Calculated Tumor Volume Research Articles

NIMG-06. AUTOMATED VOLUMETRY OF MENINGIOMAS IN CONTRAST-ENHANCED T1-WEIGHTED MRI USING DEEP LEARNING

Abstract BACKGROUND With the widespread use of MRI equipment and brain docks, there are more opportunities to perform follow-up observation for meningiomas. In recent years, attempts have been made to predict prognosis by using tumor volume as a highly objective imaging biomarker. On the other hand, manual lesion extraction by a reader with anatomical knowledge is indispensable for volume measurement, which requires a certain amount of labor and time. This is a major barrier to the generation of evidence and clinical application in this field. OBJECTIVE To establish the clinical significance of tumor volume as an imaging biomarker in meningiomas, and to develop a simple and highly reproducible application for automated volume measurement using artificial intelligence, and to investigate its accuracy and potential for clinical application. METHODS 178 patients with meningiomas who underwent MRI at Osaka University Hospital were included in the study. Contrast-enhanced T1-weighted images were used for manual lesion extraction by two neurosurgeons. These annotated image data were randomly divided into training (90%) and testing (10%). The deeplabV3 model was used to train the artificial intelligence, and leave-one-out cross-validation was used to train and validate the automated model. The test data were used for comparison, and the agreement rate (Dice index) on the images of the automatically extracted regions and the error rate of the calculated tumor volume (mean square error rate: RMSPE) were used as indices of measurement performance. RESULTS The average agreement rate between the automatically extracted area and the test data was 92.3±5.1%. The error rate of tumor volume was 9.5±1.2%. CONCLUSION This application using artificial intelligence was considered to have a certain validity in the accuracy of automatic lesion extraction. This method, which enables simple tumor volume measurement, is expected to create new imaging biomarkers that will contribute to the optimization and personalization of meningioma treatment.

Surgery enhances the effectiveness of peptide receptor radionuclide therapy in metastatic gastroenteropancreatic neuroendocrine tumors

BackgroundWith the advent of peptide receptor radionuclide therapy, the timing and sequence of surgery in the treatment of metastatic gastroenteropancreatic neuroendocrine tumors merits further study. We hypothesized that surgery before peptide receptor radionuclide therapy might enhance its effectiveness in patients with metastatic gastroenteropancreatic neuroendocrine tumors. MethodsEighty-nine patients with metastatic well-differentiated gastroenteropancreatic neuroendocrine tumors treated with 177Lutetium-dotatate peptide receptor radionuclide therapy between 2018 and 2023 were included. Fifty-six patients underwent surgery (primary tumor resection and/or liver debulking) before peptide receptor radionuclide therapy and 33 patients did not. Primary outcome was progression-free survival according to Response Evaluation Criteria in Solid Tumors. Pretreatment dotatate positron emission tomography/computed tomography was used to calculate tumor volumes. ResultsThe surgery and no-surgery groups were well-matched. Median progression-free survival after peptide receptor radionuclide therapy was 15.6 months (interquartile range, 9.1–22.7 months) in the no-surgery group compared with 26.1 months (interquartile range, 12.7–38.1 months) in the surgery group (P = .04). On subgroup analysis, median progression-free survival was 18.1 months (interquartile range, 11.9–38.4 months) in patients who underwent primary tumor resection only compared with 26.2 months (interquartile range, 14.0–38.1 months) in patients who underwent liver debulking (P = .04). Tumor volume was lowest in patients who underwent liver debulking (median 146.07 mL3) compared with no surgery (median 626.42 mL3) (P = .001). On univariable analysis, a tumor volume <138.8 mL3 was associated with longer progression-free survival (hazard ratio, 2.03; 95% confidence interval, 0.95–4.34, P = .05), with a median progression-free survival of 38.1 months (interquartile range, 16.9–41.3 months) compared with 17.8 months (interquartile range, 10.8–28.7 months). ConclusionSurgery may enhance the effectiveness of 177Lutetium-dotatate in the treatment of metastatic well-differentiated gastroenteropancreatic neuroendocrine tumors. This positive effect may be the result of a lower tumor volume in patients after surgery. Our findings fortify the concept of using surgical debulking to improve systemic therapies such as peptide receptor radionuclide therapy.

Pretherapeutic PSMA PET-Derived Semiquantitative Parameters as Predictors of PSA Response in Patients with mCRPC Receiving [ 177 Lu]Lu-PSMA-617 Radioligand Therapy.

