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<front>
<journal-meta>
<!-- 出版商赋予期刊ID-->
<journal-id journal-id-type="publisher-id">YIKE</journal-id>
<journal-title-group>
<!-- 期刊中文全称-->
<journal-title>安徽医科大学学报</journal-title>
<!-- 期刊英文全称-->
<journal-title xml:lang="en">Acta Universitatis Medicinalis Anhui</journal-title>
<!-- 期刊英文缩写-->
<abbrev-journal-title abbrev-type="publisher" xml:lang="en">Acta Universitatis Medicinalis Anhui</abbrev-journal-title>
<!-- 期刊中文缩写-->
<abbrev-journal-title abbrev-type="publisher">安徽医科大学学报</abbrev-journal-title>
</journal-title-group>
<!-- 期刊ISSN号-->
<issn pub-type="ppub">1000-1492</issn>
<!-- 期刊CN号-->
<issn pub-type="cn">34-1065/R</issn>
<publisher>
<!--出版商英文名称【预置实体】 待确认 -->
<publisher-name xml:lang="en">Anhui Lianzhong Printing Limited Company</publisher-name>
<!--出版商英文地址【预置实体】 -->
<publisher-loc xml:lang="en">Editorial Board of Acta Universitatis Medi-cinalis Anhui Meishan Road , Hefei 230032</publisher-loc>
<!-- 出版商中文名称【预置实体】-->
<publisher-name>《安徽医科大学学报》编辑部</publisher-name>
<!--出版商中文地址【预置实体】 -->
<publisher-loc>安徽省合肥市安徽医科大学校内老图书馆三楼</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="publisher-id">1000–1492（2026）05–0937–06</article-id>
<article-id pub-id-type="doi">10.19405/j.cnki.issn1000–1492.2026.05 019</article-id>
<article-id pub-id-type="manuscript">V220-冯路路-深度学习重建技术</article-id>
<article-categories>
<subj-group subj-group-type="clc">
<subject>R 445.2</subject>
</subj-group>
<subj-group subj-group-type="dc">
<subject>A</subject>
</subj-group>
<subj-group subj-group-type="heading">
<subject>临床医学研究</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>深度学习重建技术用于提升肝脏MRI中HASTE与DWI序列成像效能及质量的应用价值</article-title>
<trans-title-group xml:lang="en">
<trans-title>Application value of deep learning reconstruction technology in enhancing the imaging efficiency and quality of HASTE and DWI sequences for liver MRI</trans-title>
</trans-title-group>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name-alternatives>
<name name-style="eastern">
<surname>冯</surname>
<given-names>路路</given-names>
</name>
<name name-style="eastern" xml:lang="en">
<surname>Feng</surname>
<given-names>Lulu</given-names>
</name>
</name-alternatives>
<xref ref-type="aff" rid="aff1"/>
<xref ref-type="author-notes" rid="fna1"/>
</contrib>
<contrib contrib-type="author">
<name-alternatives>
<name name-style="eastern">
<surname>潘</surname>
<given-names>志立</given-names>
</name>
<name name-style="eastern" xml:lang="en">
<surname>Pan</surname>
<given-names>Zhili</given-names>
</name>
</name-alternatives>
<xref ref-type="aff" rid="aff1"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name-alternatives>
<name name-style="eastern">
<surname>赵</surname>
<given-names>英明</given-names>
</name>
<name name-style="eastern" xml:lang="en">
<surname>Zhao</surname>
<given-names>Yingming</given-names>
</name>
</name-alternatives>
<xref ref-type="aff" rid="aff1"/>
<xref ref-type="corresp" rid="cor1"/>
<xref ref-type="author-notes" rid="fna2"/>
</contrib>
<aff-alternatives id="aff1">
<aff>
<institution>中国科学技术大学附属第一医院（安徽省立医院）影像科</institution>，
<city>合肥</city>  
