIONS

Combined tumor volume measurement and estimation of tumor regression and growth rate has potential to enhance assessment of treatment effects in clinical studies of colorectal cancer that would not be achieved with conventional, RECIST-based unidimensional measurements.

Diagnosis of Invasive Lung Adenocarcinoma Based on Chest CT Radiomic Features of Part-Solid Pulmonary Nodules: A Multicenter Study

Background Solid components of part-solid nodules (PSNs) at CT are reflective of invasive adenocarcinoma, but studies describing radiomic features of PSNs and the perinodular region are lacking. Purpose To develop and to validate radiomic signatures diagnosing invasive lung adenocarcinoma in PSNs compared with the Brock, clinical-semantic features, and volumetric models. Materials and Methods This retrospective multicenter study (https://ClinicalTrials.gov, NCT03872362) included 291 patients (median age, 60 years; interquartile range, 55-65 years; 191 women) from January 2013 to October 2017 with 297 PSN lung adenocarcinomas split into training (n = 229) and test (n = 68) data sets. Radiomic features were extracted from the different regions (gross tumor volume [GTV], solid, ground-glass, and perinodular). Random-forest models were trained using clinical-semantic, volumetric, and radiomic features, and an online nodule calculator was used to compute the Brock model. Performances of models were evaluated using standard metrics such as area under the curve (AUC), accuracy, and calibration. The integrated discrimination improvement was applied to assess model performance changes after the addition of perinodular features. Results The radiomics model based on ground-glass and solid features yielded an AUC of 0.98 (95% confidence interval [CI]: 0.96, 1.00) on the test data set, which was significantly higher than the Brock (AUC, 0.83 [95% CI: 0.72, 0.94]; P = .007), clinical-semantic (AUC, 0.90 [95% CI: 0.83, 0.98]; P = .03), volumetric GTV (AUC, 0.87 [95% CI: 0.78, 0.96]; P = .008), and radiomics GTV (AUC, 0.88 [95% CI: 0.80, 0.96]; P = .01) models. It also achieved the best accuracy (93% [95% CI: 84%, 98%]). Both this model and the model with added perinodular features showed good calibration, whereas adding perinodular features did not improve the performance (integrated discrimination improvement, -0.02; P = .56). Conclusion Separating ground-glass and solid CT radiomic features of part-solid nodules was useful in diagnosing the invasiveness of lung adenocarcinoma, yielding a better predictive performance than the Brock, clinical-semantic, volumetric, and radiomics gross tumor volume models. Online supplemental material is available for this article. See also the editorial by Nishino in this issue. Published under a CC BY 4.0 license.

Tumor volume is more reliable to predict nodal metastasis in non-small cell lung cancer of 3.0 cm or less in the greatest tumor diameter

Background

In this study, we sought to evaluate the correlation between TV, GTD, and lymph node metastases in NSCLC patients with tumors of GTD ≤ 3.0 cm.

Methods

We retrospectively analyzed the characteristics of clinicopathologic variables for lymph node involvement in 285 NSCLC patients with tumors of GTD ≤ 3.0 cm who accepted curative surgical resection. The TVs were semi-automatically measured by a software, and optimal cutoff points were obtained using the X-tile software. The relationship between GTD and TV were described using non-linear regression. The correlation between GTD, TV, and N stages was analyzed using the Pearson correlation coefficient. The one-way ANOVA was used to compare the GTD and TV of different lymph node stage groups.

Results

The relationship between GTD and TV accorded with the exponential growth model: y = 0.113e^1.455x (y = TV, x = GTD). TV for patients with node metastases (4.78 cm³) was significantly greater than those without metastases (3.57 cm³) (P < 0.001). However, there were no obvious GTD differences in cases with or without lymph node metastases (P = 0.054). We divided all cases into three TV groups using the two cutoff values (0.9 cm³ and 3.9 cm³), and there was an obvious difference in the lymphatic involvement rate between the groups (P < 0.001). The tendency to metastasize was greater with higher TV especially when the TV was > 0.9–14.2 cm³ (P = 0.010).

Conclusions

For NSCLC tumors with GTD ≤ 3.0 cm, TV is a more sensitive marker than GTD in predicting the positive lymph node metastases. The likelihood for metastasis increases with an increasing TV especially when GTD is > 2.0–3.0 cm.

Evaluation of Simulated Lesions as Surrogates to Clinical Lesions for Thoracic CT Volumetry: The Results of an International Challenge

RATIONALE AND OBJECTIVES

To evaluate a new approach to establish compliance of segmentation tools with the computed tomography volumetry profile of the Quantitative Imaging Biomarker Alliance (QIBA); and determine the statistical exchangeability between real and simulated lesions through an international challenge.

MATERIALS AND METHODS

The study used an anthropomorphic phantom with 16 embedded physical lesions and 30 patient cases from the Reference Image Database to Evaluate Therapy Response with pathologically confirmed malignancies. Hybrid datasets were generated by virtually inserting simulated lesions corresponding to physical lesions into the phantom datasets using one projection-domain-based method (Method 1), two image-domain insertion methods (Methods 2 and 3), and simulated lesions corresponding to real lesions into the Reference Image Database to Evaluate Therapy Response dataset (using Method 2). The volumes of the real and simulated lesions were compared based on bias (measured mean volume differences between physical and virtually inserted lesions in phantoms as quantified by segmentation algorithms), repeatability, reproducibility, equivalence (phantom phase), and overall QIBA compliance (phantom and clinical phase).

RESULTS

For phantom phase, three of eight groups were fully QIBA compliant, and one was marginally compliant. For compliant groups, the estimated biases were -1.8 ± 1.4%, -2.5 ± 1.1%, -3 ± 1%, -1.8 ± 1.5% (±95% confidence interval). No virtual insertion method showed statistical equivalence to physical insertion in bias equivalence testing using Schuirmann's two one-sided test (±5% equivalence margin). Differences in repeatability and reproducibility across physical and simulated lesions were largely comparable (0.1%-16% and 7%-18% differences, respectively). For clinical phase, 7 of 16 groups were QIBA compliant.

