Objective:To study the magnetic resonance imaging apparent diffusion coefficient (ADC) before and after neoadjuvant chemotherapy in patients with breast cancer and its correlation with tumor load.Methods: Patients wit...Objective:To study the magnetic resonance imaging apparent diffusion coefficient (ADC) before and after neoadjuvant chemotherapy in patients with breast cancer and its correlation with tumor load.Methods: Patients with stage II-III breast cancer who intended to receive radical operation for breast cancer in our hospital between May 2015 and February 2018 were selected and divided into the experimental group who accepted neoadjuvant chemotherapy and the control group who received surgery directly according to the adoption of preoperative neoadjuvant chemotherapy or not in the history data. Experimental group underwent magnetic resonance imaging before and after neoadjuvant chemotherapy to measure the ADC, and control group underwent magnetic resonance imaging before surgery to measure the ADC;the tumor tissues surgically removed from the two groups of patients were collected to measure the expression of oncogenes and invasion genes.Results:ADC value of experimental group after neoadjuvant chemotherapy was higher than that before neoadjuvant chemotherapy, ADC value of experimental group before neoadjuvant chemotherapy was not significantly different from that of control group whereas ADC value after neoadjuvant chemotherapy was significantly higher than that of control group;MCM3, CyclinD1, TC-1,β-catenin, YAP and MMP2 mRNA expression levels in surgically removed tumor tissues of experimental group were significantly lower than those of control group whereas CCN5, ARID1A and PDCD4 mRNA expression levels were significantly higher than those of control group;MCM3, CyclinD1, TC-1,β-catenin, YAP and MMP2 mRNA expression levels in tumor tissues with high ADC value were significantly lower than those in tumor tissues with low ADC value whereas CCN5, ARID1A and PDCD4 mRNA expression levels were significantly higher than those in tumor tissues with low ADC value.Conclusion:The increase of ADC after breast cancer neoadjuvant chemotherapy is related to the activity of cancer cell proliferation and invasion, and can be used to evaluate the changes of tumor load before and after chemotherapy.展开更多
Breast cancer is a major oncological challenge for females worldwide.The incorporation of neoadjuvant chemotherapy into comprehensive management strategies for breast cancer underscores the importance of the precise p...Breast cancer is a major oncological challenge for females worldwide.The incorporation of neoadjuvant chemotherapy into comprehensive management strategies for breast cancer underscores the importance of the precise prognostication of therapeutic efficacy.In clinical diagnostics,medical imaging has emerged as a critical tool for delineating the structural transformations within breast cancer tumors resulting from pharmacological interventions.The evolution of artificial intelligence(AI)technologies has precipitated the delineation and quantification of imaging-based phenotypic features,thereby translating these structural modifications into quantifiable data alterations.This analytical approach has led to the development of innovative biomarkers for enhancing the predictability of neoadjuvant chemotherapy outcomes.This study aimed to elucidate the instrumental role of AI technology in the prognosis of neoadjuvant chemotherapy efficacy in breast cancer through the analytical exploration of ultrasound,magnetic resonance imaging,and histopathological imagery,while envisaging prospective trajectories within this research domain.展开更多
Treatment-induced apoptosis of cancer cells is one goal of cancer therapy.Interestingly,more heat is generated by mitochondria during apoptosis,especially the uncoupled apoptotic state,^(1,2) compared to the resting s...Treatment-induced apoptosis of cancer cells is one goal of cancer therapy.Interestingly,more heat is generated by mitochondria during apoptosis,especially the uncoupled apoptotic state,^(1,2) compared to the resting state.In this case study,we explore these thermal effects by longitudinally measuring temperature variations in a breast lesion of a pathological complete responder during neoadjuvant chemotherapy(NAC).Diffuse Optical Spectroscopic Imaging(DOSI)was employed to derive absolute deep tissue temperature using subtle spectral features of the water peak at 975 nm.^(3)A significant temperature increase was observed in time windows during the anthracycline and cyclophosphamide(AC)regimen but not in the paclitaxel and bevacizumab regimen.Hemoglobin concentration changes generally did not follow temperature,suggesting the measured temperature increases were likely due to mitochondrial uncoupling rather than a direct vascular effect.A simultaneous increase of tissue oxygen saturation with temperature was observed,suggesting that oxidative stress also contributes to apoptosis.Although preliminary,this study indicates longitudinal DOSI tissue temperature monitoring provides information that can improve our understanding of the mechanisms of tissue response during NAC.展开更多