<postal-code>230001</postal-code>
</aff>
<aff xml:lang="en">
<institution>Department of Radiology，The First Affiliated Hospital of USTC，Division of Life Sciences and Medicine， University of Science and Technology of China， Hefei</institution>　
<postal-code>230001</postal-code>
</aff>
</aff-alternatives>
</contrib-group>
<author-notes>
<corresp xml:lang="en" id="cor1">
<named-content content-type="corresp-name">Zhao Yingming</named-content>，E-mail：
<email>wisezhao158@ustc.edu.cn</email>
</corresp>
<fn fn-type="other" specific-use="about-author" id="fna1">
<p>
<named-content content-type="corresp-name">冯路路</named-content>，女，影像技师
</p>
</fn>
<fn fn-type="other" specific-use="about-author" id="fna2">
<p>
<named-content content-type="corresp-name">赵英明</named-content>，男，副主任技师，硕士生导师，通信作者，E-mail：
<email>wisezhao158@ustc.edu.cn</email>
</p>
</fn>
</author-notes>
<pub-date pub-type="epub" iso-8601-date="2026-04-13T10：37：28">
<day>13</day>
<month>04</month>
<year>2026</year>
</pub-date>
  
    <history>
<date date-type="received">       
<day>17</day>
<month>03</month>
<year>2026</year>
</date>
  </history>
<pub-date pub-type="ppub">
<day>23</day>
<month>05</month>
<year>2026</year>
</pub-date>
<volume>61</volume>
<issue>5</issue>
<issue-id>16</issue-id>
<fpage>937</fpage>
<lpage>942</lpage>
<page-range>937-942</page-range>
<abstract abstract-type="key-points">
<sec>
<title>目的</title>
<p>比较深度学习重建（DLR）的单次激发半傅里叶快速自旋回波（HASTE
<sub>DLR</sub>）和扩散加权成像（DWI
<sub>DLR</sub>）序列与传统刀锋伪影校正技术（BLADE）及DWI
<sub>常规</sub>序列在肝脏磁共振成像（MRI）中的价值。
</p>
</sec>
<sec>
<title>方法</title>
<p>70例患者接受MRI检查，2名观察者独立评估各序列图像质量（肝缘、血管、病灶清晰度等），并测量病灶信噪比（SNR）和病灶对比噪声比（CNR）以及表观扩散系数（ADC）值，采用组内相关系数（ICC）评估观察者一致性。</p>
</sec>
<sec>
<title>结果</title>
<p>观察者一致性较高（ICC：0.84~0.97）。HASTE
<sub>DLR</sub>和DWI
<sub>DLR</sub>序列扫描时间分别减少92.63%和50%。HASTE
<sub>DLR</sub>组病灶清晰度评分显著优于BLADE组（
<italic>P</italic>&lt;0.001），两组DLR序列伪影均减少（
<italic>P</italic>&lt;0.05）。HASTE
<sub>DLR</sub>组SNR、CNR及DWI
<sub>DLR</sub>组SNR、ADC值均更高（
<italic>P</italic>&lt;0.05）。
</p>
</sec>
<sec>
<title>结论</title>
<p>DLR技术可提升肝脏MRI扫描效率，改善图像质量并减少伪影，具有良好的应用前景。</p>
</sec>
</abstract>
<trans-abstract abstract-type="key-points" xml:lang="en">
<sec>
<title>Objective</title>
<p>To explore the value of deep learning reconstruction （DLR） in liver magnetic resonance imaging （MRI） by comparing the single-shot half-fourier rapid spin-echo sequence with DLR （HASTE
<sub>DLR</sub>） and diffusion-weighted imaging sequence with DLR （DWI
<sub>DLR</sub>） against the conventional BLADE and conventional DWI sequences.
</p>
</sec>
<sec>
<title>Methods</title>
<p>70 patients underwent MRI examinations. Two observers independently evaluated the image quality of each sequence （including liver edge， blood vessels， lesion clarity， etc.）. Additionally， quantitative evaluation was conducted by measuring the signal to noise ratio （SNR） of liver parenchyma and lesions， contrast to noise ratio （CNR） of lesions， as well as apparent diffusion coefficient （ADC） values from conventional DWI and DWI
<sub>DLR</sub>. Intraclass correlation coefficient （ICC） was used to evaluate the consistency between the two observers.
