Mechanism of ERBB2 gene overexpression by the formation of super-enhancer with genomic structural abnormalities in lung adenocarcinoma without clinically actionable genetic alterations.

BACKGROUND: In an extensive genomic analysis of lung adenocarcinomas (LUADs), driver mutations have been recognized as potential targets for molecular therapy. However, there remain cases where target genes are not identified. Super-enhancers and structural variants are frequently identified in several hundred loci per case. Despite this, most cancer research has approached the analysis of these data sets separately, without merging and comparing the data, and there are no examples of integrated analysis in LUAD. METHODS: We performed an integrated analysis of super-enhancers and structural variants in a cohort of 174 LUAD cases that lacked clinically actionable genetic alterations. To achieve this, we conducted both WGS and H3K27Ac ChIP-seq analyses using samples with driver gene mutations and those without, allowing for a comprehensive investigation of the potential roles of super-enhancer in LUAD cases. RESULTS: We demonstrate that most genes situated in these overlapped regions were associated with known and previously unknown driver genes and aberrant expression resulting from the formation of super-enhancers accompanied by genomic structural abnormalities. Hi-C and long-read sequencing data further corroborated this insight. When we employed CRISPR-Cas9 to induce structural abnormalities that mimicked cases with outlier ERBB2 gene expression, we observed an elevation in ERBB2 expression. These abnormalities are associated with a higher risk of recurrence after surgery, irrespective of the presence or absence of driver mutations. CONCLUSIONS: Our findings suggest that aberrant gene expression linked to structural polymorphisms can significantly impact personalized cancer treatment by facilitating the identification of driver mutations and prognostic factors, contributing to a more comprehensive understanding of LUAD pathogenesis.

Characteristics of false-positive lesions in evaluating colorectal liver metastases on gadoxetic acid-enhanced magnetic resonance imaging.

PURPOSE: Gadoxetic acid-enhanced MRI (Gd-EOB-MRI) shows higher sensitivity for colorectal liver metastases (CRLM) than contrast-enhanced computed tomography (CECT). However, the details of false-positive lesions for each imaging modality are unknown. METHODS: Cases undergoing hepatectomy for CRLM following a preoperative evaluation with both CECT and Gd-EOB-MRI between July 2008 and December 2016 were reviewed. The false-positive and false-negative rates were assessed for each modality, and the characteristics of false-positive lesions were evaluated. RESULTS: We evaluated 275 partial hepatectomies in 242 patients without preoperative chemotherapy. Among the 275 hepatectomies, 546 lesions were recognized by CECT and/or Gd-EOB-MRI. The false-positive rates for CECT and Gd-EOB-MRI were 4% (18/422) and 7% (37/536), respectively. The size of false-positive lesions was significantly smaller than that of correctly diagnosed lesions (median: 28 mm [3-120 mm] vs 7.6 mm [320 mm], P < 0.001). Compared with the 233 correctly diagnosed lesions ≤ 20 mm in diameter, false-positive lesions were more frequently located near the liver surface or vasculobiliary structures than true lesions (33/37 [89%] vs 149/233 [64%], respectively; P = 0.0021). CONCLUSION: Gd-EOB-MRI had a 7% false-positive rate. A small size and tumor location near the surface or near vasculobiliary structures were associated with false positivity.

Circumferential Resection Margin Status as a Predictive Factor for Recurrence in Preoperative MRI for Advanced Lower Rectal Cancer Without Preoperative Therapy.