Objective: The aim of our study was to assess the value of dynamic contrast-enhanced magnetic resonance imaging (DMRI) in predicting early response to neoadjuvant chemotherapy (NAC) in patients with locally advan...Objective: The aim of our study was to assess the value of dynamic contrast-enhanced magnetic resonance imaging (DMRI) in predicting early response to neoadjuvant chemotherapy (NAC) in patients with locally advanced breast cancer (LABC) and to assess the accuracy of DMRI in evaluating residual disease after NAC. Methods: DMRI were per- formed in 43 women with LABC (44 lesions, all were invasive ductal carcinoma) before, after the first and final cycle of NAC. Tumour volume, early enhanced ratio (El), maximum enhanced ratio (Emax), and maximum enhanced time (Tmax), dynamic signal intensity-time curve were obtained during treatment. Residual tumour volumes obtained using DMRI were compared with pathological findings to assess the accuracy of DMRI. Results: After 1st cycle of NAC, the mean volume of responders decreased insignificantly, P 〉 0.05, but after NAC, mean volume of residual tumor decreased significantly (P 〈 0.01). Morphol- ogy change: 29 cases showed a concentric shrinkage pattern while 7 cases showed a dendritic shrinkage pattern. Significant differences were found in El, Emax and Tmax between responders and non-responders (P 〈 0.05). After 1st cycle of NAC, El, Emax and Tmax of responders changed significantly (P 〈 0.001); while there is no significant change in non-responders (P 〉 0.05). After NAC, dynamic signal intensity-time types were changed in responders, and tended to be significantly flat- tening, while no significant change was found in non-responders. The residual tumour volume correlation coefficient between DMRI and pathology measurements was very high (r = 0.866, P = 0.000). Conclusion: DMRI is useful to evaluate the early response to NAC in LABC. The presence and volume of residual disease in LABC patients treated with NAC could be ac- curately evaluated by DMRI.展开更多
Background: Diffusion-weighted imaging (DWI) with the intravoxel incoherent motion (IVIM) model has shown promising results for providing both diffusion and perfusion intbrmation in cervical cancer; however, its ...Background: Diffusion-weighted imaging (DWI) with the intravoxel incoherent motion (IVIM) model has shown promising results for providing both diffusion and perfusion intbrmation in cervical cancer; however, its use to predict and monitor the efficacy ofneoadjuvant chemotherapy (NACT) in cervical cancer is relatively rare. The study aimed to evaluate the use of DWl with 1VIM and monoexponential models to predict and monitor the efficacy of NACT in cervical cancer. Methods: Forty-two patients with primary cervical cancer underwent magnetic resonance exams at 3 time points (pre-NACT, 3 weeks after the first NACT cycle, and 3 weeks after the second NACT cycle). The response to treatment was determined according to the response evaluation criteria in solid tumors 3 weeks after the second NACT treatment, and the subjects were classified as two groups: responders and nonresponders groups. The apparent diffusion coefficient (ADC), true diffusion coefficient (D), perfusion-related pseudo-diffusion coefficient (D*), and perfusion fraction (f) values were determined. The differences in IVlM-derived variables and ADC between the different groups at the different time points were calculated using an independent samples t-test. Results: The D and ADC values were all significantly higher for the responders than tbr the nonresponders at all 3 time points, but no significant differences were observed in the D* and fvalues. An analysis of the receiver operating characteristic (ROC) curves indicated that a D value threshold 〈0.93 × 10 3 mm2/s and an ADC threshold 〈1.11× 10 3 mm2/s could differentiate responders from nonresponders at pre-NACT time point, yielding area under the curve (AUC) of which were 0.771 and 0.806, respectively. The ROC indicated that the AUCs of D and ADC at the 3 weeks after the first NACT cycle and 3 weeks after the second NACT cycle were 0.823, 0.763, and 0.787, 0.794, respectively. The AUC values of D and ADC at these 3 time points were not significantly different (P = 0.641, 0.512, and 0.547, respectively). Conclusions: D and ADC values may be useful for predicting and monitoring the efficacy of NACT in cervical cancer. An IVIM model may be equal to monoexponential model in predicting and monitoring the efficacy of NACT in cervical cancer.展开更多
