Multicenter radio-multiomic analysis for predicting breast cancer outcome and unravelling imaging-biological connection.

Radiomics offers a noninvasive avenue for predicting clinicopathological factors. However, thorough investigations into a robust breast cancer outcome-predicting model and its biological significance remain limited. This study develops a robust radiomic model for prognosis prediction, and further excavates its biological foundation and transferring prediction performance. We retrospectively collected preoperative dynamic contrast-enhanced MRI data from three distinct breast cancer patient cohorts. In FUSCC cohort (n = 466), Lasso was used to select features correlated with patient prognosis and multivariate Cox regression was utilized to integrate these features and build the radiomic risk model, while multiomic analysis was conducted to investigate the model's biological implications. DUKE cohort (n = 619) and I-SPY1 cohort (n = 128) were used to test the performance of the radiomic signature in outcome prediction. A thirteen-feature radiomic signature was identified in the FUSCC cohort training set and validated in the FUSCC cohort testing set, DUKE cohort and I-SPY1 cohort for predicting relapse-free survival (RFS) and overall survival (OS) (RFS: p = 0.013, p = 0.024 and p = 0.035; OS: p = 0.036, p = 0.005 and p = 0.027 in the three cohorts). Multiomic analysis uncovered metabolic dysregulation underlying the radiomic signature (ATP metabolic process: NES = 1.84, p-adjust = 0.02; cholesterol biosynthesis: NES = 1.79, p-adjust = 0.01). Regarding the therapeutic implications, the radiomic signature exhibited value when combining clinical factors for predicting the pathological complete response to neoadjuvant chemotherapy (DUKE cohort, AUC = 0.72; I-SPY1 cohort, AUC = 0.73). In conclusion, our study identified a breast cancer outcome-predicting radiomic signature in a multicenter radio-multiomic study, along with its correlations with multiomic features in prognostic risk assessment, laying the groundwork for future prospective clinical trials in personalized risk stratification and precision therapy.

Radiogenomic-based multiomic analysis reveals imaging intratumor heterogeneity phenotypes and therapeutic targets.

Intratumor heterogeneity (ITH) profoundly affects therapeutic responses and clinical outcomes. However, the widespread methods for assessing ITH based on genomic sequencing or pathological slides, which rely on limited tissue samples, may lead to inaccuracies due to potential sampling biases. Using a newly established multicenter breast cancer radio-multiomic dataset (n = 1474) encompassing radiomic features extracted from dynamic contrast-enhanced magnetic resonance images, we formulated a noninvasive radiomics methodology to effectively investigate ITH. Imaging ITH (IITH) was associated with genomic and pathological ITH, predicting poor prognosis independently in breast cancer. Through multiomic analysis, we identified activated oncogenic pathways and metabolic dysregulation in high-IITH tumors. Integrated metabolomic and transcriptomic analyses highlighted ferroptosis as a vulnerability and potential therapeutic target of high-IITH tumors. Collectively, this work emphasizes the superiority of radiomics in capturing ITH. Furthermore, we provide insights into the biological basis of IITH and propose therapeutic targets for breast cancers with elevated IITH.

Using a CT-based scale to evaluate disease extension and the resectability of locally advanced thyroid cancer.

OBJECTIVES: To establish a computed tomography (CT)-based scale to evaluate the resectability of locally advanced thyroid cancer. METHODS: This twin-centre retrospective study included 95 locally advanced thyroid cancer patients from the 1st centre as the training cohort and 31 patients from the 2nd centre as the testing cohort, who were categorised into the resectable and unresectable groups. Three radiologists scored the CT scans of each patient by evaluating the extension to the recurrent laryngeal nerve (RLN), trachea, oesophagus, artery, vein, soft tissue, and larynx. A 14-score scale (including all comprised structures) and a 12-score scale (excluding larynx) were developed. Receiver-operating characteristic (ROC) analysis was used to evaluate the performance of the scales. Stratified fivefold cross-validation and external verification were used to validate the scale. RESULTS: In the training cohort, compromised RLN (p < 0.001), trachea (p = 0.001), oesophagus (p = 0.002), artery (p < 0.001), vein (p = 0.005), and soft tissue (p < 0.001) were predictors for unresectability, while compromised larynx (p = 0.283) was not. The 12-score scale (AUC = 0.882, 95%CI: 0.812-0.952) was not inferior to the 14-score scale (AUC = 0.891, 95%CI: 0.823-0.960). In subgroup analysis, the AUCs of the 12-score scale were 0.826 for treatment-naïve patients and 0.976 for patients with prior surgery. The 12-score scale was further validated with a fivefold cross-validation analysis, with an overall accuracy of 78.9-89.4%. Finally, external validation using the testing cohort showed an AUC of 0.875. CONCLUSIONS: The researchers built a CT-based 12-score scale to evaluate the resectability of locally advanced thyroid cancer. Validation with a larger sample size is required to confirm the efficacy of the scale. CLINICAL RELEVANCE STATEMENT: This 12-score CT scale would help clinicians evaluate the resectability of locally advanced thyroid cancer. KEY POINTS: • The researchers built a 12-score CT scale (including recurrent laryngeal nerve, trachea, oesophagus, artery, vein, and soft tissue) to evaluate the resectability of locally advanced thyroid cancer. • This scale has the potential to help clinicians make treatment plans for locally advanced thyroid cancer.