CONCLUSION

Hybrid datasets yielded conclusions similar to real computed tomography datasets where phantom QIBA compliant was also compliant for hybrid datasets. Some groups deemed compliant for simulated methods, not for physical lesion measurements. The magnitude of this difference was small (<5.4%). While technical performance is not equivalent, they correlate, such that, volumetrically simulated lesions could potentially serve as practical proxies.

Prognostic Impact of Longitudinal Monitoring of Radiomic Features in Patients with Advanced Non-Small Cell Lung Cancer

Tumor growth dynamics vary substantially in non-small cell lung cancer (NSCLC). We aimed to develop biomarkers reflecting longitudinal change of radiomic features in NSCLC and evaluate their prognostic power. Fifty-three patients with advanced NSCLC were included. Three primary variables reflecting patterns of longitudinal change were extracted: area under the curve of longitudinal change (AUC1), beta value reflecting slope over time, and AUC2, a value obtained by considering the slope and area over the longitudinal change of features. We constructed models for predicting survival with multivariate cox regression, and identified the performance of these models. AUC2 exhibited an excellent correlation between patterns of longitudinal volume change and a significant difference in overall survival time. Multivariate regression analysis based on cut-off values of radiomic features extracted from baseline CT and AUC2 showed that kurtosis of positive pixel values and surface area from baseline CT, AUC2 of density, skewness of positive pixel values, and entropy at inner portion were associated with overall survival. For the prediction model, the areas under the receiver operating characteristic curve (AUROC) were 0.948 and 0.862 at 1 and 3 years of follow-up, respectively. Longitudinal change of radiomic tumor features may serve as prognostic biomarkers in patients with advanced NSCLC.

Tumor Volume Is Better Than Diameter for Predicting the Prognosis of Patients with Early-Stage Non-small Cell Lung Cancer

BACKGROUND

This study aimed to investigate whether tumor volume (TV) is better than diameter for predicting the prognosis of patients with early-stage non-small cell lung cancer (NSCLC) after complete resection.

METHODS

This study retrospectively reviewed the clinicopathologic characteristics of 274 patients with early-stage NSCLC who had received pretreatment computed tomography (CT) scans and complete resection. TV was semi-automatically measured from CT scans using an imaging software program. The optimal cutoff of TV was determined by X-tile software. Disease-free survival (DFS) and overall survival (OS) were assessed by the Kaplan-Meier method. The prognostic significance of TV and other variables was assessed by Cox proportional hazards regression analysis.

RESULTS

Using 3.046 cm³ and 8.078 cm³ as optimal cutoff values of TV, the patients were separated into three groups. A larger TV was significantly associated with poor DFS and OS in the multivariable analysis. Kaplan-Meier curves of DFS and OS showed significant differences on the basis of TV among patients with stage 1a disease, greatest tumor diameter (GTD) of 2 cm or smaller, and GTD of 2-3 cm, respectively. Using two TV cutoff points, three categories of TV were created. In 54 cases (19.7%), patients migrated from the GTD categories of 2 cm or smaller, 2-3 cm, and larger than 3 cm into the TV categories of 3.046 cm³ or smaller, 3.046-8.078 cm³, and larger than 8.078 cm³.

CONCLUSION

TV is an independent prognostic factor of DFS and OS for early-stage NSCLC. The findings show that TV is better than GTD for predicting the prognosis of patients with early-stage NSCLC.

The relation of radiological tumor volume response to histological response and outcome in patients with localized Ewing Sarcoma

Background

Magnetic resonance imaging (MRI) is the modality of choice for local staging and response evaluation of Ewing sarcoma (EwS). Aim of this study was to determine the relevance of tumor volume response (TVR) in relation to histological response (HisRes) and survival, in order to evaluate if early modification of chemotherapy might be indicated in patients with inadequate TVR.

Methods

Three dimensional (3D)‐tumor volume data at diagnosis, during early induction phase (1‐3 courses of chemotherapy; n = 195) and/or late induction phase (4‐6 courses; n = 175) from 241 localized patients were retrospectively analyzed. A distinction was made between adequate response (reduction ≥67%) and inadequate response (reduction <67% or progression). Correlations between TVR, HisRes, event free survival (EFS), and overall survival (OS) were analyzed using chi‐square tests, log‐rank tests, and the Cox‐regression model.

Results

Early adequate TVR, noted in 41% of patients, did not correlate with EFS (P = 0.92) or OS (P = 0.38). During late induction phase 62% of patients showed an adequate TVR. EFS for patients with late adequate TVR was better (78%) than for those with inadequate late TVR (61%) (P = 0.01); OS was 80% and 69% (P = 0.26), respectively. No correlation was found between TVR and HisRes. Multivariate analysis showed that poor HisRes, pelvic location and late inadequate TVR were associated with poor outcome.

Conclusions

Early inadequate TVR does not predict adverse outcome; therefore, changing the treatment to second line chemotherapy is not indicated in case of inadequate early TVR. Late adequate TVR and good HisRes correlate with better EFS; patients with late inadequate TVR might benefit from augmented therapy.

Tumor Response Assessment for Precision Cancer Therapy: Response Evaluation Criteria in Solid Tumors and Beyond

Objective assessment of tumor responses and treatment results has been the basis for the advancement of cancer therapies, and imaging plays a key role to provide a "common language" to describe the results of cancer treatment. Although Response Evaluation Criteria in Solid Tumors (RECIST) has been the most widely accepted method for assessing tumor response in the past decades, the limitations of RECIST have increasingly becoming recognized, especially with the recent advances of precision-medicine approaches to cancer. This article reviews the current concept of tumor response evaluations based on RECIST, describes the limitations of RECIST, and proposes strategies to overcome the limitations. The article emphasizes specific limitations in the setting of precision cancer therapy and cancer immunotherapy and discusses the important insights provided by the cutting-edge investigations in the emerging fields.