Objective [ 177 Lu]Lu-prostate-specific membrane antigen (PSMA)-617 radioligand therapy (RLT) shows promise for metastatic castration-resistant prostate cancer (mCRPC) patients with positive PSMA positron emission tomography (PET) imaging. Identifying high-risk patients is crucial. We evaluated pretherapeutic PSMA PET-derived parameters to predict prostate-specific antigen (PSA) response in patients undergoing [ 177 Lu]Lu-PSMA-617 RLT. Materials and Methods We conducted a retrospective analysis among 27 patients (mean age: 71.0 ± 9.5 years; range: 52-85 years) who underwent PSMA PET/computed tomography (CT) and subsequent [ 177 Lu]Lu-PSMA-617 RLT between March 2019 and January 2023. After excluding patients with liver metastases, the number of patients left for analysis was 21 (14 responders and 7 nonresponders). Tumors were semiautomatically delineated with calculation of total tumor volume (PSMA-TV), lesion uptake (PSMA-TLU = PSMA-TV * standardized uptake value [SUV]mean), and lesion quotient (PSMA-TLQ = PSMA-TV/SUVmean) for each patient. Semiquantitative parameters were analyzed only in patients with mCRPC and no liver metastasis. Results In total, 17/27 patients (62.96%) had a decline in PSA levels; 15/27 patients (55.56%) experienced a decline of > 50%. Pretherapeutic PSMA PET/CT results revealed significant differences in PSMA-TV ( p = 0.003), PSMA-TLU ( p = 0.013), and PSMA-TLQ ( p = 0.011) between responders and nonresponders. SUVmax was significantly correlated to the best percentage change in PSA response after 177 Lu-PSMA-617 treatment ( r = -0.79, p = 0.006). No association was observed between PSMA-TV ( p = 0.367), PSMA-TLU ( p = 0.128), and PSMA-TLQ ( p = 0.556), with the best percentage change in PSA response after 177 Lu-PSMA-617 therapy. Conclusion Pretherapeutic PSMA PET-derived PSMA-TV, PSMA-TLU, and PSMA-TLQ were significant negative predictors of PSA response in patients with mCRPC and no liver metastasis receiving [ 177 Lu]Lu-PSMA-617 RLT.

Calculating Tumor Volume Using Three-Dimensional Models in Preoperative Soft-Tissue Sarcoma Surgical Planning: Does Size Matter?

This feasibility study aims to explore the use of three-dimensional virtual surgical planning to preoperatively determine the need for reconstructive surgery following resection of an extremity soft-tissue sarcoma. As flap reconstruction is performed more often in advanced disease, we hypothesized that tumor volume would be larger in the group of patients that had undergone flap reconstruction. All patients that were treated by surgical resection for an extremity soft-tissue sarcoma between 1 January 2016 and 1 October 2019 in the University Medical Center Groningen were included retrospectively. Three-dimensional models were created using the diagnostic magnetic resonance scan. Tumor volume was calculated for all patients. Three-dimensional tumor volume was 107.8 (349.1) mL in the group of patients that had undergone primary closure and 29.4 (47.4) mL in the group of patients in which a flap reconstruction was performed, p = 0.004. Three-dimensional tumor volume was 76.1 (295.3) mL in the group of patients with a complication following ESTS treatment, versus 57.0 (132.4) mL in patients with an uncomplicated course following ESTS treatment, p = 0.311. Patients who had undergone flap reconstruction had smaller tumor volumes compared to those in the group of patients treated by primary closure. Furthermore, a larger tumor volume did not result in complications for patients undergoing ESTS treatment. Therefore, tumor volume does not seem to influence the need for reconstruction. Despite the capability of three-dimensional virtual surgical planning to measure tumor volume, we do not recommend its utilization in the multidisciplinary extremity soft-tissue sarcoma treatment, considering the findings of the study.

The Value of Micro-CT in the Diagnosis of Lung Carcinoma: A Radio-Histopathological Perspective.

Micro-computed tomography (micro-CT) is a relatively new imaging modality and the three-dimensional (3D) images obtained via micro-CT allow researchers to collect both quantitative and qualitative information on various types of samples. Micro-CT could potentially be used to examine human diseases and several studies have been published on this topic in the last decade. In this study, the potential uses of micro-CT in understanding and evaluating lung carcinoma and the relevant studies conducted on lung and other tumors are summarized. Currently, the resolution of benchtop laboratory micro-CT units has not reached the levels that can be obtained with light microscopy, and it is not possible to detect the histopathological features (e.g., tumor type, adenocarcinoma pattern, spread through air spaces) required for lung cancer management. However, its ability to provide 3D images in any plane of section, without disturbing the integrity of the specimen, suggests that it can be used as an auxiliary technique, especially in surgical margin examination, the evaluation of tumor invasion in the entire specimen, and calculation of primary and metastatic tumor volume. Along with future developments in micro-CT technology, it can be expected that the image resolution will gradually improve, the examination time will decrease, and the relevant software will be more user friendly. As a result of these developments, micro-CT may enter pathology laboratories as an auxiliary method in the pathological evaluation of lung tumors. However, the safety, performance, and cost effectiveness of micro-CT in the areas of possible clinical application should be investigated. If micro-CT passes all these tests, it may lead to the convergence of radiology and pathology applications performed independently in separate units today, and the birth of a new type of diagnostician who has equal knowledge of the histological and radiological features of tumors.