Bidirectional crosstalk between therapeutic cancer vaccines and the tumor microenvironment: Beyond tumor antigens.

Immunotherapy has rejuvenated cancer therapy, especially after anti-PD-(L)1 came onto the scene. Among the many therapeutic options, therapeutic cancer vaccines are one of the most essential players. Although great progress has been made in research on tumor antigen vaccines, few phase III trials have shown clinical benefits. One of the reasons lies in obstruction from the tumor microenvironment (TME). Meanwhile, the therapeutic cancer vaccine reshapes the TME in an ambivalent way, leading to immune stimulation or immune escape. In this review, we summarize recent progress on the interaction between therapeutic cancer vaccines and the TME. With respect to vaccine resistance, innate immunosuppressive TME components and acquired resistance caused by vaccination are both involved. Understanding the underlying mechanism of this crosstalk provides insight into the treatment of cancer by directly targeting the TME or synergizing with other therapeutics.

Radiomics features for assessing tumor-infiltrating lymphocytes correlate with molecular traits of triple-negative breast cancer.

BACKGROUND: Tumor-infiltrating lymphocytes (TILs) have become a promising biomarker for assessing tumor immune microenvironment and predicting immunotherapy response. However, the assessment of TILs relies on invasive pathological slides. METHODS: We retrospectively extracted radiomics features from magnetic resonance imaging (MRI) to develop a radiomic cohort of triple-negative breast cancer (TNBC) (n = 139), among which 116 patients underwent transcriptomic sequencing. This radiomic cohort was randomly divided into the training cohort (n = 98) and validation cohort (n = 41) to develop radiomic signatures to predict the level of TILs through a non-invasive method. Pathologically evaluated TILs in the H&E sections were set as the gold standard. Elastic net and logistic regression were utilized to perform radiomics feature selection and model training, respectively. Transcriptomics was utilized to infer the detailed composition of the tumor microenvironment and to validate the radiomic signatures. RESULTS: We selected three radiomics features to develop a TILs-predicting radiomics model, which performed well in the validation cohort (AUC 0.790, 95% confidence interval (CI) 0.638-0.943). Further investigation with transcriptomics verified that tumors with high TILs predicted by radiomics (Rad-TILs) presented activated immune-related pathways, such as antigen processing and presentation, and immune checkpoints pathways. In addition, a hot immune microenvironment, including upregulated T cell infiltration gene signatures, cytokines, costimulators and major histocompatibility complexes (MHCs), as well as more CD8+ T cells, follicular helper T cells and memory B cells, was found in high Rad-TILs tumors. CONCLUSIONS: Our study demonstrated the feasibility of radiomics model in predicting TILs status and provided a method to make the features interpretable, which will pave the way toward precision medicine for TNBC.

Radiogenomic analysis reveals tumor heterogeneity of triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is a subset of breast cancer with an adverse prognosis and significant tumor heterogeneity. Here, we extract quantitative radiomic features from contrast-enhanced magnetic resonance images to construct a breast cancer radiomic dataset (n = 860) and a TNBC radiogenomic dataset (n = 202). We develop and validate radiomic signatures that can fairly differentiate TNBC from other breast cancer subtypes and distinguish molecular subtypes within TNBC. A radiomic feature that captures peritumoral heterogeneity is determined to be a prognostic factor for recurrence-free survival (p = 0.01) and overall survival (p = 0.004) in TNBC. Combined with the established matching TNBC transcriptomic and metabolomic data, we demonstrate that peritumoral heterogeneity is associated with immune suppression and upregulated fatty acid synthesis in tumor samples. Collectively, this multi-omic dataset serves as a useful public resource to promote precise subtyping of TNBC and helps to understand the biological significance of radiomics.