BACKGROUND: In Japan, total mesorectal excision plus lateral lymph node dissection without preoperative therapy is the standard treatment for advanced lower rectal cancer. Although long-term oncologic outcomes with preoperative therapy based on circumferential resection margin status in preoperative MRI has been reported, outcomes without preoperative therapy are unknown. OBJECTIVE: This study evaluated long-term oncologic outcomes of radical surgery without preoperative therapy in advanced lower rectal cancer based on circumferential resection margin status in preoperative MRI, with the aim of defining appropriate patient populations for preoperative therapy. DESIGN: This retrospective analysis compared long-term oncologic outcomes with preoperative MRI in patients with lower rectal cancer. SETTINGS: Patients were identified through a database managed by our institute. PATIENTS: In total, 338 patients with lower rectal cancer who underwent radical surgery between 2000 and 2014 at the National Cancer Center Hospital without preoperative therapy were included. MAIN OUTCOME MEASURES: The main outcome was relapse-free survival. RESULTS: The median follow-up period was 61.7 months (range, 3-153 months). Five-year relapse-free survival rates in MRI-predicted circumferential resection margin negative patients and positive patients were 76.0% and 55.6% (p < 0.001). Univariate and multivariate analyses revealed pN stage (HR, 2.35; 95% CI, 1.470-3.770; p < 0.001), lymphatic invasion (HR, 2.03; 95% CI, 1.302-3.176; p = 0.002), venous invasion (HR, 2.15; 95% CI, 1.184-3.9; p = 0.01), surgical procedure (HR, 1.72; 95% CI, 1.115-2.665; p = 0.01), and MRI-predicted circumferential resection margin (HR, 1.850; 95% CI, 1.206-2.838; p = 0.0051) to be independent risk factors for postoperative recurrence. LIMITATIONS: This study was retrospective in design. CONCLUSIONS: Magnetic resonance imaging-predicted circumferential resection margin was associated with relapse-free survival without preoperative therapy, indicating its potential for use in selecting optimal preoperative therapy. See Video Abstract at http://links.lww.com/DCR/B335. ESTADO DEL MARGEN DE RESECCIÓN CIRCUNFERENCIAL COMO FACTOR PREDICTIVO DE RECURRENCIA EN LA RESONANCIA MAGNÉTICA PREOPERATORIA, PARA EL CÁNCER RECTAL BAJO AVANZADO SIN TERAPIA PREOPERATORIA: En Japón, la escisión mesorrectal total con disección de ganglios linfáticos laterales y sin terapia preoperatoria, es el tratamiento estándar para el cáncer rectal bajo avanzado. Aunque se han reportado resultados oncológicos a largo plazo con terapia preoperatoria, basada en el estado del margen de resección circunferencial en la resonancia magnética preoperatoria, se desconocen los resultados sin terapia preoperatoria.Este estudio evaluó los resultados oncológicos a largo plazo de cirugía radical sin terapia preoperatoria, en cáncer rectal bajo avanzado, basado en el estado del margen de resección circunferencial en la resonancia magnética preoperatoria, con el objetivo de definir poblaciones de pacientes apropiadas para terapia preoperatoria.Este análisis retrospectivo comparó los resultados oncológicos a largo plazo con resonancia magnética preoperatoria, en pacientes con cáncer rectal bajo.Los pacientes fueron identificados a través de una base de datos administrada por nuestro instituto.Se incluyeron un total de 338 pacientes con cáncer rectal bajo, que se sometieron a cirugía radical entre 2000 y 2014 en el Hospital Nacional del Centro de Cáncer, sin terapia preoperatoria.El resultado principal fue la supervivencia libre de recaídas.La mediana del período de seguimiento fue de 61,7 meses (rango, 3-153 meses). Las tasas de supervivencia sin recaídas a cinco años, con margen de resección circunferencial predicho por resonancia magnética, en pacientes negativos y pacientes positivos fueron 76.0% y 55.6% (p <0.001), respectivamente. Los análisis univariados y multivariados revelaron estadio pN (razón de riesgo [HR], 2.35; intervalo de confianza [IC] del 95%, 1.470-3.770; p <0.001), invasión linfática (HR, 2.03; IC del 95%, 1.302-3.176; p = 0.002), invasión venosa (HR, 2.15; IC 95%, 1.184-3.9; p = 0.01), procedimiento quirúrgico (HR, 1.72; IC 95%, 1.115-2.665; p = 0.01) y circunferencial predicho por resonancia magnética en margen de resección (HR, 1.850; IC 95%, 1.206-2.838; p = 0.0051), como factores de riesgo independientes, para la recurrencia postoperatoria.Este estudio fue retrospectivo en diseño.El margen de resección circunferencial predicho de resonancia magnética, se asoció con una supervivencia libre de recaída sin terapia preoperatoria, lo que indica su potencial para uso en la selección de la terapia óptima preoperatoria. Consulte Video Resumen en http://links.lww.com/DCR/B335.

Preoperative T staging of colon cancer using CT colonography with multiplanar reconstruction: new diagnostic criteria based on "bordering vessels".