Evaluation of A Computer-Aided Detection Software for Prostate Cancer Prediction: Excellent Diagnostic Accuracy Independent of Preanalytical Factors

Prostate cancer (PCa) is the most common noncutaneous cancer in men in the Western world. In addition to accurate diagnosis, Gleason grading and tumor volume estimates are critical for patient management. Computer-aided detection (CADe) software can be used to facilitate the diagnosis and improve the diagnostic accuracy and reporting consistency. However, preanalytical factors such as fixation and staining of prostate biopsy specimens and whole slide images (WSI) on scanners can vary significantly between pathology laboratories and may, therefore, impact the quality of WSI and utility of CADe algorithms. We evaluated the performance of a CADe software in predicting PCa on WSIs of prostate biopsy specimens and focused on whether there were any significant differences in image quality between WSIs obtained on different scanners and specimens from different histopathology laboratories. Thirty prostate biopsy specimens from 2 histopathology laboratories in the United States were included in this study. The hematoxylin and eosin slides of the biopsy specimens were scanned on 3 scanners, generating 90 WSIs. These WSIs were then analyzed using a CADe software (INIFY Prostate, Algorithm), which identified and annotated all areas suspicious for PCa and calculated the tumor volume (percentage area of the biopsy core involved). Study pathologists then reviewed the Algorithm’s annotations and tumor volume calculation to confirm the diagnosis and identify benign glands that were misclassified as cancer (false positive) and cancer glands that were misclassified as benign (false negative). The CADe software worked equally well on WSIs from all 3 scanners and from both laboratories, with similar sensitivity and specificity. The overall sensitivity was 99.4%, and specificity was 97%. The percentage of suspicious cancer areas calculated by the Algorithm was similar for all 3 scanners. For WSIs with small foci of cancer (<1 mm), the Algorithm identified all cancer glands (sensitivity, 100%). Preanalytical factors had no significant impact on whole slide imaging and subsequent application of a CADe software. Prediction accuracy could potentially be further improved by processing biopsy specimens in a centralized histology laboratory and training the Algorithm on WSIs from the same laboratory in order to minimize variations in preanalytical factors and optimize the diagnostic performance of the Algorithm.

Dendritic cells infected with recombinant adenoviral vector encoding mouse fibroblast activation protein-α and human livin α exert an antitumor effect against Lewis lung carcinoma in mice.

Fibroblast activation protein-α (FAP) and livin α are considered as cancer-associated fibroblasts (CAFs) and tumor-specific targets, respectively, for immunogenic tumor vaccines. This study is designed to decipher the antitumor effect of double-gene modified dendritic cells (DCs) on Lewis lung carcinoma (LLC). By encoding mouse FAP cDNA and human livin α (i.e., hlivin α) cDNA into recombinant adenoviral vector (rAd), rAd-FAP, rAd-hlivin α, and rAd-FAP/hlivin α were constructed, which were then transduced into mouse DCs. LLC-bearinig mice were immunized with the infected DCs (5 × 105 cells/mouse), followed by calculation of tumor volume and survival rate. The identification of CAFs from mouse LLC as well as the determination on expressions of FAP and livin α, was accomplished by western blot. Cytotoxic T lymphocyte assay was harnessed to assess the effect of the infected DCs on inducing splenic lymphocytes to lyse CAFs. DCs were successfully transduced with rAd-FAP/hlivin α in vitro. FAP was highly expressed in CAFs. CAFs were positive for α-SMA and negative for CD45 and CD31. Livin α level was upregulated in mouse LLC. Immunization with rAd-FAP/hlivin α-transduced DCs suppressed LLC volume and improved the survival of tumor-bearing mice. Immunization with rAd-FAP/hlivin α-transduced DCs enhanced the cytotoxic effect of splenic lymphocytes on LLC tumor-derived CAFs. Injection with rAd-FAP/hlivin α-transduced DCs promotes immune-enhanced tumor microenvironment by decreasing CAFs and suppresses tumor growth in LLC mouse models.

Calculation of Metabolic Tumor Volume in Diffuse Large B-Cell Lymphoma Using a Deep Learning-Aided Automated Method