A phase 2 study of vorinostat in locally advanced, recurrent, or metastatic adenoid cystic carcinoma

Purpose

Vorinostat is a histone deacetylase inhibitor (HDACi). Based on a confirmed partial response (PR) in an adenoid cystic carcinoma (ACC) patient treated with vorinostat in a prior phase 1 trial, we initiated this phase 2 trial. Methods: Vorinostat was administered orally 400 mg daily, 28 day cycles. The primary objective was to evaluate response rate (RR). Exploratory studies included whole exome sequencing (WES) of selected patients.

Results

Thirty patients were enrolled. Median age of patients was 53 years (range 21–73). Median number of cycles was 5 (range 1-66). Lymphopenia (n = 5), hypertension (n = 3), oral pain (n = 2), thromboembolic events (n = 2) and fatigue (n = 2) were the only grade 3 adverse events (AEs) that occurred in more than 1 patient. Eleven patients were dose reduced secondary to drug-related AEs. Two patients had a partial response (PR), with response durations of 53 and 7.2 months. One patient had a minor response with a decrease in ascites (for 19 cycles). Stable disease was the best response in 27 patients. Targeted and WES of 8 patients in this trial identified mutations in chromatin remodeling genes highlighting the role of the epigenome in ACC. Conclusion: Vorinostat demonstrated efficacy in patients with ACC supporting the inclusion of HDACi in future studies to treat ACC.

Volumetric and linear measurements of lung tumor burden from non-gated micro-CT imaging correlate with histological analysis in a genetically engineered mouse model of non-small cell lung cancer

In vivo micro-computed tomography (CT) imaging allows longitudinal studies of pulmonary neoplasms in genetically engineered mouse models. Respiratory gating increases the accuracy of lung tumor measurements but lengthens anesthesia time in animals that may be at increased risk for complications. We hypothesized that semiautomated, volumetric, and linear tumor measurements performed in micro-CT images from non-gated scans would have correlation with histological findings. Primary lung tumors were induced in eight FVB mice with two transgenes (FVB/N-Tg(tetO-Kras2)12Hev/J; FVB.Cg-Tg(Scgb1a1-rtTA)1Jaw/J). Non-gated micro-CT scans were performed and the lungs were subsequently harvested. In the acquired micro-CT scans, measurements of all identified tumors were determined using the following methods: semiautomated three-dimensional (3D) volume, ellipsoid volume, Response Evaluation Criteria in Solid Tumors (RECIST; sum of largest axial (i.e., transverse) diameter from five tumors), sum of largest axial diameters from all tumors (modified RECIST), and average axial diameter. For histological analysis, all five lung lobes were analyzed and the tumor area was summed from measurements made on five histological sections that were 300 µm apart from each other (covering a total depth of 1200 µm). All micro-CT measurement methods had very strong correlation with histological tumor burden (Pearson's correlation coefficient, 0.87 ( p = 0.0053) -0.98 ( p < 0.0001)). The only methods found to have different correlations were the semiautomated 3D method and the RECIST method (Williams' test for dependent overlapping correlations, p = 0.013). Our results suggest quantification of lung tumor burden from non-gated micro-CT imaging will reflect histological differences between mice and can therefore be used for between-group comparisons or when concerns about systemic health of research animals may limit lengthy anesthetic procedures.

Best Response According to RECIST During First-line EGFR-TKI Treatment Predicts Survival in EGFR Mutation-positive Non-Small-cell Lung Cancer Patients

INTRODUCTION

The association between the response to first-line epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) and survival in EGFR mutation-positive non-small-cell lung cancer (NSCLC) remains unclear. We studied the association between the response to first-line EGFR-TKIs and survival using Response Evaluation Criteria In Solid Tumors (RECIST) and maximal tumor shrinkage.

MATERIALS AND METHODS

We analyzed data from patients with advanced EGFR mutation-positive NSCLC enrolled in first-line gefitinib and afatinib trials. A total of 98 patients who achieved a response or stable disease and had ≥ 1 measurable target lesion were included. The association between the best response by RECIST or maximal tumor shrinkage and survival was analyzed in Kaplan-Meier and Cox regression models with the landmark method. The specified landmark time points were 8 weeks, the median time to maximal tumor shrinkage (16.5 weeks), and median progression-free survival (PFS; 56 weeks).

RESULTS

A total of 76 patients (77%) responded to gefitinib or afatinib. Of these 76 patients, 49 (64%) and 75 (99%) had achieved a response at 8 and 16.5 weeks, respectively. All responders had achieved a response by 56 weeks. The responders had a significantly longer PFS and overall survival (OS) compared with those with stable disease at 16.5 weeks (PFS, P = .003; OS, P < .001) and 56 weeks (PFS, P = .026; OS, P = .016) but not at 8 weeks (PFS, P = .104; OS, P = .313). Among the responders, greater tumor shrinkage was not associated with longer PFS or OS.

CONCLUSION

Those with a response to first-line gefitinib or afatinib had more favorable PFS and OS compared with those with stable disease. A sufficient observation period was required for the response to occur and predict outcomes. Greater maximal tumor shrinkage in the responders was not predictive of survival.

Comparison of One-Dimensional and Volumetric Computed Tomography Measurements of Injected-Water Phantoms

The goal of this study was to compare volumetric analysis in computed tomography (CT) with the length measurement prescribed by the Response Evaluation Criteria in Solid Tumors (RECIST) for a system with known mass and unknown shape. We injected 2 mL to 4 mL of water into vials of sodium polyacrylate and into disposable diapers. Volume measurements of the sodium polyacrylate powder were able to predict both mass and proportional changes in mass within a 95 % prediction interval of width 12 % and 16 %, respectively. The corresponding figures for RECIST were 102 % and 82 %.

Prognostic value of tumor volume for patients with advanced lung cancer treated with chemotherapy

BACKGROUND AND OBJECTIVE

We aim to develop a reference system utilizing computed tomography to calculate changes in tumor volume of lung cancer patients after chemotherapy to assist physicians in clinical treatment and evaluation.