</p>
</sec>
<sec>
<title>Results</title>
<p>The inter-observer consistency was high （ICC： 0.84-0.97）. The scanning time was reduced by 92.63% for HASTE
<sub>DLR</sub> and 50% for DWI
<sub>DLR</sub> sequences， respectively. The lesion clarity score of the HASTE
<sub>DLR</sub> group was significantly better than that of the BLADE group （
<italic>P</italic>&lt;0.001）， with artifacts reduced in both DLR sequences （
<italic>P</italic>&lt; 0.05）. The HASTE
<sub>DLR</sub> group demonstrated higher SNR and CNR， while the DWI
<sub>DLR</sub> group showed higher SNR and ADC values （all 
<italic>P</italic>&lt;0.05）.
</p>
</sec>
<sec>
<title>Conclusion</title>
<p>The DLR technology can enhance the efficiency of liver MRI scans， improve image quality， and reduce artifacts， demonstrating promising application prospects.</p>
</sec>
</trans-abstract>
<kwd-group kwd-group-type="author">
<kwd>深度学习重建</kwd>
<kwd>信噪比</kwd>
<kwd>对比噪声比</kwd>
<kwd>图像质量</kwd>
<kwd>磁共振成像</kwd>
</kwd-group>
<kwd-group xml:lang="en" kwd-group-type="author">
<kwd>deep learning reconstruction</kwd>
<kwd>signal to noise ratio</kwd>
<kwd>contrast to noise ratio</kwd>
<kwd>image quality</kwd>
<kwd>magnetic resonance imaging</kwd>
</kwd-group>
<funding-group>
<award-group>
<funding-source>安徽省高等学校省级质量工程项目</funding-source>
<award-id>2022jyxm1840</award-id>
</award-group>
<funding-statement>安徽省高等学校省级质量工程项目（编号：2022jyxm1840）</funding-statement>
</funding-group>
<funding-group xml:lang="en">
<award-group>
<funding-source>Provincial Quality Engineering Project of Colleges and Universities in Anhui Province</funding-source>
<award-id>2022jyxm1840</award-id>
</award-group>
<funding-statement>Provincial Quality Engineering Project of Colleges and Universities in Anhui Province （No. 2022jyxm1840）</funding-statement>
</funding-group>
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<fig-count count="1"/>
<table-count count="4"/>
<equation-count count="0"/>
<ref-count count="16"/>
<page-count count="6"/>
<word-count count="15437"/>
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<meta-value>1.0.0.25091</meta-value>
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<meta-value>2026-06-30T11:07:41</meta-value>
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</front>
<body>

<p>T2加权成像和扩散加权成像（diffusion-weighted imaging， DWI）是肝脏局灶性病变检测的关键磁共振成像（magnetic resonance imaging ，MRI）技术。单次激发半傅里叶快速自旋回波（half fourier acquisition single shot turbo spin echo， HASTE）序列通过单次激发和短回波间隔较传统快速自旋回波（fast spin echo， FSE）序列显著缩短扫描时间并减少运动伪影，但其长回波链和部分傅里叶采样可能导致T2对比度失真、信噪比（signal to noise ratio， SNR）及空间分辨率下降。此外，基于平面回波成像（echo planar imaging， EPI）的DWI序列易受磁敏感伪影影响。而常用的加速采集技术如并行成像（parallel imaging， PI）会伴随SNR下降
<sup>［
<xref ref-type="bibr" rid="R1">1</xref>］
</sup>。近年来，深度学习重建（deep learning reconstruction， DLR）技术基于卷积神经网络或变分网络整合k空间数据一致性约束与图像正则化，在缩短扫描时间的同时能够从欠采样数据中重建高SNR图像
<sup>［
<xref ref-type="bibr" rid="R2">2</xref>］
</sup>。这为解决平衡成像效率与质量这一问题提供了新思路。目前，针对肝脏这类运动敏感器官的DLR应用仍处于探索阶段。该研究通过定性与定量分析，对比基于DLR的HASTE和DWI序列与传统T2加权刀锋伪影校正技术 （BLADE）及DWI在肝脏MRI中的表现。
</p>
<sec id="s1">