Background: Metabolic tumor volume (MTV) has been shown to be a robust prognostic biomarker in diffuse large B cell lymphoma (DLBCL). Currently available semiautomatic software for calculating MTV can be tedious, time consuming and requires manual input from the reader, therefore, limiting its routine application in clinical research. Our objective was to develop a fully automated method for calculating MTV and to validate the algorithm by comparing the automated results with 2 experienced nuclear medicine (NM) readers. Methods: The automated method designed for this study employed a deep convolutional neural network to segment normal physiologic structures from the CT scans which demonstrate intense avidity on FDG PET scans, including the brain, heart, kidneys, and bladder. The segmentation model was built off the 2D dilated residual U-net using cross entropy and Dice loss as the objective function. The contours obtained for these structures were then automatically transferred and adapted to the PET scans according to their respective PET presentations by aid of an array of ad-hoc image processing algorithms including region growing, active contours, and fast matching. MTV was derived on the PET scans by thresholding with respect to 41% of the maximum SUV within the imaged body volume excluding the above-mentioned normal physiologic structures followed by filtering with a cutoff volume of 1 mL (Figure 1). The study cohort consisted of 100 patients with newly diagnosed DLBCL who were randomly selected from the Alliance/CALGB 50303 (NCT00118209) trial. De-identified imaging and clinical data were retrieved from The Cancer Imaging Archive. MTV and SUV of the lesion with the highest metabolic activity (SUVmax) were analyzed for the included patients by 2 experienced NM physicians using the Hermes Affinity Viewer and compared to the fully automated results from the developed algorithm. For examining agreement, we estimated Pearson's correlation coefficients and inter-class correlation coefficients (ICCs) along with corresponding 95% confidence intervals and p-values. For visualization, we displayed scatter plots and Bland-Altman plots between readers and the automated method. All tests were two-sided and statistical significance was considered when p<.05. Statistical software R was used for all statistical analyses. Results: Among 100 patients included in this final analysis, the mean MTV calculated by reader 1 was 226.47 mL (standard deviation (SD) 260.06 and coefficient of variation (CV) 114.83), for reader 2 was 226.799 mL (SD 261.965 and CV 115.505) and for the automated method (AM) was 205.704 mL (SD 245.825 and CV 119.504). Comparing reader 1 to reader 2, the Pearson's correlation coefficients and ICCs were 0.9997, p<.0001 and 1, p<.0001 (95%CI=1 to 1) for MTV and 1, p<.0001 and 1, p<.0001 (95%CI=1 to 1) for SUVmax, respectively. Comparing reader 1 to AM, the Pearson's correlation coefficients and ICCs were 0.9814, p<.0001 and 0.98, p<.0001 (95%CI=0.96 to 0.99) for MTV and 0.9868, p<.0001 and 1, p<.0001 (95%CI=0.99 to 1) for SUVmax, respectively. Comparing reader 2 to AM, the Pearson's correlation coefficients and ICCs were 0.9818, p<.0001 and 0.98, p<.0001 (95%CI=0.96 to 0.99) for MTV and 0.9868, p<.0001 and 1, p<.0001 (95%CI=0.99 to 1) for SUVmax, respectively. The Bland-Altman plots showed only relatively small systematic errors between the proposed method and the manual readings across the entire data range being examined for both MTV and SUVmax. Limitations of the automated segmentation algorithm occurred when tumor activity was located in close proximity to normal physiologic structures such as the bladder or kidneys or when normal anatomy had been distorted either due to the disease process or image artifacts such as misregistration or patient motion. Overall, the AM enabled faster MTV calculations (median time 5 minutes) compared to a semiautomatic approach (median time 20 minutes). Conclusion: The proposed automated method for calculating MTV demonstrates a high agreement with 2 experienced NM readers. Furthermore, the algorithm was highly accurate in classifying FDG-avidity in patients from a multicenter clinical trial involving 17 centers that obtained images on different scanner models with variable reconstruction settings. This approach possess the potential to integrate PET-based biomarkers in clinical trials. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

DAP10 integration in CAR-T cells enhances the killing of heterogeneous tumors by harnessing endogenous NKG2D

Although chimeric antigen receptor T (CAR-T) cells have achieved remarkable successes in hematological malignancies, the efficacies of CAR-T cells against solid tumors remains unsatisfactory. Heterogeneous antigen expression is one of the obstacles on its effective elimination of solid cancer cells. DNAX-activating protein 10 (DAP10) interacts with natural killer group 2D (NKG2D), acting as an adaptor that targets various malignant cells for surveillance. Here, we designed a DAP10 chimeric receptor that utilized native NKG2D on T cells to target NKG2D ligand-expressing cancer cells. We then tandemly incorporated it with anti-glypican 3 (GPC3) single-chain variable fragment (scFv) to construct a dual-antigen-targeting system. T cells expressing DAP10 chimeric receptor (DAP10-T cells) displayed with an enhancement on both cytotoxicity and cytokine secretion against solid cancer cell lines, and its tandem connection with anti-GPC3 scFv (CAR GPC3-DAP10-T cells) exhibited a dual-antigen-targeting capacity on eliminating heterogeneous cancer cells in vitro and suppressing the growth of heterogeneous cancer in vivo. Thus, this novel dual-targeting system enabled a high efficacy on killing cancer cells and extended the recognition profile of CAR-T cells toward tumors, which providing a potential strategy on treatment of solid cancer clinically.

Long-term outcomes in patients with localized Ewing sarcoma treated with interval-compressed chemotherapy: A long-term follow-up report from Children’s Oncology Group study AEWS0031.