PURPOSE: Preoperative T staging of colon cancer, in particular, for distinguishing T3 from T2 and T4, has been a challenge. The aim of this study was to evaluate newly developed criteria for preoperative T staging of colorectal cancer using computed tomography colonography (CTC) with multiplanar reconstruction (MPR), based on the spatial relationship of tumors and "bordering vessels," that is, marginal vessels that are detectable by multi-detector row CT with MPR. METHODS: A total of 172 patients with colon and upper rectal cancer who underwent preoperative CTC and surgery between August 2011 and September 2013 were included. Preoperative T staging using the new criteria was performed prospectively and compared with pathologic results. RESULTS: Sensitivity, specificity, and accuracy of T staging by CTC using the new criteria were 63%, 80%, and 77% for T2 (n = 30); 72%, 94%, and 81% for T3 (n = 95); and 79%, 99%, and 97% for T4a (n = 14), respectively. Positive predictive value for T3 was 93%, indicating that a T3 diagnosis by CTC is precise. In addition, negative predictive value for pathological T4a was 98%, indicating that a "not T4a" diagnosis by CTC is also precise. CONCLUSIONS: Our newly developed criteria are useful for preoperative T staging, particularly for distinguishing T3 from T2 and T4.

Efficacy and Safety of Pazopanib for Recurrent or Metastatic Solitary Fibrous Tumor.

OBJECTIVE: To investigate the efficacy and safety of pazopanib for recurrent or metastatic solitary fibrous tumor (SFT) in first- and second-line settings. METHODS: Patients histologically diagnosed with SFT at our hospital who received pazopanib monotherapy for inoperable disease between January 2013 and November 2016 were eligible. We retrospectively investigated treatment outcomes according to the treatment lines and assessed adverse events. RESULTS: Nine patients were eligible. The median age was 67 years (range 42-81), and 6 patients (66.7%) were male. Four patients (50%) received pazopanib as second-line treatment. According to the RECIST and Choi criteria, the respective response rates were 0 and 50%, while the respective disease control rates were 88.9 and 75%. The median progression-free survival (PFS) was 6.2 months (95% confidence interval 3.2-8.8). Treatment line and high frequency of mitosis were not predictive of PFS (p = 0.67, 0.92). Two patients (22.2%) experienced elevated liver enzymes of grade 3 or higher. CONCLUSION: Pazopanib is an effective treatment option for recurrent or metastatic SFT in first- and second-line settings. Liver injury is a major adverse event and adequate treatment withdrawal and dose reduction should be considered when necessary.

Intersphincteric Resection Has Similar Long-term Oncologic Outcomes Compared With Abdominoperineal Resection for Low Rectal Cancer Without Preoperative Therapy: Results of Propensity Score Analyses.

BACKGROUND: Intersphincteric resection has been performed for very low rectal cancer in place of abdominoperineal resection to avoid permanent colostomy. OBJECTIVE: This study aimed to evaluate long-term oncologic outcomes of intersphincteric resection compared with abdominoperineal resection. DESIGN: In this retrospective study, propensity score matching and stratification analyses were performed to reduce the effects of confounding factors between groups, including age, sex, BMI, CEA value, tumor height, tumor depth, lymph node enlargement, and circumferential resection margin measured by MRI. SETTING: A database maintained at our institute was used to identify patients during the period between 2000 and 2014. PATIENTS: A total of 285 patients who underwent curative intersphincteric resection (n = 112) or abdominoperineal resection (n = 173) for stage I to III low rectal cancer without preoperative chemoradiotherapy were enrolled in this study. MAIN OUTCOME MEASURE: The main outcome was recurrence-free survival. RESULTS: Patients in the abdominoperineal resection group were more likely to have a preoperative diagnosis of advanced cancer before case matching. After case matching, clinical outcomes were similar between intersphincteric resection and abdominoperineal resection groups. Five-year relapse-free survival rates were 69.9% for the intersphincteric resection group and 67.9% for abdominoperineal resection group (p = 0.64), and were similar in the propensity score-matched cohorts (89 matched pairs). Three-year cumulative local recurrence rates were 7.3% for intersphincteric resection and 3.9% for abdominoperineal resection (p = 0.13). In the propensity score-matched model, the hazard ratio for recurrence after intersphincteric resection in comparison with abdominoperineal resection was 0.90. Stratification analysis revealed similar recurrence rates (HR, 0.75-1.68) for intersphincteric resection in comparison with abdominoperineal resection. LIMITATION: Eight covariates were incorporated into the model, but other covariates were not included. CONCLUSIONS: Our findings suggest similar oncologic outcomes for intersphincteric resection and abdominoperineal resection without preoperative chemoradiotherapy in patients with low rectal cancer adjusted for background variables. See Video Abstract at http://links.lww.com/DCR/A661.