METHODS

Image processing techniques were used to analyze the computed tomography of lung cancer, locate the tumor, and calculate the tumor volume. The medical indicator was then evaluated and analyzed. We examined the correlation between reduced tumor volume and survival duration of 88 patients after chemotherapy at Tri-Service General Hospital, Taiwan. The innovative survival prediction index was obtained by four statistical methods: receiver operating characteristic curve, Youden index, Kaplan-Meier method, and log rank test.

RESULTS

From the image processing techniques, tumor volume from each patient were obtained within an average of 7.25 seconds. The proposed method was shown to achieve rapid positioning of lung tumors and volume reconstruction with an estimation error of 1.92% when calibrated with an irregularly shaped stone. In medical indicator evaluation and analysis, the area below the receiver operating characteristic curve is greater than 0.8, indicating good predictability of the medical index used herein. The Youden index spotted the best cut-off point of volume, and the correlation between the volume's cut-off point and survival time was confirmed again by Kaplan-Meier and log rank test. The p-values were all less than 0.05, presenting a high degree of correlation between the two, indicating that this medical indicator is highly reliable.

CONCLUSIONS

The proposed techniques can automatically find the location of tumors in the lung, reconstruct the volume, and calculate changes in volume before and after treatment, thus obtaining an innovative survival prediction index. This will help facilitate early and accurate predictions of disease outcomes during the course of therapy, and categorize patient stratification into risk groups for more efficient therapies.

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.

Co-clinical quantitative tumor volume imaging in ALK-rearranged NSCLC treated with crizotinib

PURPOSE

To evaluate and compare the volumetric tumor burden changes during crizotinib therapy in mice and human cohorts with ALK-rearranged non-small-cell lung cancer (NSCLC).

METHODS

Volumetric tumor burden was quantified on serial imaging studies in 8 bitransgenic mice with ALK-rearranged adenocarcinoma treated with crizotinib, and in 33 human subjects with ALK-rearranged NSCLC treated with crizotinib. The volumetric tumor burden changes and the time to maximal response were compared between mice and humans.

RESULTS

The median tumor volume decrease (%) at the maximal response was -40.4% (range: -79.5%-+11.7%) in mice, and -72.9% (range: -100%-+72%) in humans (Wilcoxon p=0.03). The median time from the initiation of therapy to maximal response was 6 weeks in mice, and 15.7 weeks in humans. Overall volumetric response rate was 50% in mice and 97% in humans. Spider plots of tumor volume changes during therapy demonstrated durable responses in the human cohort, with a median time on therapy of 13.1 months.

CONCLUSION

The present study described an initial attempt to evaluate quantitative tumor burden changes in co-clinical imaging studies of genomically-matched mice and human cohorts with ALK-rearranged NSCLC treated with crizotinib. Differences are noted in the degree of maximal volume response between the two cohorts in this well-established paradigm of targeted therapy, indicating a need for further studies to optimize co-clinical trial design and interpretation.

Survival analyses in lung cancer

BACKGROUND

Although survival analyses represent one of the cornerstones in oncology in general, some aspects of the reported survival data in lung cancer patients are still not fully elucidated.

METHODS

After having defined several open questions, an evidence based approach was applied in order to answer these questions. Areas of interest were: (I) possible uncertainties in reported survival data; (II) survival surrogates; (III) recommended methods for evaluating progression free survival (PFS) as a surrogate endpoint in future datasets; (IV) postoperative lung cancer recurrence and survival.

RESULTS

In recent years, PFS has seen increasing use as a primary endpoint, particularly in phase II trials. This article focuses on the statistical aspects, and particularly on evaluating the ability of PFS to accurately predict the overall survival (OS) outcome. If the data are available from randomized trials, then the evaluation of trial level surrogacy should be carried out, in addition to the methods described in the paper. If it is not a case, the patient-level methods should be applied. Suggestions for "landmark analysis" are also given: (I) classify your cases according to progression status (progressed, progression-free, or unknown) at one or more time points of interest; (II) perform a separate Cox proportional hazards regression analysis for each time point; (III) determine and report the landmark time point where progression status best predicts survival according to the hazard ratios and P values; (IV) calculate the concordance index for each landmark analysis model. The concordance index (or "c-Index") is essentially the probability that for any two randomly selected cases, the case that is predicted to have the worst outcome, does in fact have the worst outcome.

CONCLUSIONS

the widening spectrum of diagnostic and treatment in pulmonary oncology imposes the need for an updated knowledge about statistical method that would fit best for the analysed problem.

Volumes Learned: It Takes More Than Size to "Size Up" Pulmonary Lesions

RATIONALE AND OBJECTIVES

This study aimed to review the current understanding and capabilities regarding use of imaging for noninvasive lesion characterization and its relationship to lung cancer screening and treatment.

MATERIALS AND METHODS

Our review of the state of the art was broken down into questions about the different lung cancer image phenotypes being characterized, the role of imaging and requirements for increasing its value with respect to increasing diagnostic confidence and quantitative assessment, and a review of the current capabilities with respect to those needs.

RESULTS

The preponderance of the literature has so far been focused on the measurement of lesion size, with increasing contributions being made to determine the formal performance of scanners, measurement tools, and human operators in terms of bias and variability. Concurrently, an increasing number of investigators are reporting utility and predictive value of measures other than size, and sensitivity and specificity is being reported. Relatively little has been documented on quantitative measurement of non-size features with corresponding estimation of measurement performance and reproducibility.

CONCLUSIONS

The weight of the evidence suggests characterization of pulmonary lesions built on quantitative measures adds value to the screening for, and treatment of, lung cancer. Advanced image analysis techniques may identify patterns or biomarkers not readily assessed by eye and may also facilitate management of multidimensional imaging data in such a way as to efficiently integrate it into the clinical workflow.