11505 Background: Children’s Oncology Group study AEWS0031 demonstrated superior 5-year event-free survival (EFS) in patients with localized Ewing sarcoma (ES) receiving interval-compressed (IC) chemotherapy (every 2 weeks) compared to standard timing (ST) chemotherapy (every 3 weeks). We assessed the long-term outcome of patients treated on AEWS0031 to determine whether the survival advantage of IC chemotherapy was maintained at 10 years. Methods: AEWS0031 enrolled 568 eligible patients with localized ES. Patients were stratified into four groups by age (&lt;18 years and ≥ 18 years) and primary site (pelvic and non-pelvic), and randomized to receive 14 cycles of alternating vincristine-doxorubicin-cyclophosphamide and ifosfamide-etoposide given every 3 weeks (ST; Regimen A) vs. every 2 weeks (IC; Regimen B). For this updated report, one patient was excluded due to uncertainty of original diagnosis giving a total of 567 patients in this analysis. Data for tumor measurements and histologic response were collected retrospectively from institutional reports. EFS and overall survival (OS) were estimated using the Kaplan-Meier method and compared using the log-rank test and Gray’s test for cumulative incidence (CI). Results: The 10-year EFS for patients treated with IC chemo was 70% compared to 61% for ST chemo (p = 0.03), and the OS was 76% with IC chemo compared to 69% for ST chemo (p = 0.03). The 10-year CI of second malignant neoplasms (SMNs) for ST chemo was 4.2% [95% confidence interval: 2.4-7.5] compared to 3.2% (95% confidence interval: 1.6-6.3) for IC chemo (p = 0.5). There was a trend towards improved 10-year EFS in those receiving IC chemo both with non-pelvic (N = 477; 71% vs. 64%) and pelvic (N = 90; 67% vs. 43%) primary tumors. Similarly, the 10-year EFS was superior for patients treated with IC chemo in both the &lt; 18 years (N = 500; 73% vs. 64%) and ≥ 18 years (N = 67; 53% vs. 37%) age groups. Among the 184 patients with available histologic response data, the 10-year EFS from the time of local control was 76% for those with &lt; 10% viable tumor and 56% for those with ≥ 10% viable tumor (p = 0.01). Additional analysis comparing patients with any viable tumor vs. no viable tumor (NVT) by treatment regimen demonstrated that patients with NVT who received IC chemo had 10-year EFS and OS from local control of 91% and 97%, respectively. In the 210 patients for whom tumor volume calculations were possible, there was no difference in the 10-year EFS for patients with tumors &lt; 200 mL vs. ≥ 200 mL. Conclusions: With longer term follow-up, IC chemotherapy for localized ES is associated with superior EFS and OS without an increase in SMNs. This study suggests patients ≥ 18 years with poor necrosis or pelvic primary tumors remain at high risk for relapse despite IC chemo, emphasizing the need for alternative treatment strategies to improve their outcomes. Clinical trial information: NCT00006734.

Matrine Combined with Mammalian Target of Rapamycin Inhibitor Enhances Anti-Tumor Efficacy of dendritic cell Vaccines in hepatocellular carcinoma

ABSTRACT Dendritic cells (DCs), as the most important antigen-presenting cells, play a crucial role in T cell activation. The latest research showed that inhibition of the mammalian target of rapamycin (mTOR) could enhance DCs maturation, promoting antigen presentation. Matrine has been identified as one of the key alkaloids isolated from the roots of Sophora flavescens. In present study, we combined matrine and mTOR inhibitor KU0063794 to observe the DCs functions, especially the antigen presentation ability. DCs were activated by phosphate-buffered saline (PBS), lipopolysaccharide (LPS), LPS+KU0063794, LPS+Matrine, and LPS+KU0063794+Matrine. The surface markers in DCs, proliferation of T cells and cytokines were detected by flow cytometry, cell counting kit-8 (CCK-8) and enzyme-linked immunosorbent assay (ELISA), respectively. The lactate dehydrogenase (LDH) release test was used to detect the antitumor efficacy. The tumor growth curves were plotted by calculating tumor volume. The apoptosis was detected by Terminal-deoxynucleoitidyl Transferase-Mediated Nick End Labeling (TUNEL) method. Matrine combined with KU0063794 could enhance the maturity of DCs, T cells proliferation and cytokines secretion (P < 0.05). The cytotoxic T lymphocytes (CTL) killing efficacy of LPS+KU0063794+Matrine group was higher than other groups (P < 0.05). In vivo, the tumor weights and volumes in LPS+KU0063794+Matrine group were lower than other groups. The detections of tumor apoptosis were increased in LPS+KU0063794+Matrine group (P < 0.05). DC vaccine with mTOR inhibitor and matrine could significantly improve the efficacy of antitumor immunity in vitro and vivo. These findings illustrated that mTOR inhibitor and matrine, as two immunomodulators, could enhance DC activation and differentiation.

Role of MRI with diffusion and whole tumor volume calculation in detection of response in rectal cancer patients under therapy

Background: MRI examination of the rectum has evolved as the standard technique in the assessment of cancer rectum having multiplaner capabilities and high tissue contrast imaging. The aim of this study: The aim of this study is to evaluate the role of MRI in assessment of rectal neoplasm. Patients and methods: In this study we prospectively evaluated 40 patients (24 male -60%) and (16 females -40%), who referred to the MRI unit, Radiology department, (Minia Oncology Center) for further assessment of histopathology proven rectal carcinoma, during the period of (August 2019 ) to (August 2021). Results: 10% of patients (4 participants) had high rectal cancer while 55% of them (22 patients) had middle rectal cancer. On the other hand, 35% of them (14 patients) had low rectal cancer. 85% of participants (34 patients) were diagnosed as adenocarcinoma while the remaining 6 participants (15% of patients) were diagnosed as mucinous adenocarcinoma. 77.5% of patients (31 participants) had grade II rectal cancer while 9 patients (22.5% of participants) were diagnosed as grade III rectal cancer. On performing TNM staging, we found that the majority of cases; 37.5% of participants (15 patients); were found to be in stage IIA.

Diagnostic Accuracy of Calculated Tumor Volumes and Apparent Diffusion Coefficient Values in Predicting Endometrial Cancer Grade.