Preoperative T staging using CT colonography with multiplanar reconstruction for very low rectal cancer.

BACKGROUND: Preoperative T staging of lower rectal cancer is an important criterion for selecting intersphincteric resection (ISR) or abdominoperineal resection (APR) as well as selecting neoadjuvant therapy. The aim of this study was to evaluate the accuracy of preoperative T staging using CT colonography (CTC) with multiplanar reconstruction (MPR), in which with the newest workstation the images can be analyzed with a slice thickness of 0.5 mm. METHODS: Between 2011 and 2013, 45 consecutive patients with very low rectal adenocarcinoma underwent CTC with MPR. The accuracy of preoperative T staging using CTC with MPR was evaluated. The accuracy of preoperative T staging using MRI in the same patient population (34 of 45 patients) was also examined. RESULTS: Overall accuracy of T staging was 89% (41/45) for CTC with MPR and 71% (24/34) for MRI. CTC with MPR was particularly sensitive for pT2 tumors (82%; 14/17), whereas MRI tended to overstage pT2 tumors and its sensitivity for pT2 was 53% (8/15). CONCLUSIONS: CTC with MPR, with an arbitrary selection, could be aligned to the tumor axis and better demonstrated tumor margins consecutively including the deepest section of the tumor. The accuracy of T2 and T3 staging using CTC with MPR seemed to surpass that of MRI, suggesting a potential role of CTC with MPR in preoperative T staging for very low rectal cancer.

Feasibility of Routine Application of Gadoxetic Acid-Enhanced MRI in Combination with Diffusion-Weighted MRI for the Preoperative Evaluation of Colorectal Liver Metastases.

BACKGROUND: Gadoxetic acid-enhanced magnetic resonance imaging (MRI) in combination with diffusion-weighted MRI (Gd-EOB-MRI/DWI) has become popular for evaluating colorectal liver metastases (CRLM). This retrospective observational study aimed to determine whether this procedure should be indicated prior to hepatectomy in all patients with CRLM. METHODS: A retrospective survey of relevant data of patients who had undergone hepatectomy for CRLM from 2008 to 2014 was performed. The rates of detection by contrast-enhanced computed tomography (CE-CT) and Gd-EOB-MRI/DWI were evaluated. In addition, relapse-free and overall survivals after primary hepatectomy were compared between patients who had undergone only CE-CT versus those who had undergone both CE-CT and Gd-EOB-MRI/DWI. RESULTS: In all, 419 pathologically confirmed CRLM were resected in 202 hepatectomies in 177 patients. The sensitivity of detection of CRLM was 77 % for CE-CT and 93 % for Gd-EOB-MRI/DWI (P < 0.01). The sensitivity of detection of 1-5, 6-10, and 11-15 mm CRLM by CE-CT was 9.6 % (5/52), 47 % (26/55), and 76 % (57/75), respectively, whereas that by Gd-EOB-MRI/DWI was 54 % (28/52), 91 % (50/55), and 99 % (74/75), respectively; these differences are significant (P < 0.01 for all three groups). Relapse-free (P = 0.99) and overall survival (P = 0.79) did not differ significantly between 37 patients evaluated preoperatively by only CE-CT and 168 patients evaluated by both CE-CT and Gd-EOB-MRI/DWI. CONCLUSION: Gd-EOB-MRI/DWI detects small CRLM (≤15 mm) with higher sensitivity than CE-CT. However, whether Gd-EOB-MRI/DWI should be a routine component of preoperative evaluation remains unclear in terms of survival benefit.

Prognostic impact of extramural venous invasion detected by contrast-enhanced CT colonography in colon cancer.