A Multiomics Signature Highlights Alterations Underlying Homologous Recombination Deficiency in Triple-Negative Breast Cancer.

BACKGROUND: Homologous recombination (HR) is a key pathway in DNA double-strand damage repair. HR deficiency (HRD) occurs more commonly in triple-negative breast cancers (TNBCs) than in other breast cancer subtypes. Several clinical trials have demonstrated the value of HRD in stratifying breast cancer patients into distinct groups based on their responses to poly(ADP ribose) polymerase inhibitors and chemotherapy. METHODS: We retrospectively collected TNBC samples to establish a multiomics cohort (n = 343) and explored the biological and phenotypic mechanisms underlying the better prognosis of patients with high HRD scores. Gene set enrichment analysis was conducted to elucidate the underlying pathways in patients with low HRD scores, and a radiomics model was established to predict the HRD score via a noninvasive method. RESULTS: Multivariable Cox analysis revealed the independent prognostic value of a low HRD score (hazard ratio 2.20, 95% confidence interval 1.05-4.59; p = 0.04). Furthermore, amino acid and lipid metabolism pathways were highly enriched in tumors from patients with low HRD scores, which was also demonstrated by differential abundant metabolite analysis. A noninvasive radiomics method was developed to predict the HRD status and it performed well in the independent validation cohort (support vector machine model: area under the curve [AUC] 0.739, sensitivity 0.571, and specificity 0.824; logistic regression model: AUC 0.695, sensitivity 0.571, and specificity 0.882). CONCLUSIONS: We revealed the prognostic value of the HRD score, predicted the HRD status with noninvasive radiomics features, and preliminarily explored druggable targets for TNBC patients with low HRD scores.

Development of MRI-Based Radiomics Model to Predict the Risk of Recurrence in Patients With Advanced High-Grade Serous Ovarian Carcinoma.

OBJECTIVE. The purpose of our study was to develop a radiomics model based on preoperative MRI and clinical information for predicting recurrence-free survival (RFS) in patients with advanced high-grade serous ovarian carcinoma (HGSOC). MATERIALS AND METHODS. This retrospective study enrolled 117 patients with HGSOC, including 90 patients with recurrence and 27 without recurrence; 1046 radiomics features were extracted from T2-weighted images and contrast-enhanced T1-weighted images using a manual segmentation method. L1 regularization-based least absolute shrinkage and selection operator (LASSO) regression was performed to select features, and the synthetic minority oversampling technique (SMOTE) was used to balance our dataset. A support vector machine (SVM) classifier was used to build the classification model. To validate the performance of the proposed models, we applied a leave-one-out cross-validation method to train and test the classifier. Cox proportional hazards regression, Harrell concordance index (C-index), and Kaplan-Meier plots analysis were used to evaluate the associations between radiomics signatures and RFS. RESULTS. The fusion radiomics-based model yielded a significantly higher AUC value of 0.85 in evaluating RFS than the model using contrast-enhanced T1-weighted imaging features alone or T2-weighted imaging features alone (AUC = 0.79 and 0.74 and p = .02 and .01, respectively). Kaplan-Meier survival curves showed significant differences between high and low recurrence risk in patients with HGSOC by different models. The fusion model combining radiomics features and clinical information showed higher performance than the clinical model (C-index = 0.62 and 0.60, respectively). CONCLUSION. The proposed MRI-based radiomics signatures may provide a potential way to develop a prediction model and can help identify patients with advanced HGSOC who have a high risk of recurrence.

Sclerosing adenosis: Ultrasonographic and mammographic findings and correlation with histopathology.