Patients with hormone receptor(HR)-positive tumors breast cancer usually experience a relatively low pathological complete response(p CR)to neoadjuvant chemotherapy(NAC).Here,we derived a 10-micro RNA risk score(10-mi...Patients with hormone receptor(HR)-positive tumors breast cancer usually experience a relatively low pathological complete response(p CR)to neoadjuvant chemotherapy(NAC).Here,we derived a 10-micro RNA risk score(10-mi RNA RS)-based model with better performance in the prediction of p CR and validated its relation with the disease-free survival(DFS)in 755 HRpositive breast cancer patients(273,265,and 217 in the training,internal,and external validation sets,respectively).This model,presented as a nomogram,included four parameters:the 10-mi RNA RS found in our previous study,progesterone receptor(PR),human epidermal growth factor receptor 2(HER2)status,and volume transfer constant(K).Favorable calibration and discrimination of 10-mi RNA RS-based model with areas under the curve(AUC)of 0.865,0.811,and 0.804 were shown in the training,internal,and external validation sets,respectively.Patients who have higher nomogram score(>92.2)with NAC treatment would have longer DFS(hazard ratio=0.57;95%CI:0.39–0.83;P=0.004).In summary,our data showed the 10-mi RNA RS-based model could precisely identify more patients who can attain p CR to NAC,which may help clinicians formulate the personalized initial treatment strategy and consequently achieves better clinical prognosis for patients with HRpositive breast cancer.展开更多
文摘Objective:To study the magnetic resonance imaging apparent diffusion coefficient (ADC) before and after neoadjuvant chemotherapy in patients with breast cancer and its correlation with tumor load.Methods: Patients with stage II-III breast cancer who intended to receive radical operation for breast cancer in our hospital between May 2015 and February 2018 were selected and divided into the experimental group who accepted neoadjuvant chemotherapy and the control group who received surgery directly according to the adoption of preoperative neoadjuvant chemotherapy or not in the history data. Experimental group underwent magnetic resonance imaging before and after neoadjuvant chemotherapy to measure the ADC, and control group underwent magnetic resonance imaging before surgery to measure the ADC;the tumor tissues surgically removed from the two groups of patients were collected to measure the expression of oncogenes and invasion genes.Results:ADC value of experimental group after neoadjuvant chemotherapy was higher than that before neoadjuvant chemotherapy, ADC value of experimental group before neoadjuvant chemotherapy was not significantly different from that of control group whereas ADC value after neoadjuvant chemotherapy was significantly higher than that of control group;MCM3, CyclinD1, TC-1,β-catenin, YAP and MMP2 mRNA expression levels in surgically removed tumor tissues of experimental group were significantly lower than those of control group whereas CCN5, ARID1A and PDCD4 mRNA expression levels were significantly higher than those of control group;MCM3, CyclinD1, TC-1,β-catenin, YAP and MMP2 mRNA expression levels in tumor tissues with high ADC value were significantly lower than those in tumor tissues with low ADC value whereas CCN5, ARID1A and PDCD4 mRNA expression levels were significantly higher than those in tumor tissues with low ADC value.Conclusion:The increase of ADC after breast cancer neoadjuvant chemotherapy is related to the activity of cancer cell proliferation and invasion, and can be used to evaluate the changes of tumor load before and after chemotherapy.
基金supported by the National Natural Science Foundation of China grant numbers 62333022,82371936)the Natural Science Basic Research Program of Shaanxi(grant number 2023-JC-YB-682)Xi'an Science and Technology Program(grant number 22GXFW0036).