Background:Magnetic resonance imaging (MRI) has been shown to be an accurate imaging technique for the preoperative assessment of local staging of endometrial cancer and for evaluating the depth of myometrial invasion.Materials and Methods:This was a single-center retrospective study performed on patients with histopathologically proven endometrial carcinoma who underwent an MRI examination of the pelvis between October 2017 and May 2020.Results:In the present analysis, mean apparent diffusion coefficient (ADC) values for each histologic grade were 0.72 ± 0.13 × 10−3 mm2/s (G1), 0.76 ± 0.17 × 10−3 mm2/s (G2), and 0.74 ± 0.12 × 10−3 mm2/s (G3), respectively, showing no significant correlation between ADC values and tumor grade (P = 0.73). Overall, ADC minimum was significant in differentiating grades of endometrial carcinoma (P = 0.02) with the ability to differentiate Grade I and II lesions (P = 0.01). A mean tumor volume of 25.2 cc could differentiate low-grade tumors (Grade I and Grade II) from high-grade tumors (Grade III) with a sensitivity and specificity of 88% and specificity of 89%. The tumor volume/uterine volume ratio (TV/UV) differentiates high-grade tumors from low-grade tumors (P < 0.001), however, no significant difference in the ratio was observed among Grade I and II lesions (P = 0.48). The area under the curve of tumor volume was 0.875 (95% confidence interval 0.0–1.00) (P = 0.001), indicating that tumor volume was an effective tool for distinguishing high-grade and low-grade endometrioid adenocarcinomas. The corresponding sensitivity and specificity were 88.0% and 89.0%, respectively.Conclusion:Preoperative noninvasive radiological assessment for tumor volume, TV/ UV or tumor volume/uterine volume is important surrogate markers for preoperative prognostication of endometrial carcinoma.

COT-16 Development of automatic lesion extraction application using artificial intelligence for the purpose of simplifying tumor volume measurement of meningioma

BACKGROUND: With the widespread use of MRI equipment and brain scans, opportunities to perform follow-up examinations for meningiomas have increased. On the other hand, an objective evaluation index for meningiomas characterized by slow changes on imaging has not been established. To establish a volume-based evaluation index for meningoceles, we are developing an application for automatic lesion extraction using artificial intelligence as a highly reproducible tumor volume measurement technique that enables large volume image data processing. METHODS: In this study, 195 patients with meningioma who underwent contrast-enhanced MRI imaging at Osaka University Hospital were included. The images were manually extracted by three neurosurgeons and used as supervised data. deeplabV3 was used as the learning network. All the supervised data were randomly divided into training (80%) and testing (20%) data, and the application was constructed by deep learning and validation with 5-fold cross-validation. The matching rate of the area of the region automatically extracted by the device against the test data and the mean square error rate of the calculated tumor volume were used as indices of the product measurement performance. RESULTS: The matching rate using the automatic extraction application for the correct data(Dice index) was 91.5% on average. The mean squared error rate of the tumor volume calculated from these extracted regions was 8.84%. CONCLUSION: We consider that this application using artificial intelligence has a certain degree of validity in terms of the accuracy of extracted lesions. In the future, it is necessary not only to improve the performance of the equipment but also to clarify the clinical significance of the new imaging biomarkers based on tumor volume that can be obtained from these lesion extraction techniques.

Regression and pseudoprogression of pediatric optic pathway glioma in patients treated with proton beam therapy.

We examined regression patterns in pediatric optic pathway gliomas (OPGs) after proton beam therapy (PBT) and evaluated local control and visual outcomes. A total of 42 brain magnetic resonance imaging (MRI) scans from seven consecutive sporadic OPGs that were initially treated with chemotherapy and received PBT between June 2007 and September 2016 at the National Cancer Center, Korea were analyzed. Patients underwent brain MRI regularly before and after PBT. Total tumor, cystic lesion, and solid enhancing lesion area delineation and volume calculations were performed on gadolinium-enhanced T1-weighted MRI using Eclipse version 13, Varian. The median follow-up period after PBT was 70months (range 47-88). The median age at the time of PBT was 7years (range 4-16) and the median duration of chemotherapy before referral to PBT center was 25months (range 3-70). The median time to the greatest increase in cystic volume was 32months (range 12-43) after PBT. Solid enhancing lesion volume gradually decreased throughout the follow-up period. On an individual basis, total volume change was varied. However, on average, it regressed, although at a slower rate than solid enhancing lesion volume did. The local control rate was 85.7% (5-year progression-free survival rate, 80%; 5-year overall survival rate, 100%) and the rate of vision preservation was 71.4% (five of seven patients). The regression patterns in pediatric OPGs after PBT involve significant cystic change. Therefore, total volume is not appropriate for evaluating response. Care by a multidisciplinary team is necessary to manage clinical symptoms related to radiologic changes.

Intracranial meningioma surveillance using volumetrics from T2-weighted MRI.