Quantitative Computed Tomography Imaging Biomarkers in the Diagnosis and Management of Lung Cancer

Tumor diameter has traditionally been used as a standard metric in terms of diagnosis and prognosis prediction of lung cancer. However, recent advances in imaging techniques and data analyses have enabled novel quantitative imaging biomarkers that can characterize disease status more comprehensively and/or predict tumor behavior more precisely. The most widely used imaging modality for lung tumor assessment is computed tomography. Therefore, we focused on computed tomography imaging biomarkers such as tumor volume and mass, ground-glass opacities, perfusion parameters, as well as texture features in this review. Herein, we first appraised the conventional 1- or 2-dimensional measurement with brief discussion on their limits and then introduced the potential imaging biomarkers with emphasis on the current understanding of their clinical usefulness with respect to the malignancy differentiation, treatment response monitoring, and patient outcome prediction.

Statistical analysis of lung nodule volume measurements with CT in a large-scale phantom study

PURPOSE

To determine inter-related factors that contribute substantially to measurement error of pulmonary nodule measurements with CT by assessing a large-scale dataset of phantom scans and to quantitatively validate the repeatability and reproducibility of a subset containing nodules and CT acquisitions consistent with the Quantitative Imaging Biomarker Alliance (QIBA) metrology recommendations.

METHODS

The dataset has about 40 000 volume measurements of 48 nodules (5-20 mm, four shapes, three radiodensities) estimated by a matched-filter estimator from CT images involving 72 imaging protocols. Technical assessment was performed under a framework suggested by QIBA, which aimed to minimize the inconsistency of terminologies and techniques used in the literature. Accuracy and precision of lung nodule volume measurements were examined by analyzing the linearity, bias, variance, root mean square error (RMSE), repeatability, reproducibility, and significant and substantial factors that contribute to the measurement error. Statistical methodologies including linear regression, analysis of variance, and restricted maximum likelihood were applied to estimate the aforementioned metrics. The analysis was performed on both the whole dataset and a subset meeting the criteria proposed in the QIBA Profile document.

RESULTS

Strong linearity was observed for all data. Size, slice thickness × collimation, and randomness in attachment to vessels or chest wall were the main sources of measurement error. Grouping the data by nodule size and slice thickness × collimation, the standard deviation (3.9%-28%), and RMSE (4.4%-68%) tended to increase with smaller nodule size and larger slice thickness. For 5, 8, 10, and 20 mm nodules with reconstruction slice thickness ≤0.8, 3, 3, and 5 mm, respectively, the measurements were almost unbiased (-3.0% to 3.0%). Repeatability coefficients (RCs) were from 6.2% to 40%. Pitch of 0.9, detail kernel, and smaller slice thicknesses yielded better (smaller) RCs than those from pitch of 1.2, medium kernel, and larger slice thicknesses. Exposure showed no impact on RC. The overall reproducibility coefficient (RDC) was 45%, and reduced to about 20%-30% when the slice thickness and collimation were fixed. For nodules and CT imaging complying with the QIBA Profile (QIBA Profile subset), the measurements were highly repeatable and reproducible in spite of variations in nodule characteristics and imaging protocols. The overall measurement error was small and mostly due to the randomness in attachment. The bias, standard deviation, and RMSE grouped by nodule size and slice thickness × collimation in the QIBA Profile subset were within ±3%, 4%, and 5%, respectively. RCs are within 11% and the overall RDC is equal to 11%.

CONCLUSIONS

The authors have performed a comprehensive technical assessment of lung nodule volumetry with a matched-filter estimator from CT scans of synthetic nodules and identified the main sources of measurement error among various nodule characteristics and imaging parameters. The results confirm that the QIBA Profile set is highly repeatable and reproducible. These phantom study results can serve as a bound on the clinical performance achievable with volumetric CT measurements of pulmonary nodules.

Three-dimensional Radiologic Assessment of Chemotherapy Response in Ewing Sarcoma Can Be Used to Predict Clinical Outcome

Purpose To compare the agreement of three-dimensional (3D) tumor measurements for therapeutic response assessment of Ewing sarcoma according to the Children's Oncology Group (COG) criteria, one-dimensional (1D) Response Evaluation Criteria in Solid Tumors (RECIST), and two-dimensional (2D) measurements defined by the World Health Organization (WHO) with tumor volume measurements as the standard of reference and to determine which method correlates best with clinical outcomes. Materials and Methods This retrospective study was approved by the institutional review board of three institutions. Seventy-four patients (mean age ± standard deviation, 14.5 years ± 6.5) with newly diagnosed Ewing sarcoma treated at three medical centers were evaluated. Primary tumor size was assessed on pre- and posttreatment magnetic resonance images according to 1D RECIST, 2D WHO, and 3D COG measurements. Tumor responses were compared with the standard of reference (tumor volume) on the basis of RECIST, COG, and WHO therapeutic response thresholds. Agreement between the percentage reduction measurements of the methods was assessed with concordance correlation, Bland-Altman analysis, and Spearman rank correlation. Agreement between therapeutic responses was assessed with Kendall tau and unweighted κ statistics. Tumor responses were compared with patient survival by using the log-rank test, Kaplan-Meier plots, and Cox regression. Results Agreement with the reference standard was significantly better for 3D measurement than for 1D and 2D measurements on the basis of RECIST and COG therapeutic response thresholds (concordance correlation of 0.41, 0.72, and 0.84 for 1D, 2D, and 3D measurements, respectively; P < .0001). Comparison of overall survival of responders and nonresponders demonstrated P values of .4133, .0112, .0032, and .0027 for 1D, 2D, 3D, and volume measurements, respectively, indicating that higher dimensional measurements were significantly better predictors of overall survival. Conclusion The 3D tumor measurements according to COG are better predictors of therapeutic response of Ewing sarcoma than 1D RECIST or 2D WHO measurements and show a significantly higher correlation with clinical outcomes. (©) RSNA, 2016 Online supplemental material is available for this article.