文摘Breast cancer is a major oncological challenge for females worldwide.The incorporation of neoadjuvant chemotherapy into comprehensive management strategies for breast cancer underscores the importance of the precise prognostication of therapeutic efficacy.In clinical diagnostics,medical imaging has emerged as a critical tool for delineating the structural transformations within breast cancer tumors resulting from pharmacological interventions.The evolution of artificial intelligence(AI)technologies has precipitated the delineation and quantification of imaging-based phenotypic features,thereby translating these structural modifications into quantifiable data alterations.This analytical approach has led to the development of innovative biomarkers for enhancing the predictability of neoadjuvant chemotherapy outcomes.This study aimed to elucidate the instrumental role of AI technology in the prognosis of neoadjuvant chemotherapy efficacy in breast cancer through the analytical exploration of ultrasound,magnetic resonance imaging,and histopathological imagery,while envisaging prospective trajectories within this research domain.
基金This work was supported by NIH R01-CA75124,R01-EB002109Susan G.Komen for the Cure Postdoctoral Fellowship provided to University of Pennsylvania,and P41-RR01192,U54-CA105480,U54CA136400,P30-CA62203 provided to University of California,Irvine.
文摘Treatment-induced apoptosis of cancer cells is one goal of cancer therapy.Interestingly,more heat is generated by mitochondria during apoptosis,especially the uncoupled apoptotic state,^(1,2) compared to the resting state.In this case study,we explore these thermal effects by longitudinally measuring temperature variations in a breast lesion of a pathological complete responder during neoadjuvant chemotherapy(NAC).Diffuse Optical Spectroscopic Imaging(DOSI)was employed to derive absolute deep tissue temperature using subtle spectral features of the water peak at 975 nm.^(3)A significant temperature increase was observed in time windows during the anthracycline and cyclophosphamide(AC)regimen but not in the paclitaxel and bevacizumab regimen.Hemoglobin concentration changes generally did not follow temperature,suggesting the measured temperature increases were likely due to mitochondrial uncoupling rather than a direct vascular effect.A simultaneous increase of tissue oxygen saturation with temperature was observed,suggesting that oxidative stress also contributes to apoptosis.Although preliminary,this study indicates longitudinal DOSI tissue temperature monitoring provides information that can improve our understanding of the mechanisms of tissue response during NAC.
文摘Objective: The aim of our study was to assess the value of dynamic contrast-enhanced magnetic resonance imaging (DMRI) in predicting early response to neoadjuvant chemotherapy (NAC) in patients with locally advanced breast cancer (LABC) and to assess the accuracy of DMRI in evaluating residual disease after NAC. Methods: DMRI were per- formed in 43 women with LABC (44 lesions, all were invasive ductal carcinoma) before, after the first and final cycle of NAC. Tumour volume, early enhanced ratio (El), maximum enhanced ratio (Emax), and maximum enhanced time (Tmax), dynamic signal intensity-time curve were obtained during treatment. Residual tumour volumes obtained using DMRI were compared with pathological findings to assess the accuracy of DMRI. Results: After 1st cycle of NAC, the mean volume of responders decreased insignificantly, P 〉 0.05, but after NAC, mean volume of residual tumor decreased significantly (P 〈 0.01). Morphol- ogy change: 29 cases showed a concentric shrinkage pattern while 7 cases showed a dendritic shrinkage pattern. Significant differences were found in El, Emax and Tmax between responders and non-responders (P 〈 0.05). After 1st cycle of NAC, El, Emax and Tmax of responders changed significantly (P 〈 0.001); while there is no significant change in non-responders (P 〉 0.05). After NAC, dynamic signal intensity-time types were changed in responders, and tended to be significantly flat- tening, while no significant change was found in non-responders. The residual tumour volume correlation coefficient between DMRI and pathology measurements was very high (r = 0.866, P = 0.000). Conclusion: DMRI is useful to evaluate the early response to NAC in LABC. The presence and volume of residual disease in LABC patients treated with NAC could be ac- curately evaluated by DMRI.
基金This work was supported by the grants form National Natural Science Foundation of China (No. 81371524 and No. 81271529) and the Hubei Provincial Natural Science Foundation of China (No. 2014CFB298).