<label>1</label>
<title>材料与方法</title>
<sec id="s1a">
<label>1.1</label>
<title>病例资料</title>
<p specific-use="noneIndent">收集2024年11月—2025年4月于本院接受肝脏MRI平扫+增强检查的成年患者。排除标准：① 患者存在MRI对比剂禁忌证；② 临床数据或MRI数据采集不完整。最终纳入70例患者，年龄41~69（54.66±13.95）岁，男性52例，女性18例，其中其中肝细胞癌40例、肝内胆管细胞癌5例、肝硬化结节7例、肝血管瘤3例、肝脏转移瘤7例、肝脏局灶性结节增生8例。研究已通过医院伦理委员会批准（伦理编号：2025-RE-267），所有参与者均提供了书面知情同意。</p>
</sec>
<sec id="s1b">
<label>1.2</label>
<title>MRI检查方法</title>
<p specific-use="noneIndent">所有患者均在同一台MRI扫描仪（MAGNETOM Vida，3.0T，德国西门子医疗系统有限公司），患者取仰卧位、头先进，采用18通道体部线圈接受上腹部MRI扫描。检查前患者需禁食、禁水4 h。扫描序列包括轴位T1WI、T2WI、HASTE
<sub>DLR</sub>、BLADE、DWI
<sub>常规、DLR</sub>和三期动态增强。HASTE
<sub>DLR</sub>、BLADE及DWI
<sub>常规、DLR</sub>序列采集参数详见
<xref ref-type="table" rid="T1">表1</xref>。HASTE
<sub>DLR</sub>和DWI
<sub>DLR</sub>序列扫描时间较BLADE和DWI
<sub>常规</sub>序列减少92.63%和50.00%。DWI序列均在自由呼吸状态下采集完成，扩散敏感系数b值（diffusion sensitivity factor，b-value）分别为50、800 s/mm²。DWI
<sub>常规</sub>b值采集平均次数分别为2、6；DWI
<sub>DLR</sub>b值采集平均次数分别为1、3。DWI
<sub>常规、DLR</sub>均采用相同的后处理方法计算获得表观扩散系数图（apparent diffusion coefficient，ADC）。
</p>
<table-wrap id="T1">
<object-id pub-id-type="doi">10.19405/j.cnki.issn1000–1492.2026.05.019.T001</object-id>
<label>表1</label>
<caption>
<p>HASTE
<sub>DLR</sub>、BLADE和DWI
<sub>DLR、常规</sub>扫描参数
</p>
</caption>
<abstract abstract-type="caption" xml:lang="en">
<label>Tab.1</label>
<title>Scanning parameters of HASTE
<sub>DLR</sub>， BLADE， and DWI
<sub>DLR， convention</sub>
</title>
</abstract>
<alternatives>
<table id="Table1">
<thead>
<tr>
<th align="left" style="border-top:solid;border-bottom:solid;">Scanning parameters</th>
<th align="center" style="border-top:solid;border-bottom:solid;">HASTE
<sub>DLR</sub>
</th>
<th align="center" style="border-top:solid;border-bottom:solid;">BLADE</th>
<th align="center" style="border-top:solid;border-bottom:solid;">DWI
<sub>DLR</sub>
</th>
<th align="center" style="border-top:solid;border-bottom:solid;">DWI
<sub>conventionl</sub>
</th>
</tr>
</thead>
<tbody>
<tr align="center">
<td align="left">Respiration mode</td>
<td align="center">Single breath-hold</td>
<td align="center">Free breathing</td>
<td align="center">Free breathing</td>
<td align="center">Free breathing</td>
</tr>
<tr align="center">
<td align="left">Scanning time （min）</td>
<td align="center">00∶21</td>
<td align="center">04∶45</td>
<td align="center">01∶18</td>
<td align="center">02∶36</td>
</tr>
<tr align="center">
<td align="left">TR （ms）</td>
<td align="center">600</td>
<td align="center">1 800</td>
<td align="center">7 100</td>
<td align="center">7 700</td>
</tr>
<tr align="center">
<td align="left">TE （ms）</td>
<td align="center">74</td>
<td align="center">100</td>
<td align="center">45</td>
<td align="center">47</td>
</tr>
<tr align="center">
<td align="left">Matrix</td>
<td align="center">384×250</td>
<td align="center">384×250</td>
<td align="center">120×120</td>
<td align="center">152×152</td>
</tr>
<tr align="center">
<td align="left">Field of view （mm
<sup>2</sup>）
</td>
<td align="center">360×225</td>
<td align="center">380×380</td>