Volume-based growth tumor kinetics as a prognostic biomarker for patients with EGFR mutant lung adenocarcinoma undergoing EGFR tyrosine kinase inhibitor therapy: a case control study

BACKGROUND

We aim to determine whether volumetric assessment has the potential to serve as a prognostic biomarker, and to assess the relationship between longitudinal tumor data during treatment and prognosis in lung adenocarcinoma patients with sensitizing EGFR mutations treated with EGFR tyrosine kinase inhibitors (TKI).

METHODS

We retrospectively assessed patients with EGFR-mutant stage IV lung adenocarcinoma who were treated with EGFR TKIs until disease progression. CT studies of 106 patients were quantitatively analyzed in terms of tumor size and volume by comparing baseline and follow-up CT scans obtained at every two treatment cycles. Tumor response was quantified using longitudinal measurements, and tumor growth kinetics was determined. Correlation with early surrogate parameters for tumor response evaluation such as change in size, volume, and response rate was performed. The Cox-proportional hazard model and Log-rank test were used to predict overall survival (OS).

RESULTS

Responders based on the percent change in volume after four cycles of TKI therapy had a higher OS than non-responders (P = 0.035). The percent of volume and size changes after four cycles of TKI therapy were significantly correlated with TTP (P < 0.001).

CONCLUSION

Volume measurements and corresponding rates of growth appear to be helpful adjuncts for predicting survival in patients undergoing EGFR-TKI therapy.

Volumetric Tumor Response and Progression in EGFR-mutant NSCLC Patients Treated with Erlotinib or Gefitinib

RATIONALE AND OBJECTIVES

The aims of this study were to investigate the association between 8-week tumor volume decrease and survival in an independent cohort of epidermal growth factor receptor (EGFR)-mutant advanced non-small cell lung cancer (NSCLC) patients treated with first-line erlotinib or gefitinib, and to assess the rate of their volumetric tumor growth after the volume nadir.

MATERIALS AND METHODS

In patients with advanced NSCLC harboring sensitizing EGFR mutations treated with first-line erlotinib or gefitinib, computed tomography (CT) tumor volumes of dominant lung lesions were analyzed for (1) the association with survival, and (2) the volumetric tumor growth rate after the volume nadir.

RESULTS

In 44 patients with the 8-week follow-up CT, the 8-week tumor volume decrease (%) was significantly associated with longer overall survival when fitted as a continuous variable in a Cox model (P = 0.01). The growth rate of the logarithm of tumor volume (logeV), obtained using a linear mixed-effects model adjusting for time since baseline, was 0.096/month (SE: 0.013/month; 95% confidence interval [CI]: 0.071-0.12/month), which was similar to the rate of 0.12/month (SE: 0.015/month; 95%CI: 0.090-0.15/month) observed in the previous report.

CONCLUSIONS

The 8-week tumor volume decrease was validated as a marker for longer survival in the independent cohort of EGFR-mutant NSCLC patients treated with first-line erlotinib or gefitinib. The volumetric tumor growth rate after the nadir in this cohort was similar to that of the previous cohort, indicating the reproducibility of the observation among different patient cohorts.

Changes of lung tumour volume on CT - prediction of the reliability of assessments

Background

For oncological evaluations, quantitative radiology gives clinicians significant insight into patients’ response to therapy. In regard to the Response Evaluation Criteria in Solid Tumours (RECIST), the classification of disease evolution partly consists in applying thresholds to the measurement of the relative change of tumour. In the case of tumour volumetry, response thresholds have not yet been established. This study proposes and validates a model for calculating thresholds for the detection of minimal tumour change when using the volume of pulmonary lesions on CT as imaging biomarker.

Methods

Our work is based on the reliability analysis of tumour volume measurements documented by the Quantitative Imaging Biomarker Alliance. Statistics of measurements were entered into a multi-parametric mathematical model of the relative changes derived from the Geary-Hinkley transformation. The consistency of the model was tested by comparing modelled thresholds against Monte Carlo simulations of tumour volume measurements with additive random error. The model has been validated by repeating measurements on real patient follow ups.

Results

For unchanged tumour volume, relying on a normal distribution of error, the agreement between model and simulations featured a type I error of 5.25 %. Thus, we established that a threshold of 35 % of volume reduction corresponds to a partial response (PR) and a 55 % volume increase corresponds to progressive disease (PD). Changes between −35 and +55 % are categorized as stable disease (SD). Tested on real clinical data, 97.1 % [95.7; 98.0] of assessments fall into the range of variability predicted by our model of confidence interval.

Conclusions

Our study indicates that the Geary Hinkley model, using published statistics, is appropriate to predict response thresholds for the volume of pulmonary lesions on CT.

Photodynamic therapy as an effective therapeutic approach in MAME models of inflammatory breast cancer

Photodynamic therapy (PDT) is a minimally invasive, FDA-approved therapy for treatment of endobronchial and esophageal cancers that are accessible to light. Inflammatory breast cancer (IBC) is an aggressive and highly metastatic form of breast cancer that spreads to dermal lymphatics, a site that would be accessible to light. IBC patients have a relatively poor survival rate due to lack of targeted therapies. The use of PDT is underexplored for breast cancers but has been proposed for treatment of subtypes for which a targeted therapy is unavailable. We optimized and used a 3D mammary architecture and microenvironment engineering (MAME) model of IBC to examine the effects of PDT using two treatment protocols. The first protocol used benzoporphyrin derivative monoacid A (BPD) activated at doses ranging from 45 to 540 mJ/cm(2). The second PDT protocol used two photosensitizers: mono-L-aspartyl chlorin e6 (NPe6) and BPD that were sequentially activated. Photokilling by PDT was assessed by live-dead assays. Using a MAME model of IBC, we have shown a significant dose-response in photokilling by BPD-PDT. Sequential activation of NPe6 followed by BPD is more effective in photokilling of tumor cells than BPD alone. Sequential activation at light doses of 45 mJ/cm(2) for each agent resulted in >90 % cell death, a response only achieved by BPD-PDT at a dose of 360 mJ/cm(2). Our data also show that effects of PDT on a volumetric measurement of 3D MAME structures reflect efficacy of PDT treatment. Our study is the first to demonstrate the potential of PDT for treating IBC.