BACKGROUND: The impact of computed tomography (CT)-detected extramural venous invasion on the recurrence of colon cancer is not fully understood. The aim of this study was to investigate the clinical significance of extramural venous invasion diagnosed before surgery by contrast-enhanced CT colonography using three-dimensional multiplanar reconstruction images. METHODS: Patients with colon cancer staged greater than or equal to T2 and/or stage I-III who underwent contrast-enhanced CT colonography between 2013 and 2018 at the National Cancer Center Hospital in Japan were retrospectively investigated for CT-detected extramural venous invasion. Inter-observer agreement for the detection of CT-detected extramural venous invasion was evaluated and Kaplan-Meier survival curves were plotted for recurrence-free survival using CT-TNM staging and CT-detected extramural venous invasion. Preoperative clinical variables were analysed using Cox regression for recurrence-free survival. RESULTS: Out of 922 eligible patients, 544 cases were analysed (50 (9.2 per cent) were diagnosed as positive for CT-detected extramural venous invasion and 494 (90.8 per cent) were diagnosed as negative for CT-detected extramural venous invasion). The inter-observer agreement for CT-detected extramural venous invasion had a κ coefficient of 0.830. The group positive for CT-detected extramural venous invasion had a median follow-up of 62.1 months, whereas the group negative for CT-detected extramural venous invasion had a median follow-up of 60.7 months. When CT-TNM stage was stratified according to CT-detected extramural venous invasion status, CT-T3 N(-)extramural venous invasion(+) had a poor prognosis compared with CT-T3 N(-)extramural venous invasion(-) and CT-stage I (5-year recurrence-free survival of 50.6 versus 89.3 and 90.1 per cent respectively; P < 0.001). In CT-stage III, the group positive for CT-detected extramural venous invasion also had a poor prognosis compared with the group negative for CT-detected extramural venous invasion (5-year recurrence-free survival of 52.0 versus 78.5 per cent respectively; P = 0.003). Multivariable analysis revealed that recurrence was associated with CT-T4 (HR 3.10, 95 per cent c.i. 1.85 to 5.20; P < 0.001) and CT-detected extramural venous invasion (HR 3.08, 95 per cent c.i. 1.90 to 5.00; P < 0.001). CONCLUSION: CT-detected extramural venous invasion was found to be an independent predictor of recurrence and could be used in combination with preoperative TNM staging to identify patients at high risk of recurrence.

Sketch-based semantic retrieval of medical images.

The volume of medical images stored in hospitals is rapidly increasing; however, the utilization of these accumulated medical images remains limited. Existing content-based medical image retrieval (CBMIR) systems typically require example images, leading to practical limitations, such as the lack of customizable, fine-grained image retrieval, the inability to search without example images, and difficulty in retrieving rare cases. In this paper, we introduce a sketch-based medical image retrieval (SBMIR) system that enables users to find images of interest without the need for example images. The key concept is feature decomposition of medical images, which allows the entire feature of a medical image to be decomposed into and reconstructed from normal and abnormal features. Building on this concept, our SBMIR system provides an easy-to-use two-step graphical user interface: users first select a template image to specify a normal feature and then draw a semantic sketch of the disease on the template image to represent an abnormal feature. The system integrates both types of input to construct a query vector and retrieves reference images. For evaluation, ten healthcare professionals participated in a user test using two datasets. Consequently, our SBMIR system enabled users to overcome previous challenges, including image retrieval based on fine-grained image characteristics, image retrieval without example images, and image retrieval for rare cases. Our SBMIR system provides on-demand, customizable medical image retrieval, thereby expanding the utility of medical image databases.

Ability of preoperative 3.0-Tesla magnetic resonance imaging to predict the absence of side-specific extracapsular extension of prostate cancer.

OBJECTIVE: Recent studies have shown an improvement in prostate cancer diagnosis with the use of 3.0-Tesla magnetic resonance imaging. We retrospectively assessed the ability of this imaging technique to predict side-specific extracapsular extension of prostate cancer. METHODS: From October 2007 to August 2011, prostatectomy was carried out in 396 patients after preoperative 3.0-Tesla magnetic resonance imaging. Among these, 132 (primary sample) and 134 patients (validation sample) underwent 12-core prostate biopsy at the National Cancer Center Hospital of Tokyo, Japan, and at other institutions, respectively. In the primary dataset, univariate and multivariate analyses were carried out to predict side-specific extracapsular extension using variables determined preoperatively, including 3.0-Tesla magnetic resonance imaging findings (T2-weighted and diffusion-weighted imaging). A prediction model was then constructed and applied to the validation study sample. RESULTS: Multivariate analysis identified four significant independent predictors (P < 0.05), including a biopsy Gleason score of ≥8, positive 3.0-Tesla diffusion-weighted magnetic resonance imaging findings, ≥2 positive biopsy cores on each side and a maximum percentage of positive cores ≥31% on each side. The negative predictive value was 93.9% in the combination model with these four predictors, meanwhile the positive predictive value was 33.8%. Good reproducibility of these four significant predictors and the combination model was observed in the validation study sample. CONCLUSIONS: The side-specific extracapsular extension prediction by the biopsy Gleason score and factors associated with tumor location, including a positive 3.0-Tesla diffusion-weighted magnetic resonance imaging finding, have a high negative predictive value, but a low positive predictive value.