文摘Background: Diffusion-weighted imaging (DWI) with the intravoxel incoherent motion (IVIM) model has shown promising results for providing both diffusion and perfusion intbrmation in cervical cancer; however, its use to predict and monitor the efficacy ofneoadjuvant chemotherapy (NACT) in cervical cancer is relatively rare. The study aimed to evaluate the use of DWl with 1VIM and monoexponential models to predict and monitor the efficacy of NACT in cervical cancer. Methods: Forty-two patients with primary cervical cancer underwent magnetic resonance exams at 3 time points (pre-NACT, 3 weeks after the first NACT cycle, and 3 weeks after the second NACT cycle). The response to treatment was determined according to the response evaluation criteria in solid tumors 3 weeks after the second NACT treatment, and the subjects were classified as two groups: responders and nonresponders groups. The apparent diffusion coefficient (ADC), true diffusion coefficient (D), perfusion-related pseudo-diffusion coefficient (D*), and perfusion fraction (f) values were determined. The differences in IVlM-derived variables and ADC between the different groups at the different time points were calculated using an independent samples t-test. Results: The D and ADC values were all significantly higher for the responders than tbr the nonresponders at all 3 time points, but no significant differences were observed in the D* and fvalues. An analysis of the receiver operating characteristic (ROC) curves indicated that a D value threshold 〈0.93 × 10 3 mm2/s and an ADC threshold 〈1.11× 10 3 mm2/s could differentiate responders from nonresponders at pre-NACT time point, yielding area under the curve (AUC) of which were 0.771 and 0.806, respectively. The ROC indicated that the AUCs of D and ADC at the 3 weeks after the first NACT cycle and 3 weeks after the second NACT cycle were 0.823, 0.763, and 0.787, 0.794, respectively. The AUC values of D and ADC at these 3 time points were not significantly different (P = 0.641, 0.512, and 0.547, respectively). Conclusions: D and ADC values may be useful for predicting and monitoring the efficacy of NACT in cervical cancer. An IVIM model may be equal to monoexponential model in predicting and monitoring the efficacy of NACT in cervical cancer.
基金the National Natural Science Foundation of China(92159303,81621004,81720108029,81930081,91940305,81672594,81772836,81872139,82072907,and 82003311)Guangdong Science and Technology Department(2020B1212060018 and 2020B1212030004)+8 种基金Clinical Innovation Research Program of Bioland Laboratory(2018GZR0201004)Bureau of Science and Technology of Guangzhou(20212200003)Program for Guangdong Introducing Innovative and Enterpreneurial Teams(2019BT02Y198)the Project of The Beijing Xisike Clinical Oncology Research Foundation(YRoche2019/2-0078)the Technology Development Program of Guangdong province(2021A0505030082)the Project of The Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation(2020B1212060018)Sun Yat-Sen Memorial Hospital Cultivation Project for Clinical Research(SYS-C-201805 and SYS-Q-202004)Guangzhou Science and Technology Program(202102010272)Medical Science and Technology Research Fund of Guangdong Province(A2020391)。
文摘Patients with hormone receptor(HR)-positive tumors breast cancer usually experience a relatively low pathological complete response(p CR)to neoadjuvant chemotherapy(NAC).Here,we derived a 10-micro RNA risk score(10-mi RNA RS)-based model with better performance in the prediction of p CR and validated its relation with the disease-free survival(DFS)in 755 HRpositive breast cancer patients(273,265,and 217 in the training,internal,and external validation sets,respectively).This model,presented as a nomogram,included four parameters:the 10-mi RNA RS found in our previous study,progesterone receptor(PR),human epidermal growth factor receptor 2(HER2)status,and volume transfer constant(K).Favorable calibration and discrimination of 10-mi RNA RS-based model with areas under the curve(AUC)of 0.865,0.811,and 0.804 were shown in the training,internal,and external validation sets,respectively.Patients who have higher nomogram score(>92.2)with NAC treatment would have longer DFS(hazard ratio=0.57;95%CI:0.39–0.83;P=0.004).In summary,our data showed the 10-mi RNA RS-based model could precisely identify more patients who can attain p CR to NAC,which may help clinicians formulate the personalized initial treatment strategy and consequently achieves better clinical prognosis for patients with HRpositive breast cancer.