Impact Total Psoas Volume on Short- and Long-Term Outcomes in Patients Undergoing Curative Resection for Pancreatic Adenocarcinoma: a New Tool to Assess Sarcopenia

BACKGROUND

While sarcopenia is typically defined using total psoas area (TPA), characterizing sarcopenia using only a single axial cross-sectional image may be inadequate. We sought to evaluate total psoas volume (TPV) as a new tool to define sarcopenia and compare patient outcomes relative to TPA and TPV.

METHOD

Sarcopenia was assessed in 763 patients who underwent pancreatectomy for pancreatic adenocarcinoma between 1996 and 2014. It was defined as the TPA and TPV in the lowest sex-specific quartile. The impact of sarcopenia defined by TPA and TPV on overall morbidity and mortality was assessed using multivariable analysis.

RESULT

Median TPA and TPV were both lower in women versus men (both P < 0.001). TPA identified 192 (25.1%) patients as sarcopenic, while TPV identified 152 patients (19.9%). Three hundred sixty-nine (48.4%) patients experienced a postoperative complication. While TPA-sarcopenia was not associated with higher risk of postoperative complications (OR 1.06; P = 0.72), sarcopenia defined by TPV was associated with morbidity (OR 1.79; P = 0.002). On multivariable analysis, TPV-sarcopenia remained independently associated with an increased risk of postoperative complications (OR 1.69; P = 0.006), as well as long-term survival (HR 1.46; P = 0.006).

CONCLUSION

The use of TPV to define sarcopenia was associated with both short- and long-term outcomes following resection of pancreatic cancer. Assessment of the entire volume of the psoas muscle (TPV) may be a better means to define sarcopenia rather than a single axial image.

Lung cancer-a fractal viewpoint

Fractals are mathematical constructs that show self-similarity over a range of scales and non-integer (fractal) dimensions. Owing to these properties, fractal geometry can be used to efficiently estimate the geometrical complexity, and the irregularity of shapes and patterns observed in lung tumour growth (over space or time), whereas the use of traditional Euclidean geometry in such calculations is more challenging. The application of fractal analysis in biomedical imaging and time series has shown considerable promise for measuring processes as varied as heart and respiratory rates, neuronal cell characterization, and vascular development. Despite the advantages of fractal mathematics and numerous studies demonstrating its applicability to lung cancer research, many researchers and clinicians remain unaware of its potential. Therefore, this Review aims to introduce the fundamental basis of fractals and to illustrate how analysis of fractal dimension (FD) and associated measurements, such as lacunarity (texture) can be performed. We describe the fractal nature of the lung and explain why this organ is particularly suited to fractal analysis. Studies that have used fractal analyses to quantify changes in nuclear and chromatin FD in primary and metastatic tumour cells, and clinical imaging studies that correlated changes in the FD of tumours on CT and/or PET images with tumour growth and treatment responses are reviewed. Moreover, the potential use of these techniques in the diagnosis and therapeutic management of lung cancer are discussed.

Anatomy packing with hierarchical segments: an algorithm for segmentation of pulmonary nodules in CT images

BACKGROUND

This paper proposes a semantic segmentation algorithm that provides the spatial distribution patterns of pulmonary ground-glass nodules with solid portions in computed tomography (CT) images.

METHODS

The proposed segmentation algorithm, anatomy packing with hierarchical segments (APHS), performs pulmonary nodule segmentation and quantification in CT images. In particular, the APHS algorithm consists of two essential processes: hierarchical segmentation tree construction and anatomy packing. It constructs the hierarchical segmentation tree based on region attributes and local contour cues along the region boundaries. Each node of the tree corresponds to the soft boundary associated with a family of nested segmentations through different scales applied by a hierarchical segmentation operator that is used to decompose the image in a structurally coherent manner. The anatomy packing process detects and localizes individual object instances by optimizing a hierarchical conditional random field model. Ninety-two histopathologically confirmed pulmonary nodules were used to evaluate the performance of the proposed APHS algorithm. Further, a comparative study was conducted with two conventional multi-label image segmentation algorithms based on four assessment metrics: the modified Williams index, percentage statistic, overlapping ratio, and difference ratio.

RESULTS

Under the same framework, the proposed APHS algorithm was applied to two clinical applications: multi-label segmentation of nodules with a solid portion and surrounding tissues and pulmonary nodule segmentation. The results obtained indicate that the APHS-generated boundaries are comparable to manual delineations with a modified Williams index of 1.013. Further, the resulting segmentation of the APHS algorithm is also better than that achieved by two conventional multi-label image segmentation algorithms.

CONCLUSIONS

The proposed two-level hierarchical segmentation algorithm effectively labelled the pulmonary nodule and its surrounding anatomic structures in lung CT images. This suggests that the generated multi-label structures can potentially serve as the basis for developing related clinical applications.

Volumetric evaluation of hepatic tumors: multi-vendor, multi-reader liver phantom study

PURPOSE

To compare liver lesion volume measurement on multiple 3D software platforms using a liver phantom.

METHODS

An anthropomorphic phantom constructed with ten liver lesions of varying size, attenuation, and shape with known volume and long axis measurement was scanned (120 kVp, 80-440 smart mA, NI 12). DICOM data were uploaded to five commercially available 3D visualization systems and manual tumor volume was obtained by three-independent readers. Accuracy and reproducibility of linear and volume measurements were compared. The two most promising systems were then compared with an additional prototype system by two readers using both manual and semi-automated measurement with similar comparison between linear and volume measures. Measurements were performed on 5- and 1.25-mm data sets. Inter- and intra-observer variability was also assessed.