Colorectal laterally spreading tumors by computed tomographic colonography.

To date, few reports focused primarily on detecting colorectal laterally spreading tumors (LSTs) have been published. The aim of this study was to determine the visibility of LSTs on computed tomographic colonography (CTC) compared with that on colonoscopy as a standard. We retrospectively reviewed and matched data on endoscopic and CTC reports in 157 patients (161 LSTs) who received a multidetector CT scan using contrast media immediately after total colonoscopy at the National Cancer Center Hospital in Tokyo, Japan, between December 2005 and August 2010. The results of the total colonoscopy were known at the time of the CTC procedure and reading. Of the 161 LSTs detected on colonoscopy, 138 were observed and matched by CTC (86%). Of the 91 granular type LSTs (LST-Gs), 88 (97%) were observed and matched, while of the 70 non-granular type LSTs (LST-NGs), 50 (71%) were observed and matched by CTC (p<0.0001). CTC enabled observation of 73% (22/30) of 20-29 mm, 83% (35/42) of 30-39 mm, 88% (49/56) of 40-59 mm, and 97% (32/33) of ≥60 mm tumors. The rate of observed LSTs by CTC was 86% (97% of LST-G, 71% of LST-NG) of the LSTs found during total colonoscopy.

Pharmacokinetic parameters from 3-Tesla DCE-MRI as surrogate biomarkers of antitumor effects of bevacizumab plus FOLFIRI in colorectal cancer with liver metastasis.

Bevacizumab (BV) is an antivascular endothelial growth factor antibody. When administered with other chemotherapeutic drugs, BV-combined regimens prolong survival of colorectal cancer patients. We conducted a phase II trial to confirm the pharmacokinetic parameters from 3-Tesla dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) as surrogate biomarkers of BV + FOLFIRI regimen efficacy in colorectal cancer with liver metastases. DCE-MRI was performed before treatment, on the seventh day after first treatment and every 8 weeks thereafter using a 3-Tesla MRI system. DCE-MRI parameters-area under the contrast concentration versus time curve at 90 and 180 s (AUC90 and AUC180, respectively) after contrast injection, and volume transfer constant of contrast agents (K(trans) and K(ep) ) were calculated from liver metastases. Fifty-eight liver metastases were analyzed. Univariate analysis revealed that a decrease in K(trans) ratios (ΔK(trans) ), K(ep) ratios (ΔK(ep) ), AUC90 ratios (ΔAUC90) and AUC180 ratios (ΔAUC180) correlated with higher response (all p < 0.0001) and longer time to progression (TTP) (ΔK(trans) : p = 0.001; ΔK(ep) : p = 0.004; ΔAUC90: p = 0.006; ΔAUC180: p < 0.0001). Multivariate analysis showed that ΔAUC180 was correlated with higher response (p = 0.009), and ΔK(trans) and ΔAUC180 were correlated with longer TTP (ΔK(trans) : p = 0.001; ΔAUC180: p = 0.024). ΔK(trans) and ΔAUC180 are pharmacodynamic biomarkers of the blood perfusion of BV + FOLFIRI. Our data suggest that ΔK(trans) and ΔK(ep) can predict response to chemotherapy at 1 week. Changes in 3-Tesla DCE-MRI parameters confirmed the potential of these biomarkers of blood perfusion as surrogate predictors of response and TTP.

Neoadjuvant chemotherapy in breast cancer: prediction of pathologic response with PET/CT and dynamic contrast-enhanced MR imaging--prospective assessment.