<td align="center">360×288</td>
<td align="center">380×305</td>
</tr>
<tr align="center">
<td align="left">Slice thickness （mm）</td>
<td align="center">3</td>
<td align="center">3</td>
<td align="center">3</td>
<td align="center">3</td>
</tr>
<tr align="center">
<td align="left">Fat suppression technique</td>
<td align="center">SPAIR</td>
<td align="center">SPAIR</td>
<td align="center">SPAIR</td>
<td align="center">SPAIR</td>
</tr>
<tr align="center">
<td align="left" style="border-bottom:solid;">Parallel acceleration factor</td>
<td align="center" style="border-bottom:solid;">2</td>
<td align="center" style="border-bottom:solid;">2</td>
<td align="center" style="border-bottom:solid;">3</td>
<td align="center" style="border-bottom:solid;">3</td>
</tr>
</tbody>
</table>
<graphic specific-use="big" xlink:href="alternativeImage/FD496FFE-0F18-4788-97F2-FD05D1E8DF1C-T001.jpg"><?fx-imagestate width="169.80000305" height="45.94001007"?>
</graphic>
<graphic specific-use="small" xlink:href="alternativeImage/FD496FFE-0F18-4788-97F2-FD05D1E8DF1C-T001c.jpg"><?fx-imagestate width="169.80000305" height="45.94001007"?>
</graphic>
</alternatives>
</table-wrap>
</sec>
<sec id="s1c">
<label>1.3</label>
<title>深度学习重建</title>
<p specific-use="noneIndent">HASTE
<sub>DLR</sub>和DWI
<sub>DLR</sub>序列图像重建分别采用变分网络和展开式迭代网络架构
<sup>［
<xref ref-type="bibr" rid="R3">3</xref>］
</sup>。在图像重建过程中，k空间数据、偏置场校正结果和线圈灵敏度图会被输入网络。HASTE
<sub>DLR</sub>变分网络在前22次迭代中不施加正则化，专注于并行成像重建；在后续12次迭代中引入基于残差密集U-Net网络的正则化。DWI
<sub>DLR</sub>展开式迭代网络在前6次迭代中不施加正则化；在随后的11次迭代中引入基于卷积神经网络的正则化模块。
</p>
<p>HASTE
<sub>DLR</sub>和DWI
<sub>DLR</sub>重建网络模型分别基于约1万幅传统HASTE序列图像和约50万次DWI重复扫描数据进行训练。训练数据使用多台1.5T/3TMRI（西门子MAGNETOM系列）采集，训练在PyTorch框架下使用配备NVIDIA Tesla V100 GPU（32GB显存）的集群完成，训练获得的模型权重参数转换为专有的推理框架，并集成至现有MRI扫描仪重建流程中使用。
</p>
</sec>
<sec id="s1d">
<label>1.4</label>
<title>图像质量定性评价</title>
<p specific-use="noneIndent">2名具有5年以上肝脏MRI诊断经验的腹部放射科医师独立阅评HASTE
<sub>DLR</sub>、BLADE以及b=800 s/mm² DWI
<sub>DLR、常规</sub>序列。为避免回忆偏倚，所有患者的序列图像以随机顺序呈现给观察者阅评。两位观察者对成像参数、其他MRI序列检查结果以及患者临床信息均设盲。采用5分制评分法对各序列肝缘清晰度、肝内血管及胰腺轮廓清晰度、脂肪抑制均匀性、&gt;5 mm肝脏病灶显影清晰度（5分：优秀；4分：良好；3分：一般；2分：较差，影响诊断；1分：无法诊断）和图像伪影（5分：无伪影；4分：轻度伪影，不影响诊断；3分：中度伪影，不影响诊断；2分：重度伪影，影响诊断；1分：重度伪影，无法诊断）进行评分，以其中高年资医师评分结果为最终评分。两名观察者独立记录所有非肝囊肿局灶性病变数量，最终病灶总数由一名上级医师确定。
</p>
</sec>
<sec id="s1e">
<label>1.5</label>
<title>图像质量定量评价</title>
<p specific-use="noneIndent">在避开伪影区、血管、胆管或局灶性病变前提下，在HASTE
<sub>DLR</sub>、BLADE和b=800 s/mm² DWI
<sub>常规、DLR</sub>序列左、右叶肝实质相同解剖位置放置直径1 cm的圆形感兴趣区（region of interest， ROI），另在局灶性病灶最大径层面（排除肝囊肿病灶）绘制覆盖整个病灶ROI。测量肝脏及病灶SNR、病灶对比噪声比（contrast noise ratio，CNR）和ADC
<sub>常规、DLR</sub>值。由于各序列采用了PI加速成像，噪声并非均匀分布在整个图像上，通过组织信号与背景噪声比进行SNR测量并不准确。因此，在本研究中采用改良SNR和CNR计算公式
<sup>［
<xref ref-type="bibr" rid="R4">4</xref>–
<xref ref-type="bibr" rid="R5">5</xref>］
</sup>：
</p>
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</alternatives>、
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</mml:mrow>
</mml:msub>
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<mml:mrow>
<mml:mi>S</mml:mi>
<mml:msub>
<mml:mrow>