The present study was conducted to evaluate the radiological findings, particularly the ultrasonographic (US) characteristics of sclerosing adenosis (SA), and their correlation with histopathological results. A retrospective review identified 191 patients with a total of 200 lesions histopathologically confirmed as SA following breast surgery between July 2009 and December 2012. Of the 191 patients, 145 (151 lesions) with SA as the major component were included for US and mammographic (MG) analysis. All 145 patients analyzed were female, with a mean age ± standard deviation of 46.8±7.8 years (range, 25-71 years). All 145 patients underwent US examination and the imaging findings included heterogeneously echogenic areas in 9.3% (14/151), masses in 51.7% (78/151), masses with calcifications in 13.9% (21/151), focal acoustic shadowing in 4.0% (6/151) and were negative in 21.2% (32/151) patients. Among the 119 lesions with visible abnormalities, 87.4% (104/119) were hypoechoic, 58.0% (69/119) were irregular in shape, 52.1% (62/119) had an ill-defined margin, calcifications were found in 17.6% (21/119) and 7.6% (9/119) were hypervascular, while none of the characteristics mentioned above were significantly correlated with histopathology. A total of 136 patients underwent MG at the Fudan University Shanghai Cancer Center, and the imaging findings included microcalcifications in 31.6% (43/136), masses in 23.5% (32/136), asymmetric focal density in 14.7% (20/136), focal architectural distortion in 22.8% (31/136), and were negative in 7.4% (10/136). The mass lesions were fewer on MG compared with US (23.5 vs. 65.6%, respectively). The area under the curve of US distinguishing between benign and malignant lesions was significantly larger compared with that of MG (0.547 vs. 0.497, respectively; P=0.036). In the 60 lesions that were overestimated by Breast Imaging Reporting and Data System US category, one or more characteristics of malignancy were found on US imaging. The most common finding of SA was masses with or without calcifications on US and microcalcifications on MG. The accuracy of US was limited, but higher compared with that of MG; however, SA mimicking the characteristics of malignancy may contribute to misdiagnosis with US.

Digital breast tomosynthesis plus mammography, magnetic resonance imaging plus mammography and mammography alone: A comparison of diagnostic performance in symptomatic women.

PURPOSE: To compare the diagnostic efficiency of digital breast tomosynthesis (DBT) plus digital mammography (DM) and magnetic resonance imaging (MRI) plus DM in symptomatic women. MATERIALS AND METHODS: The protocol used in our study was accepted by the ethics committee at our hospital, and informed consent was obtained from all patients. Between June and December 2014, 197 patients with 238 histologically proven lesions all underwent DM, DBT and MRI. Two radiologists were responsible for interpreting all images according to the Breast Imaging Reporting and Data System (BI-RADS). The diagnostic performance of each method was assessed by receiver-operating characteristic (ROC) curve. The sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) were compared using McNemar's test and Fisher's exact test. A Kappa test was used to assess the interobserver agreement. RESULTS: The area under the ROC curve (AUC) was lower in the group that underwent DM alone (Radiologist1 [R1], 0.849; Radiologist2 [R2], 0.850) than in the group that underwent DBT plus DM (R1, 0.907, P = 0.0204; R2, 0.900, P = 0.0239) and MRI plus DM (R1, 0.939, P = 0.0006; R2, 0.935, P = 0.0009). However, the difference between the group that received DBT plus DM and the group that received MRI plus DM was not significant (R1, P = 0.1262; R2, P = 0.0843). The accuracy (R1, 71.8%; R2, 71.4%) and sensitivity (R1, 71.9%; R2, 71.2%) of DM were lower than those of DBT ((accuracy: R1, 85.3%, P = 0.001; R2, 83.6%, P < 0.001; sensitivity: R1,92.1%, P < 0.001; R2, 90.8%, P < 0.001) and MRI combined with DM (accuracy: R1, 90.3%, P = 0.001; R2, 90.7%, P < 0.001; sensitivity: R1, 94.7%, P < 0.001; R2, 95.4%, P < 0.001). In contrast, no significant difference was observed between DBT and MRI combined with DM (accuracy: R1, P = 0.644; R2, P = 0.360; sensitivity: R1, P = 0.502; R2, P = 0.359). The interobserver agreement of each method was excellent (k = 0.894 0.919 and 0.882 for DM, DBT and MRI combined with DM, respectively). CONCLUSION: The diagnostic performance of DBT and MRI combined with DM is superior to that of DM alone in symptomatic women; MRI plus DM is slightly better than that of DBT plus DM, but this difference was not statistically significant.

Imaging Manifestation of Adenoid Cystic Carcinoma of the Breast.

