CAJ | 학술논문

目的：探讨MR ADC直方图预测局部晚期乳腺癌（LABC）患者新辅助化疗（NACT）疗效的价值。方法回顾性分析经病理证实为乳腺浸润性导管癌行NACT治疗，且NACT治疗后行乳腺癌手术的35例患者。患者NACT前行乳腺常规MRI、动态增强扫描和DWI检查，乳腺癌手术后参照病理结果，依据实体瘤疗效评价标准将患者分为治疗有效组（19例）和无效组（16例）。测量记录2组患者ADC直方图的定量参数，包括ADC值平均数、众数、中位数、最小值、最大值、偏度系数和峰度系数，并采用独立样本t检验进行比较。对于有统计学意义的ADC直方图参数，采用最大Youden指数来确定绘制ROC直方图参数区分有效组和无效组乳腺癌的最佳临界值，计算各参数预测NACT疗效的效能。结果有效组患者ADC值平均数、最小值分别为（0.955±0.135）×10?3、（0.535±0.115）×10?3mm2/s，偏度系数和峰度系数分别为0.85±0.61、2.93±0.17；无效组患者ADC值平均数、最小值分别为（1.103±0.233）×10?3、（0.650±0.104）×10?3mm2/s，偏度系数和峰度系数分别为－0.42±0.17、3.11±0.25，2组间上述参数差异有统计学意义（t值分别为2.345、3.096、8.051和2.524，P均<0.05）。2组间ADC值众数、最大值和中位数差异无统计学意义（P均>0.05）。2组间的峰度系数重叠过多，无法获得最佳临界值。以ADC值平均数为0.956×10?3mm2/s为临界值绘制ROC曲线，曲线下面积为0.678，对NACT疗效预测的敏感度为73.7%，特异度为62.5%；以最小值0.580×10?3mm2/s为临界值绘制ROC曲线，曲线下面积为0.770，对NACT疗效预测的敏感度为78.9%，特异度为68.8%；以偏度系数0.890为临界值绘制ROC曲线，曲线下面积为0.730，对NACT疗效预测的敏感度为63.2%，特异度为75.0%。结论 ADC直方图分析预测LABC患者NACT疗效具有一定价值，ADC最小值的敏感度最高，偏度系数的特异度最高。目的：探討MR ADC直方圖預測跼部晚期乳腺癌（LABC）患者新輔助化療（NACT）療效的價值。方法迴顧性分析經病理證實為乳腺浸潤性導管癌行NACT治療，且NACT治療後行乳腺癌手術的35例患者。患者NACT前行乳腺常規MRI、動態增彊掃描和DWI檢查，乳腺癌手術後參照病理結果，依據實體瘤療效評價標準將患者分為治療有效組（19例）和無效組（16例）。測量記錄2組患者ADC直方圖的定量參數，包括ADC值平均數、衆數、中位數、最小值、最大值、偏度繫數和峰度繫數，併採用獨立樣本t檢驗進行比較。對于有統計學意義的ADC直方圖參數，採用最大Youden指數來確定繪製ROC直方圖參數區分有效組和無效組乳腺癌的最佳臨界值，計算各參數預測NACT療效的效能。結果有效組患者ADC值平均數、最小值分彆為（0.955±0.135）×10?3、（0.535±0.115）×10?3mm2/s，偏度繫數和峰度繫數分彆為0.85±0.61、2.93±0.17；無效組患者ADC值平均數、最小值分彆為（1.103±0.233）×10?3、（0.650±0.104）×10?3mm2/s，偏度繫數和峰度繫數分彆為－0.42±0.17、3.11±0.25，2組間上述參數差異有統計學意義（t值分彆為2.345、3.096、8.051和2.524，P均<0.05）。2組間ADC值衆數、最大值和中位數差異無統計學意義（P均>0.05）。2組間的峰度繫數重疊過多，無法穫得最佳臨界值。以ADC值平均數為0.956×10?3mm2/s為臨界值繪製ROC麯線，麯線下麵積為0.678，對NACT療效預測的敏感度為73.7%，特異度為62.5%；以最小值0.580×10?3mm2/s為臨界值繪製ROC麯線，麯線下麵積為0.770，對NACT療效預測的敏感度為78.9%，特異度為68.8%；以偏度繫數0.890為臨界值繪製ROC麯線，麯線下麵積為0.730，對NACT療效預測的敏感度為63.2%，特異度為75.0%。結論 ADC直方圖分析預測LABC患者NACT療效具有一定價值，ADC最小值的敏感度最高，偏度繫數的特異度最高。
목적：탐토MR ADC직방도예측국부만기유선암（LABC）환자신보조화료（NACT）료효적개치。방법회고성분석경병리증실위유선침윤성도관암행NACT치료，차NACT치료후행유선암수술적35례환자。환자NACT전행유선상규MRI、동태증강소묘화DWI검사，유선암수술후삼조병리결과，의거실체류료효평개표준장환자분위치료유효조（19례）화무효조（16례）。측량기록2조환자ADC직방도적정량삼수，포괄ADC치평균수、음수、중위수、최소치、최대치、편도계수화봉도계수，병채용독립양본t검험진행비교。대우유통계학의의적ADC직방도삼수，채용최대Youden지수래학정회제ROC직방도삼수구분유효조화무효조유선암적최가림계치，계산각삼수예측NACT료효적효능。결과유효조환자ADC치평균수、최소치분별위（0.955±0.135）×10?3、（0.535±0.115）×10?3mm2/s，편도계수화봉도계수분별위0.85±0.61、2.93±0.17；무효조환자ADC치평균수、최소치분별위（1.103±0.233）×10?3、（0.650±0.104）×10?3mm2/s，편도계수화봉도계수분별위－0.42±0.17、3.11±0.25，2조간상술삼수차이유통계학의의（t치분별위2.345、3.096、8.051화2.524，P균<0.05）。2조간ADC치음수、최대치화중위수차이무통계학의의（P균>0.05）。2조간적봉도계수중첩과다，무법획득최가림계치。이ADC치평균수위0.956×10?3mm2/s위림계치회제ROC곡선，곡선하면적위0.678，대NACT료효예측적민감도위73.7%，특이도위62.5%；이최소치0.580×10?3mm2/s위림계치회제ROC곡선，곡선하면적위0.770，대NACT료효예측적민감도위78.9%，특이도위68.8%；이편도계수0.890위림계치회제ROC곡선，곡선하면적위0.730，대NACT료효예측적민감도위63.2%，특이도위75.0%。결론 ADC직방도분석예측LABC환자NACT료효구유일정개치，ADC최소치적민감도최고，편도계수적특이도최고。