<mml:mi>D</mml:mi>
</mml:mrow>
<mml:mrow>
<mml:mi mathvariant="normal">病灶</mml:mi>
</mml:mrow>
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</mml:mrow>
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</graphic>
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</graphic>
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<alternatives>
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<mml:mi>C</mml:mi>
<mml:mi>N</mml:mi>
<mml:msub>
<mml:mrow>
<mml:mi>R</mml:mi>
</mml:mrow>
<mml:mrow>
<mml:mi mathvariant="normal">病灶</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>=</mml:mo>
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<mml:mrow>
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<mml:mi>S</mml:mi>
<mml:msub>
<mml:mrow>
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<mml:mrow>
<mml:mi mathvariant="normal">病灶</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>-</mml:mo>
<mml:mi>S</mml:mi>
<mml:msub>
<mml:mrow>
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</mml:mrow>
<mml:mrow>
<mml:mi mathvariant="normal">肝脏</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo stretchy="false">|</mml:mo>
</mml:mrow>
<mml:mrow>
<mml:msub>
<mml:mrow>
<mml:mi>N</mml:mi>
</mml:mrow>
<mml:mrow>
<mml:mi mathvariant="normal">临肝</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:mfrac>
</mml:math>
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</graphic>
<graphic specific-use="small" xlink:href="alternativeImage/FD496FFE-0F18-4788-97F2-FD05D1E8DF1C-M003c.jpg"><?fx-imagestate width="36.99933624" height="9.05933285"?>
</graphic>
</alternatives>。
</disp-formula>
<p>肝脏和病灶ROI信号值（signal，SI）
<sub>肝脏、病灶</sub>；肝脏和病灶ROI信号标准差SD
<sub>肝脏、病灶</sub>（standard deviation，SD）； 病灶ROI临近正常局部肝实质信号标准差为噪声（noise，N），获取方式为：在病灶边缘外5~10 mm范围内选取无血管、胆管及伪影干扰的正常肝实质区域，放置3个直径0.5 cm的圆形ROI，测量各ROI信号标准差后取平均值。最终各参数取值为2名观察者测量结果的平均为值。
</p>
</sec>
<sec id="s1f">
<label>1.6</label>
<title>统计学处理</title>
<p specific-use="noneIndent">使用SPSS 21.0软件进行统计学分析。通过组内相关系数 （intraclass correlation coefficient， ICC）评价观察者间定量和定性评分一致性，并对ICC值进行显著性检验（检验水准
<italic>α</italic>=0.05）。一致性强度判断标准为：ICC≤0.4一致性较差，0.4&lt;ICC≤0.75一致性良好，0.75&lt;ICC≤1一致性高。通过Shapiro-Wilk检验评估变量的正态分布情况，正态分布的变量以
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<mml:mover accent="true">
<mml:mi>x</mml:mi>
<mml:mo>¯</mml:mo>
</mml:mover>
</mml:math>
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<graphic specific-use="small" xlink:href="alternativeImage/FD496FFE-0F18-4788-97F2-FD05D1E8DF1C-M004c.jpg"><?fx-imagestate width="1.77800000" height="2.62466669"?>
</graphic>
</alternatives>
</inline-formula>±
<italic>s</italic>表示，非正态分布的变量以
<italic>M </italic>（
<italic>P</italic>
<sub>25</sub>，
<italic>P</italic>
<sub>75</sub>）表示，分别采用配对
<italic>t</italic>检验或Wilcoxon秩和检验。
<italic>P</italic>&lt;0.05为差异有统计学意义。
</p>
</sec>
</sec>
<sec id="s2">
<label>2</label>
<title>结果</title>
<sec id="s2a">
<label>2.1</label>
<title>观察者间一致性检验</title>