The gold standard for imaging of meningiomas is MRI with gadolinium-based contrast agent. Due to increased costs, time, and uncertain chronic effects of gadolinium exposure, use of noncontrast T2-weighted imaging (T2WI) in lieu of contrast-enhanced MRI has been an increasing focus of research across various diagnostic scenarios. The purpose of this study was to evaluate the diagnostic accuracy of T2WI in detecting changes in meningioma tumor volume. Imaging and clinical data were reviewed for 82 consecutive patients undergoing MR-surveillance of intracranial meningioma. Using volumetric-T2WI, two neuroradiologists independently calculated tumor volumes. Measurements were compared to a baseline study contrast-enhanced T1 tumor volume. Using contrast-enhanced sequences as the reference standard, statistical analysis was performed to determine the accuracy of T2WI in detecting changes of meningioma volume. Using only T2WI, readers detected meningioma volume change ≥ 20% in 19/82 patients and volume change <20% in 63/82 patients. Reader accuracy for detecting change in tumor volume on T2WI ≥ 20% was 0.85, sensitivity 0.65, specificity 0.93, positive predictive value (PPV) 0.79, and negative predictive value (NPV) 0.87. For meningiomas >1 ml, reader accuracy for detecting change in tumor volume on T2WI ≥20% was 0.90, sensitivity 0.78, specificity 0.95, PPV 0.88, and NPV 0.91. Change in tumor volume on T2WI ≥20% was detected with 100% accuracy for posterior fossa meningiomas. Inter-reader agreement for all meningiomas was moderate (κ = 0.45) improving to substantial agreement (κ = 0.77) with tumor volumes >1 ml. Volumetric-T2WI detects changes in meningioma volume with comparable accuracy to gold standard T1 postcontrast imaging, particularly with higher tumor volumes and posterior fossa locations.

MP11-16 COMPARISON OF QUANTITATIVE WHOLE-BODY MRI AND BONE SCAN FOR THE PROGNOSIS OF PATIENTS WITH METASTATIC HORMONE-NAïVE PROSTATE CANCER: A PROSPECTIVE STUDY

You have accessJournal of UrologyProstate Cancer: Staging (MP11)1 Sep 2021MP11-16 COMPARISON OF QUANTITATIVE WHOLE-BODY MRI AND BONE SCAN FOR THE PROGNOSIS OF PATIENTS WITH METASTATIC HORMONE-NAïVE PROSTATE CANCER: A PROSPECTIVE STUDY Hiromichi Iwamura, Jun Ito, Shingo Hatakeyama, Yuta Kojima, Takuma Narita, Teppei Okamoto, Naoki Fujita, Kyo Togashi, Tohru Yoneyama, Hayato Yamamoto, Takahiro Yoneyama, Yasuhiro Hashimoto, Yasuhiro Kaiho, Makoto Sato, and Chikara Ohyama Hiromichi IwamuraHiromichi Iwamura More articles by this author , Jun ItoJun Ito More articles by this author , Shingo HatakeyamaShingo Hatakeyama More articles by this author , Yuta KojimaYuta Kojima More articles by this author , Takuma NaritaTakuma Narita More articles by this author , Teppei OkamotoTeppei Okamoto More articles by this author , Naoki FujitaNaoki Fujita More articles by this author , Kyo TogashiKyo Togashi More articles by this author , Tohru YoneyamaTohru Yoneyama More articles by this author , Hayato YamamotoHayato Yamamoto More articles by this author , Takahiro YoneyamaTakahiro Yoneyama More articles by this author , Yasuhiro HashimotoYasuhiro Hashimoto More articles by this author , Yasuhiro KaihoYasuhiro Kaiho More articles by this author , Makoto SatoMakoto Sato More articles by this author , and Chikara OhyamaChikara Ohyama More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000001984.16AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: To compare the prognostic significance of quantitative whole-body MRI (WB-MRI) and bone scan (BS) in patients with metastatic hormone-naive prostate cancer (mHNPC). METHODS: We prospectively enrolled 22 patients with mHNPC. All the patients underwent WB-MRI and BS at baseline and treated with first-line gonadotropin-releasing hormone-antagonist monotherapy. Total diffusion volume (tDV) was calculated using Attractive BD-Score®. Bone scan index (BSI) was calculated using BONENAVI. The associations between clinical factors including the calculated tumor volume and castration-resistant PC-free survival (CRPC-FS) were evaluated using Kaplan–Meier and Cox-regression analyses. RESULTS: The median age and follow-up periods were 73 years (69-82) and 17 months (12-26), respectively. The median tDV and BSI at baseline were 104.2 mL (71.6-165.4) and 0.44% (0.16-1.70), respectively. Kaplan–Meier analyses showed that high tDV group showed significantly worse CRPC-FS compared with low tDV group (2y; 89% vs 23%, p=0.013), whereas, CRPC-FS in high and low BSI groups were not significantly different (2y; 71% vs 46%, p=0.118). In multivariate analysis, high tDV (≥104.2 mL) was an independent risk factor for CRPC-FS (HR 69.6, p=0.019), however, high BSI (≥0.44%) was not associated with CRPC-FS (HR 1.38, p=0.540). CONCLUSIONS: Our results suggested that prognostic significance of quantitative WB-MRI is superior to that of quantitative BS. Patients with high tDV may be potential candidate for upfront intensive therapy. Source of Funding: None © 2021 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 206Issue Supplement 3September 2021Page: e185-e185 Advertisement Copyright & Permissions© 2021 by American Urological Association Education and Research, Inc.MetricsAuthor Information Hiromichi Iwamura More articles by this author Jun Ito More articles by this author Shingo Hatakeyama More articles by this author Yuta Kojima More articles by this author Takuma Narita More articles by this author Teppei Okamoto More articles by this author Naoki Fujita More articles by this author Kyo Togashi More articles by this author Tohru Yoneyama More articles by this author Hayato Yamamoto More articles by this author Takahiro Yoneyama More articles by this author Yasuhiro Hashimoto More articles by this author Yasuhiro Kaiho More articles by this author Makoto Sato More articles by this author Chikara Ohyama More articles by this author Expand All Advertisement Loading ...