Objective To investigate the value of ADC histogram analysis in the assessment of response to neoadjuvant chemotherapy (NACT) in patients with in locally advanced breast cancer (LABC). Methods Thirty?five female patients with invasive ductal carcinoma proved by pathology before NACT and treated with operation after NACT were retrospectively analyzed. All patients were received MR examination (including non?enhanced MRI, enhanced?MRI, and DWI) breast before NACT. After neoadjuvant chemotherapy, 19 of 35 patients were categorized as responders and 16 were categorized as non?responders according response evaluation criteria in solid tumors criteria. Per?patient weighted ADC histograms were generated. Mean ADC, mode ADC, maximum ADC, minimum ADC, median ADC, skewness, and kurtosis were analyzed by using t test between responders and non responders groups. ROC curves were constructed to determine the optimum threshold for each histogram parameter to differentiate non?responders and responders in breast cancers. The optimal threshold values, determined by maximal Youden index were selected when significant differences existed in two groups. Results Mean, minimum, skewness, and kurtosis of ADC between responders and non?responders group were(0.955 ± 0.135)× 10?3mm2/s,(0.535 ± 0.115)×10?3mm2/s,0.85±0.61, 2.93±0.17,and(1.103±0.233)×10?3 mm2/s,(0.650±0.104)×10?3mm2/s,-0.42± 0.17, 3.11 ± 0.25,respectively. Significant differences were found mean ADC, minimum ADC, skewness, and kurtosis (t=2.345, 3.096, 8.051 and 2.524,P<0.05), and there was no differences in mode, median, maximum between responders and non?responders(P>0.05).We set the optimal threshold criteria of mean ADC (0.956×10?3mm2/s), minimum ADC (0.580×10?3mm2/s), skewness (0.890), sensitivity, specificity of three parameters for predicting responders in LABC were 73.7%,62.5%, 78.9%,68.8%, and 63.2%,75.0%, respectively, and the areas under ROC curve of mean ADC, minimum ADC, skewness was 0.678, 0.770, and 0.890, respectively. Kurtosis of responders and non?responders did not get cutoff value for much more overlap. Conclusion ADC histogram analysis is valuable in predicting LABC in patients with NACT effect, the minimum and skewness of ADC is highest sensitivity, specificity, respectively.