<p specific-use="noneIndent">依据术后病理结果、穿刺活检病理或多模态影像学确诊结果，70例患者共计82个局灶性病灶。恶性病灶共计62个：肝细胞癌42个、肝转移瘤13个、肝内胆管细胞癌7个；良性病灶共计20个：肝血管瘤5个、肝硬化结节7个、肝局灶性结节增生8个。两位观察者独立对70例非肝囊肿患者病灶计数，结果均为82个，病灶检出率均为100%。病灶最大层面直径（26.58±21.37）mm。HASTE
<sub>DLR</sub>、BLADE和DWI
<sub>常规、DLR</sub>（b=800 s/mm²）序列图像质量定性评估ICC为0.92~0.97，SNR、CNR和ADC测量结果ICC为0.84~0.88（
<italic>P</italic>&lt;0.001），观察者间评分的一致性良好。
</p>
</sec>
<sec id="s2b">
<label>2.2</label>
<title>图像质量定性评价</title>
<p specific-use="noneIndent">HASTE
<sub>DLR</sub>、DWI
<sub>DLR</sub>与BLADE、DWI
<sub>常规</sub>组图像质量及伪影主观评分对比结果见
<xref ref-type="table" rid="T2">表2</xref>及图
<xref ref-type="fig" rid="F1">1</xref>A-
<xref ref-type="fig" rid="F1">1</xref>D。HASTE
<sub>DLR</sub>组病灶清晰度评分显著高于BLADE组（
<italic>P</italic>=0.048）。HASTE
<sub>DLR</sub>和DWI
<sub>DLR</sub>组图像伪影评分均得以改善（
<italic>P</italic>&lt;0.05）。DWI
<sub>DLR</sub>与DWI
<sub>常规</sub>除伪影外图像质量评价指标均无显著差异。
</p>
<table-wrap id="T2">
<object-id pub-id-type="doi">10.19405/j.cnki.issn1000–1492.2026.05.019.T002</object-id>
<label>表2</label>
<caption>
<p>图像质量定性评估 ［分，
<italic>M </italic>（
<italic>P</italic>
<sub>25</sub>，
<italic>P</italic>
<sub>75</sub>）］
</p>
</caption>
<abstract abstract-type="caption" xml:lang="en">
<label>Tab.2</label>
<title>Qualitative evaluation of image quality ［score， 
<italic>M </italic>（
<italic>P</italic>
<sub>25</sub>，
<italic>P</italic>
<sub>75</sub>）］
</title>
</abstract>
<alternatives>
<table id="Table2">
<thead>
<tr>
<th align="left" style="border-top:solid;border-bottom:solid;">Evaluation indicator</th>
<th align="center" style="border-top:solid;border-bottom:solid;">HASTE
<sub>DLR</sub>
</th>
<th align="center" style="border-top:solid;border-bottom:solid;">BLADE</th>
<th align="center" style="border-top:solid;border-bottom:solid;">
<italic>Z </italic>value
</th>
<th align="center" style="border-top:solid;border-bottom:solid;">
<italic>P </italic>value
</th>
<th align="center" style="border-top:solid;border-bottom:solid;">DWI
<sub>DLR</sub>
<sup>①</sup>
</th>
<th align="center" style="border-top:solid;border-bottom:solid;">DWI
<sub>convention</sub>
<sup>①</sup>
</th>
<th align="center" style="border-top:solid;border-bottom:solid;">
<italic>Z </italic>value
</th>
<th align="center" style="border-top:solid;border-bottom:solid;">
<italic>P </italic>value
</th>
</tr>
</thead>
<tbody>
<tr align="center">
<td align="left">Liver margin clarity</td>
<td align="center">3（2，4）</td>
<td align="center">3（2，4）</td>
<td align="center">-0.51</td>
<td align="center">0.610</td>
<td align="center">4（3，4）</td>
<td align="center">4（3，4）</td>
<td align="center">0.17</td>
<td align="center">0.866</td>
</tr>
<tr align="center">
<td align="left">Intrahepatic vessel clarity</td>
<td align="center">3（2，4）</td>
<td align="center">3（2，4）</td>
<td align="center">-0.33</td>
<td align="center">0.741</td>
<td align="center">4（4，5）</td>
<td align="center">4（4，5）</td>
<td align="center">0.08</td>
<td align="center">0.891</td>
</tr>
<tr align="center">
<td align="left">Pancreas contour clarity</td>
<td align="center">4（4，5）</td>
<td align="center">4（4，5）</td>
<td align="center">-0.12</td>
<td align="center">0.923</td>