RESULTS

Overall mean % volume error on the five commercially available software systems (averaging all ten liver lesions among all three readers) was 8.0% ± 7.5%, 13.7% ± 11.2%, 14.2% ± 15.2%, 16.4% ± 14.8 %, and 16.9% ± 13.8%, varying almost twofold across vendor. Moderate inter-observer variability was present. Volume measurement was slightly more accurate than linear measurement, but linear measurement was more reproducible across readers and systems. On the two "best" systems, the manual measurement method was more accurate than the automated method (p = 0.001). The prototype system demonstrated superior semi-automated assessment, with a mean % volume error of 5.3% ± 4.1% (vs. 17.8% ± 11.1% and 31.5% ± 19.7%, p < 0.001), with improved inter- and intra-observer variability.

CONCLUSIONS

Accuracy and reproducibility of volume assessment of liver lesions varies significantly by vendor, which has important implications for clinical use.

Radiologic-pathologic correlation of mesothelioma tumor volume

OBJECTIVES

Tumor volume promises to become a more important factor in patient management. Mesothelioma, with its unique morphology and complex growth pattern, presents a challenging target for tumor volumetrics derived from computed tomography (CT) scans. This study evaluated the validity of image-based mesothelioma tumor volume against the physical volume of the tumor bulk captured by the images.

MATERIALS AND METHODS

Twenty-eight patients underwent CT scanning prior to pleurectomy/decortication with an intent to achieve a macroscopic complete resection. A radiologist manually outlined the tumor border in all CT sections in which tumor appeared in the pre-surgery scan. CT-based tumor volume was computed as the number of image pixels enclosed by all tumor outlines across all sections in the scan multiplied by the physical dimensions of the voxel of tissue captured by each image pixel. The gross tumor specimen volume was measured ex vivo through a water-displacement technique. Correlation between CT volume and pathology volume was calculated.

RESULTS

A correlation coefficient r-squared value of 0.66 was found between CT-based tumor volume and gross tumor specimen volume. Differences between the mean volume (either CT volume or pathology volume) across tumors of different T stages did not achieve statistical significance.

CONCLUSION

Despite a modest correlation between CT-based tumor volume and gross tumor specimen volume, image-based volumetry for mesothelioma is not straightforward-perhaps, in part, due to the challenges of distinguishing tumor borders from adjacent structures and perhaps, in part, due to a complex pathologic reference standard.

Revisiting the relationship between tumour volume and diameter in advanced NSCLC patients: An exercise to maximize the utility of each measure to assess response to therapy

AIM

To revisit the presumed relationship between tumour diameter and volume in advanced non-small-cell lung cancer (NSCLC) patients, and determine whether the measured volume using volume-analysis software and its proportional changes during therapy matches with the calculated volume obtained from the presumed relationship and results in concordant response assessment.

MATERIALS AND METHODS

Twenty-three patients with stage IIIB/IV NSCLC with a total of 53 measurable lung lesions, treated in a phase II trial of erlotinib, were studied with institutional review board approval. Tumour volume and diameter were measured at baseline and at the first follow-up computed tomography (CT) examination using volume-analysis software. Using the measured diameter (2r) and the equation, calculated volume was obtained as (4/3)πr(3) at baseline and at the follow-up. Percent volume change was obtained by comparing to baseline for measured and calculated volumes, and response assessment was assigned.

RESULTS

The measured volume was significantly smaller than the calculated volume at baseline (median 11,488.9 mm(3) versus 17,148.6 mm(3); p < 0.0001), with a concordance correlation coefficient (CCC) of 0.7022. At follow-up, the measured volume was once again significantly smaller than the calculated volume (median 6573.5 mm(3) versus 9198.1 mm(3); p = 0.0022), with a CCC of 0.7408. Response assessment by calculated versus measured volume changes had only moderate agreement (weighted κ = 0.545), with discordant assessment results in 20% (8/40) of lesions.

CONCLUSION

Calculated volume based on the presumed relationship significantly differed from the measured volume in advanced NSCLC patients, with only moderate concordance in response assessment, indicating the limitations of presumed relationship.

Tumor volume decrease at 8 weeks is associated with longer survival in EGFR-mutant advanced non-small-cell lung cancer patients treated with EGFR TKI

BACKGROUND

The study investigated whether tumor volume changes at 8 weeks of therapy is associated with outcomes in advanced non-small-cell lung cancer (NSCLC) patients harboring sensitizing epidermal growth factor receptor (EGFR) mutations treated with EGFR tyrosine kinase inhibitors (TKIs).

METHODS

In 56 advanced NSCLC patients with sensitizing EGFR mutations treated with first-line erlotinib or gefitinib, tumor volumes of dominant lung lesions were measured on baseline and follow-up computed tomography, and were analyzed for association with survival.

RESULTS

Among 56 eligible patients, the median tumor volume was 17.8 cm (range, 1.3-172.7 cm) on the baseline scans. Forty-nine patients had follow-up computed tomography at approximately 8 weeks; the median tumor volume at 8 weeks was 7.1 cm (range, 0.4-62.3 cm), with the median proportional volume change of -59% (range, -90% to +91%) from baseline. The proportional volume change at 8 weeks was associated with survival (p = 0.02). Using the cutoff value of 38% volume decrease (75th percentile) at 8 weeks, patients with volume decrease more than 38% (n = 37) had a median overall survival of 43.5 months compared with 16.3 months among those with volume decrease of 38% or less (n = 12; p = 0.01). The median progression-free survival for patients with more than 38% volume decrease was 12.6 months, compared with 5.5 months for those with 38% or lesser volume decrease (p = 0.2).

CONCLUSION

The proportional volume change at 8 weeks is associated with overall survival in EGFR-mutant advanced NSCLC patients treated with first-line EGFR-TKIs. The observation of the study, if confirmed in larger study cohorts, indicates that tumor volume analysis at 8 weeks may provide an early marker for survival, and contribute to therapeutic decision making by identifying patients who may benefit from additional anticancer therapy after 8 weeks of EGFR-TKI therapy.