Perbandingan Pegukuran Volume Tumor Brain MRI Menggunakan Teknik Manual Dan Metode Active Contour

Background: A brain tumor is a mass of brain cells that grow abnormally. In radiological terms, a brain tumor is called a space occupying lesion (SOL) which generally means a lump. Radiologists or radiology specialists in identifying brain tumors will analyze the results of Magnetic Resonance Imaging (MRI) Brain images with post-processing techniques using a menu in a 3D editor called the region growing technique.Methods:This type of research is a quasi-experimental research design using Posttest Only Without Control Group Design. The research plan will be carried out at Hermina Hospital Bekasi using 32 samples of brain tumor MRI images, the sample size is obtained by the sample size formula for two paired populations according to Sastroasmoro (2011). Bivariate data analysis, if the data is normally distributed (p value 0.05), then the Paired T-test statistical test is performed and if the data is not normally distributed (p value 0.05) the Wilcoxon statistical test is performed.Results: The results of the analysis of brain tumors are followed by manual measurement of tumor volume using the region growing technique. It requires sufficient expertise and experience so that the diagnosis of tumor volume is given precisely and accurately so that its handling can be carried out wisely Evaluation of MRI images requires high accuracy, but doctors can make mistakes because the diagnosis is still done manually, such as errors in diagnosing the location of the tumor and the size of the object. The very complex structure of the human brain also presents its own difficulties in identifying brain tumors. Subjective factors can also affect manual doctor evaluations such as fatigue and uncontrolled time in evaluating an MRI image so that a digital image processing program is needed that can be done with a computational machine to assist doctors in evaluating an MRI image automatically. The active contour method can solve the problem of topological changes in a brain tumor image.Conclusion: The active contour method is able to classify images with high accuracy. So that it can increase the accuracy of the segmentation process for easy and fast medical diagnosis. The calculation of the volume of brain tumors can be done using the binaryization method which has been segmented through the final image produced by the active contour method. Tumor segmentation and automatic tumor volume calculation have great potential in clinical treatment by freeing doctors from the burden of manual labeling, digital image processing of brain tumors using the active contour method can be used as a complement to the MRI modality that radiologists can use in calculating brain tumor mass volume calculations

THE INFLUENCE OF VOLUMETRIC TUMOR DOUBLING TIME ON SURVIVAL OF PATIENTS WITH INTRACRANIAL TUMORS

Objective:To evaluate inuence of volumetric tumor doubling time on survival of patients with intracranial tumors. Study design: 20 patients with intracranial tumor of either sex and any age were included, if two imaging scans were available/could be done in which change in tomor volume was appreciable and the tumor margins were well demarcated. Based on change in tumor volume, tumor doubling time (DT) and predictive survival time (PST) were calculated. Patients were followed up for 6 months or longer for actual survival time (AST). Results: The histological grade was found to have a signicant correlation with DT (P value 0.046) and PST of the tumor (P value 0.038). DT and PSTwere found to be signicantly lower in high grade astrocytomas. Age, gender, tumor location and initial tumor volume were not found to have a signicant correlation with DTand PST. When DTwas compared to PST, excellent correlation was seen which was statistically signicant (Pvalue &lt; 0.001) and suggested a linear relationship. Conclusion: Computed Tomography (CT) &amp; Magnetic Resonance Imaging (MRI) can accurately dene the intracranial tumors and can reliably measure their volume. Calculation of tumor volume, change in tumor volume, DT and PST based on imaging studies is easy and reproducible. DT and PST have an excellent correlation &amp; there is a linear relationship between the two. Histological grade and DT are the signicant prognostic factors while age, gender, tumor location and initial tumor volume are not signicant prognostic factors in patients with brain tumors.

Prediction of soft tissue coverage following distal femur bone sarcoma resection: A preliminary report.

We aimed to examine the predictability of the need for soft tissue reconstruction during limb-sparing surgery through preoperative magnetic resonance (MR) imaging in patients diagnosed with a malignant bone tumor in the distal femur. The study included 42 patients who were operated for a bone sarcoma of the distal femur at our clinic between 2016 and 2018. The recorded parameters included the demographic characteristics of the patients, tumor diagnosis, tumor side, total tumor volume, tumor soft tissue component volume, tumor soft tissue component volume-to-total tumor volume ratio, tumor localization by MR imaging, the need for soft tissue reconstruction, the muscles used for soft tissue reconstruction, the biopsy site, and the biopsy type. Tumor volume was calculated on MR imaging of the distal femur region performed before surgery. Our study established cut-off values for soft tissue reconstruction need following resection as a total tumor volume of 96.4 cm3 , a tumor soft tissue component volume of 22 cm3 , a tumor soft tissue component volume-to-total tumor volume ratio of 48.9%, and tumor localization in two different regions on axial distal femoral MR images. Considering these cut-off values, by calculating tumor volume values preoperatively we can predict the need for rotational muscle flaps for soft tissue coverage following distal femur bone sarcoma resection and endoprosthesis reconstruction. Anticipating the need for soft tissue reconstruction may affect the duration and success of the operation.