PURPOSE: To clarify whether fluorine 18 ((18)F) fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) and dynamic contrast-enhanced (DCE) magnetic resonance (MR) imaging performed after two cycles of neoadjuvant chemotherapy (NAC) can be used to predict pathologic response in breast cancer. MATERIALS AND METHODS: Institutional human research committee approval and written informed consent were obtained. Accuracy after two cycles of NAC for predicting pathologic complete response (pCR) was examined in 142 women (mean age, 57 years: range, 43-72 years) with histologically proved breast cancer between December 2005 and February 2009. Quantitative PET/CT and DCE MR imaging were performed at baseline and after two cycles of NAC. Parameters of PET/CT and of blood flow and microvascular permeability at DCE MR were compared with pathologic response. Patients were also evaluated after NAC by using Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 based on DCE MR measurements and European Organization for Research and Treatment of Cancer (EORTC) criteria and PET Response Criteria in Solid Tumors (PERCIST) 1.0 based on PET/CT measurements. Multiple logistic regression analyses were performed to examine continuous variables at PET/CT and DCE MR to predict pCR, and diagnostic accuracies were compared with the McNemar test. RESULTS: Significant decrease from baseline of all parameters at PET/CT and DCE MR was observed after NAC. Therapeutic response was obtained in 24 patients (17%) with pCR and 118 (83%) without pCR. Sensitivity, specificity, and accuracy to predict pCR were 45.5%, 85.5%, and 82.4%, respectively, with RECIST and 70.4%, 95.7%, and 90.8%, respectively, with EORTC and PERCIST. Multiple logistic regression revealed three significant independent predictors of pCR: percentage maximum standardized uptake value (%SUV(max)) (odds ratio [OR], 1.22; 95% confidence interval [CI]: 1.11, 1.34; P < .0001), percentage rate constant (%k(ep)) (OR, 1.07; CI: 1.03, 1.12; P = .002), and percentage area under the time-intensity curve over 90 seconds (%AUC(90)) (OR, 1.04; CI: 1.01, 1.07; P = .048). When diagnostic accuracies are compared, PET/CT is superior to DCE MR for the prediction of pCR (%SUV(max) [90.1%] vs %κ(ep) [83.8%] or %AUC(90) [76.8%]; P < .05). CONCLUSION: The sensitivities of %SUV(max) (66.7%), %k(ep) (51.7%), and %AUC(90) (50.0%) at (18)F-FDG PET/CT and DCE MR after two cycles of NAC are not acceptable, but the specificities (96.4%, 92.0%, and 95.2%, respectively) are high for stratification of pCR cases in breast cancer.

Prediction of treatment outcomes in patients with chest wall sarcoma: evaluation with PET/CT.

OBJECTIVE: The aim of this study was to investigate the prognostic implications of (18)F-2-fluoro-2-deoxy-d-glucose positron emission tomography/computed tomography in patients with chest wall sarcoma. METHODS: Positron emission tomography/computed tomography scans of 42 patients (mean age: 46 years) with chest wall sarcomas were analyzed. Pathologic confirmation was obtained by surgical specimens in all patients. Tumor grade assessed by Ki-67 (MIB-1) immunohistochemical analysis and expression of glucose transporter protein 1 were compared with a maximum standardized uptake value. Univariate and multivariate analyses were conducted for estimates of overall and event-free survivals. RESULTS: The median maximum standardized uptake value of the tumor was 10.2 and the median MIB-1 index of the tumor was 32.5%. Glucose transporter protein 1 expression was found in 29 patients (69%). Univariate analyses revealed that surgery, chemotherapy, MIB-1 labeling index (cut-off 32.5%), MIB-1 grade, glucose transporter protein 1 expression and maximum standardized uptake value were possible predictors for overall and event-free survival. Multivariate analysis revealed that surgery (hazard ratio, 4.852; P = 0.017), maximum standardized uptake value (hazard ratio, 3.077; P = 0.037) and MIB-1 labeling index (hazard ratio, 6.549; P = 0.003) were independent predictors of event-free survival. In addition, surgery (hazard ratio, 4.092; P = 0.021) and maximum standardized uptake value (hazard ratio, 2.968; P = 0.027) were independent predictors of overall survival. CONCLUSIONS: (18)F-2-fluoro-2-deoxy-d-glucose positron emission tomography/computed tomography allows the prediction of prognosis after treatment in patients with chest wall sarcoma and may be useful in selecting high-risk patients for more risk-adapted treatments.

Observing deep radiomics for the classification of glioma grades.

Deep learning is a promising method for medical image analysis because it can automatically acquire meaningful representations from raw data. However, a technical challenge lies in the difficulty of determining which types of internal representation are associated with a specific task, because feature vectors can vary dynamically according to individual inputs. Here, based on the magnetic resonance imaging (MRI) of gliomas, we propose a novel method to extract a shareable set of feature vectors that encode various parts in tumor imaging phenotypes. By applying vector quantization to latent representations, features extracted by an encoder are replaced with a fixed set of feature vectors. Hence, the set of feature vectors can be used in downstream tasks as imaging markers, which we call deep radiomics. Using deep radiomics, a classifier is established using logistic regression to predict the glioma grade with 90% accuracy. We also devise an algorithm to visualize the image region encoded by each feature vector, and demonstrate that the classification model preferentially relies on feature vectors associated with the presence or absence of contrast enhancement in tumor regions. Our proposal provides a data-driven approach to enhance the understanding of the imaging appearance of gliomas.