OBJECTIVE: This study aimed to describe the imaging features of adenoid cystic carcinoma (ACC) of the breast using multimode imaging. MATERIALS AND METHODS: The findings from mammography, sonography, magnetic resonance imaging, or digital breast tomosynthesis in 11 patients with histopathologically confirmed ACC of the breast were reviewed. The imaging criteria included location, shape, size, number, margin, calcification, attenuation, echo and/or signal intensity, internal mass enhancement pattern, and dynamic-enhancement characteristics. RESULTS: On mammography (n = 9), ACC demonstrated as an irregular or lobulated mass with indistinct or spiculated margins. Sonographically (n = 11), ACCs appeared as a hypoechoic solid or heterogeneous mass with minimum vascularity on color Doppler examination. With regard to magnetic resonance imaging (n = 9), 2 of the largest masses had an extensive high T2-weighted imaging (T2WI) signal and hypointense internal septations, which demonstrated delayed enhancement. Dynamic enhancement illustrated washout kinetics. The 7 smaller masses appeared isointense on T2WI, and their internal septations were unenhanced. Among them, 5 demonstrated plateau kinetics and 2 demonstrated persistent kinetics. CONCLUSIONS: Although ACC is a rare event in the breast, we believe that the following signs may suggest the diagnosis of this entity: a well-defined border, extensive high T2WI signals, and internal septations that demonstrate delayed enhancement in larger lesions.

Cisplatin plus gemcitabine versus paclitaxel plus gemcitabine as first-line therapy for metastatic triple-negative breast cancer (CBCSG006): a randomised, open-label, multicentre, phase 3 trial.

BACKGROUND: Platinum chemotherapy has a role in the treatment of metastatic triple-negative breast cancer but its full potential has probably not yet been reached. We assessed whether a cisplatin plus gemcitabine regimen was non-inferior to or superior to paclitaxel plus gemcitabine as first-line therapy for patients with metastatic triple-negative breast cancer. METHODS: For this open-label, randomised, phase 3, hybrid-designed trial undertaken at 12 institutions or hospitals in China, we included Chinese patients aged 18-70 years with previously untreated, histologically confirmed metastatic triple-negative breast cancer, and an ECOG performance status of 0-1. These patients were randomly assigned (1:1) to receive either cisplatin plus gemcitabine (cisplatin 75 mg/m(2) on day 1 and gemcitabine 1250 mg/m(2) on days 1 and 8) or paclitaxel plus gemcitabine (paclitaxel 175 mg/m(2) on day 1 and gemcitabine 1250 mg/m(2) on days 1 and 8) given intravenously every 3 weeks for a maximum of eight cycles. Randomisation was done centrally via an interactive web response system using block randomisation with a size of eight, with no stratification factors. Patients and investigator were aware of group assignments. The primary endpoint was progression-free survival and analyses were based on all patients who received at least one dose of assigned treatment. The margin used to establish non-inferiority was 1·2. If non-inferiority of cisplatin plus gemcitabine compared with paclitaxel plus gemcitabine was achieved, we would then test for superiority. The trial is registered with ClinicalTrials.gov, number NCT01287624. FINDINGS: From Jan 14, 2011, to Nov 14, 2013, 240 patients were assessed for eligibility and randomly assigned to treatment (120 in the cisplatin plus gemcitabine group and 120 in the paclitaxel plus gemcitabine group). 236 patients received at least one dose of assigned chemotherapy and were included in the modified intention-to-treat analysis (118 per group). After a median follow-up of 16·3 months (IQR 14·4-26·8) in the cisplatin plus gemcitabine group and 15·9 months (10·7-25·4) in the paclitaxel plus gemcitabine group, the hazard ratio for progression-free survival was 0·692 (95% CI 0·523-0·915; pnon-inferiority<0·0001, psuperiority=0·009, thus cisplatin plus gemcitabine was both non-inferior to and superior to paclitaxel plus gemcitabine. Median progression-free survival was 7·73 months (95% CI 6·16-9·30) in the cisplatin plus gemcitabine group and 6·47 months (5·76-7·18) in the paclitaxel plus gemcitabine group. Grade 3 or 4 adverse events that differed significantly between the two groups included nausea (eight [7%] vs one [<1%]), vomiting (13 [11%] vs one [<1%]), musculoskeletal pain (none vs ten [8%]), anaemia (39 [33%] vs six [5%]), and thrombocytopenia (38 [32%] vs three [3%]), for the cisplatin plus gemcitabine compared with the paclitaxel plus gemcitabine groups, respectively. In addition, patients in the cisplatin plus gemcitabine group had significantly fewer events of grade 1-4 alopecia (12 [10%] vs 42 [36%]) and peripheral neuropathy (27 [23%] vs 60 [51%]), but more grade 1-4 anorexia (33 [28%] vs 10 [8%]), constipation (29 [25%] vs 11 [9%]), hypomagnesaemia (27 [23%] vs five [4%]), and hypokalaemia (10 [8%] vs two [2%]). Serious drug-related adverse events were seen in three patients in the paclitaxel plus gemcitabine group (interstitial pneumonia, anaphylaxis, and severe neutropenia) and four in the cisplatin plus gemcitabine group (pathological bone fracture, thrombocytopenia with subcutaneous haemorrhage, severe anaemia, and cardiogenic syncope). There were no treatment-related deaths. INTERPRETATION: Cisplatin plus gemcitabine could be an alternative or even the preferred first-line chemotherapy strategy for patients with metastatic triple-negative breast cancer. FUNDING: Shanghai Natural Science Foundation.

Metabonomic studies of pancreatic cancer response to radiotherapy in a mouse xenograft model using magnetic resonance spectroscopy and principal components analysis.

AIM: To investigate the metabolic profiles of xenograft pancreatic cancer before and after radiotherapy by high-resolution magic angle spinning proton magnetic resonance spectroscopy (HRMAS (1)H NMR) combined with principal components analysis (PCA) and evaluate the radiotherapeutic effect. METHODS: The nude mouse xenograft model of human pancreatic cancer was established by injecting human pancreatic cancer cell SW1990 subcutaneously into the nude mice. When the tumors volume reached 800 mm(3), the mice received various radiation doses. Two weeks later, tumor tissue sections were prepared for running the NMR measurements. (1)H NMR and PCA were used to determine the changes in the metabolic profiles of tumor tissues after radiotherapy. Metabolic profiles of normal pancreas, pancreatic tumor tissues, and radiation- treated pancreatic tumor tissues were compared. RESULTS: Compared with (1)H NMR spectra of the normal nude mouse pancreas, the levels of choline, taurine, alanine, isoleucine, leucine, valine, lactate, and glutamic acid of the pancreatic cancer group were increased, whereas an opposite trend for phosphocholine, glycerophosphocholine, and betaine was observed. The ratio of phosphocholine to creatine, and glycerophosphocholine to creatine showed noticeable decrease in the pancreatic cancer group. After further evaluation of the tissue metabolic profile after treatment with three different radiation doses, no significant change in metabolites was observed in the (1)H NMR spectra, while the inhibition of tumor growth was in proportion to the radiation doses. However, PCA results showed that the levels of choline and betaine were decreased with the increased radiation dose, and conversely, the level of acetic acid was dramatically increased. CONCLUSION: The combined methods were demonstrated to have the potential for allowing early diagnosis and assessment of pancreatic cancer response to radiotherapy.

Imaging Findings of Follicular Dendritic Cell Sarcoma: Report of Four Cases

Follicular dendritic cell sarcoma is a rare malignant neoplasm and little is known about its radiological features. We present here four cases of follicular dendritic cell sarcomas and we provide the image characteristics of these tumors to help radiologists recognize this entity when making a diagnosis.

[Value of dynamic contrast-enhanced MRI in assessment of early response to neoadjuvant chemotherapy in breast cancer].