Assessing Versatile Machine Learning Models for Glioma Radiogenomic Studies across Hospitals.

Radiogenomics use non-invasively obtained imaging data, such as magnetic resonance imaging (MRI), to predict critical biomarkers of patients. Developing an accurate machine learning (ML) technique for MRI requires data from hundreds of patients, which cannot be gathered from any single local hospital. Hence, a model universally applicable to multiple cohorts/hospitals is required. We applied various ML and image pre-processing procedures on a glioma dataset from The Cancer Image Archive (TCIA, n = 159). The models that showed a high level of accuracy in predicting glioblastoma or WHO Grade II and III glioma using the TCIA dataset, were then tested for the data from the National Cancer Center Hospital, Japan (NCC, n = 166) whether they could maintain similar levels of high accuracy. Results: we confirmed that our ML procedure achieved a level of accuracy (AUROC = 0.904) comparable to that shown previously by the deep-learning methods using TCIA. However, when we directly applied the model to the NCC dataset, its AUROC dropped to 0.383. Introduction of standardization and dimension reduction procedures before classification without re-training improved the prediction accuracy obtained using NCC (0.804) without a loss in prediction accuracy for the TCIA dataset. Furthermore, we confirmed the same tendency in a model for IDH1/2 mutation prediction with standardization and application of dimension reduction that was also applicable to multiple hospitals. Our results demonstrated that overfitting may occur when an ML method providing the highest accuracy in a small training dataset is used for different heterogeneous data sets, and suggested a promising process for developing an ML method applicable to multiple cohorts.

Decomposing normal and abnormal features of medical images for content-based image retrieval of glioma imaging.

In medical imaging, the characteristics purely derived from a disease should reflect the extent to which abnormal findings deviate from the normal features. Indeed, physicians often need corresponding images without abnormal findings of interest or, conversely, images that contain similar abnormal findings regardless of normal anatomical context. This is called comparative diagnostic reading of medical images, which is essential for a correct diagnosis. To support comparative diagnostic reading, content-based image retrieval (CBIR) that can selectively utilize normal and abnormal features in medical images as two separable semantic components will be useful. In this study, we propose a neural network architecture to decompose the semantic components of medical images into two latent codes: normal anatomy code and abnormal anatomy code. The normal anatomy code represents counterfactual normal anatomies that should have existed if the sample is healthy, whereas the abnormal anatomy code attributes to abnormal changes that reflect deviation from the normal baseline. By calculating the similarity based on either normal or abnormal anatomy codes or the combination of the two codes, our algorithm can retrieve images according to the selected semantic component from a dataset consisting of brain magnetic resonance images of gliomas. Moreover, it can utilize a synthetic query vector combining normal and abnormal anatomy codes from two different query images. To evaluate whether the retrieved images are acquired according to the targeted semantic component, the overlap of the ground-truth labels is calculated as metrics of the semantic consistency. Our algorithm provides a flexible CBIR framework by handling the decomposed features with qualitatively and quantitatively remarkable results.

A New Era of Neuro-Oncology Research Pioneered by Multi-Omics Analysis and Machine Learning.

Although the incidence of central nervous system (CNS) cancers is not high, it significantly reduces a patient's quality of life and results in high mortality rates. A low incidence also means a low number of cases, which in turn means a low amount of information. To compensate, researchers have tried to increase the amount of information available from a single test using high-throughput technologies. This approach, referred to as single-omics analysis, has only been partially successful as one type of data may not be able to appropriately describe all the characteristics of a tumor. It is presently unclear what type of data can describe a particular clinical situation. One way to solve this problem is to use multi-omics data. When using many types of data, a selected data type or a combination of them may effectively resolve a clinical question. Hence, we conducted a comprehensive survey of papers in the field of neuro-oncology that used multi-omics data for analysis and found that most of the papers utilized machine learning techniques. This fact shows that it is useful to utilize machine learning techniques in multi-omics analysis. In this review, we discuss the current status of multi-omics analysis in the field of neuro-oncology and the importance of using machine learning techniques.