OBJECTIVE: To assess the value of dynamic contrast-enhanced MRI (DMRI) in predicting early response to neoadjuvant chemotherapy (NAC) in patients with locally advanced breast cancer (LABC) and to assess the accuracy of MRI in evaluation of residual disease after NAC. METHODS: Forty-three women with LABC (44 lesions, all were invasive ductal carcinoma) underwent DMRI before, after the first and final cycles of NAC. For each patient, the tumor volume, early enhancement ratio (E1), maximum enhancement ratio (Emax), and maximum enhancement time (Tmax), dynamic signal intensity-time curve were obtained during treatment. The residual tumor volumes obtained by DMRI were compared with pathological findings to assess the accuracy of DMRI. RESULTS: After the first cycle of NAC, the mean volume of responders decreased insignificantly (P = 0.055), but after NAC, mean volume of residual tumor decreased significantly (P = 0.000). Morphological changes: 29 cases showed a concentric shrinkage pattern while 7 cases showed a dendritic shrinkage pattern. Significant differences were found in E1, Emax and Tmax between responders and non-responders (P < 0.05). After the first cycle of NAC, E1, Emax and Tmax of responders changed significantly (P < 0.001), while there was no significant change in non-responders (P > 0.05). After NAC, the dynamic signal intensity-time types were changed in responders, and tended to be significantly flattening, while no significant change was found in non-responders. The residual tumor volume correlation coefficient between MRI and pathology measurements was very high (r = 0.866, P < 0.01). CONCLUSION: DMRI is useful to evaluate the early response to NAC in LABC. The presence and volume of residual tumor in LABC patients treated with NAC can be accurately evaluated by DMRI.

[Value of diffusion weighted imaging (DWI) in evaluating early response to neoadjuvant chemotherapy in locally advanced breast cancer].

OBJECTIVE: To evaluate the role and the performance of diffusion weighted imaging (DWI) for predicting the early response to neoadjuvant chemotherapy (NAC) in local advanced breast cancer (LABC) and to assess the accuracy of DWI in evaluating residual lesion after NAC. METHODS: 88 women with LABC (89 lesions) underwent DWI before and after the first and final cycle of NAC. For each patient, the apparent diffusion coefficient (ADC) values were compared between the baseline and follow-up to predict the early response to NAC. The residual tumor volumes were obtained using 3D maximum intensity projections (MIP) of DWI map, and were compared with pathological findings to assess the accuracy of DWI in detecting and measuring residual tumor. All results were proved or analyzed comparing with the data from histopathology. RESULTS: There were 68 lesions responding to NAC, while 21 non-responders. The baseline ADC values of responders and non-responders were (1.049 +/- 0.135) x 10(-3) mm(2)/s and (1.171 +/- 0.134) x 10(-3)mm(2)/s, respectively, with a significant difference (t = -2.731, P = 0.009 < 0.01). The ADC value measured prior to treatment was (1.087 +/- 0.146) x 10(-3)mm(2)/s, and the degree of the changes in tumor volume after NAC was (70.4% +/- 55.1)%. A negative correlation was observed (r = -0.430, P = 0.025 < 0.05). In the response group, there was a significant difference in ADC value between prior to NAC and 1st cycle of NAC, the final cycle of NAC, respectively (P < 0.001). While no significant differences were found in non-responders during NAC (P > 0.05). The tumor volume correlation coefficient between DWI and pathology measurements was very high (r = 0.749, P < 0.01). CONCLUSION: DWI appears to provide functional information regarding changes in ADC value of tumors due to NAC. DWI may be useful in monitoring the early pathological response of tumor after the initiation of treatment and in evaluating the residual tumor after NAC.

A randomized phase II study of CEOP with or without semustine as induction chemotherapy in patients with stage IE/IIE extranodal NK/T-cell lymphoma, nasal type in the upper aerodigestive tract.

PURPOSE: In this randomized phase II study, we evaluated the efficacy of semustine added to CEOP regimen as induction chemotherapy in patients with stage I(E)/II(E) extranodal NK/T-cell lymphoma, nasal type in the upper aerodigestive tract. PATIENTS AND METHODS: Seventy-five eligible patients were randomized to receive either CEOP or CEOP plus semustine followed by involved-field radiotherapy. RESULTS: The overall response rate of induction chemotherapy was 57.9% in CEOP arm compared with 62.2% in CEOP plus semustine arm (P=0.71). With a median follow-up of 30.1 months, 2-year overall survival was 73.3% and 62.2%, respectively (P=0.37). Toxicities in both arms were comparable and manageable. Through univariate and multivariate analysis, PS of 2, Stage II(E) and elevated LDH level were identified to be adverse prognostic factors. A new prognostic index categorized three groups of patients (low risk, no adverse factors; intermediate risk, one factor; and high risk, 2 or 3 factors) with highly significant difference of prognosis. Two-year overall survival was 87.5%, 60.6% and 30%, respectively (P=0.0002). CONCLUSIONS: The addition of semustine to CEOP regimen was not associated with improved efficacy. More effective treatment needs to be explored in patients with intermediate or high risk.