<td align="center">3（2，4）</td>
<td align="center">3（2，4）</td>
<td align="center">-0.25</td>
<td align="center">0.803</td>
</tr>
<tr align="center">
<td align="left">Fat suppression uniformity</td>
<td align="center">3（2，4）</td>
<td align="center">3（2，4）</td>
<td align="center">0.29</td>
<td align="center">0.772</td>
<td align="center">4（4，5）</td>
<td align="center">4（4，5）</td>
<td align="center">0.11</td>
<td align="center">0.905</td>
</tr>
<tr align="center">
<td align="left">Lesion clarity</td>
<td align="center">4（4，5）</td>
<td align="center">4（3，4）</td>
<td align="center">-1.98</td>
<td align="center">0.048</td>
<td align="center">3（2，4）</td>
<td align="center">3（2，4）</td>
<td align="center">0.37</td>
<td align="center">0.713</td>
</tr>
<tr align="center">
<td align="left" style="border-bottom:solid;">Artifacts</td>
<td align="center" style="border-bottom:solid;">3（3，4）</td>
<td align="center" style="border-bottom:solid;">3（2，4）</td>
<td align="center" style="border-bottom:solid;">-2.03</td>
<td align="center" style="border-bottom:solid;">0.042</td>
<td align="center" style="border-bottom:solid;">4（4，5）</td>
<td align="center" style="border-bottom:solid;">4（3，4）</td>
<td align="center" style="border-bottom:solid;">-2.01</td>
<td align="center" style="border-bottom:solid;">0.044</td>
</tr>
</tbody>
</table>
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</graphic>
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</graphic>
</alternatives>
<table-wrap-foot>
<fn>
<p>①： DWI refers to images with b=800 s/mm².</p>
</fn>
</table-wrap-foot>
</table-wrap>
<fig position="float" id="F1">
<object-id pub-id-type="doi">10.19405/j.cnki.issn1000–1492.2026.05.019.F001</object-id>
<label>图1</label>
<caption>
<title>男性，56岁，肝硬化伴肝左叶肝细胞性肝癌患者上腹部DLR序列和常规序列图像</title>
</caption>
<abstract abstract-type="caption" xml:lang="en">
<label>Fig.1</label>
<title>Upper abdominal images of a 56-year-old male patient with liver cirrhosis and hepatocellular carcinomain the left lobe of the liver， obtained by DLR sequences and conventional sequences A， B： The HASTEDLR （A） sequence displayed clearer visualization of the liver margin， omentum， lesion edge， and T2WI hyperintense necrotic areas within the lesion compared with the BLADE （B） sequence； C-F： The lesion showed a slightly hyperintense signal on both DWIDLR （C） and DWIconvention （D） sequences at b=800 s/mm²； The ADC value measured by ADCDLR （E） sequence in the ROI （white circle） within the lesion was 1 021.46×10
<sup>-6</sup> mm²/s， which was higher than the value of 1 006.18×10
<sup>-6</sup> mm²/s measured by ADCconvention （F） sequence.
</title>
</abstract>
<alternatives>
<graphic specific-use="print" xlink:href="media/FD496FFE-0F18-4788-97F2-FD05D1E8DF1C-F001.eps" id="Graphic1"><?fx-imagestate width="120.65000153" height="62.44166183"?>
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</graphic>
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</graphic>
</alternatives>
</fig>
</sec>
<sec id="s2c">
<label>2.3</label>
<title>图像质量定量评价</title>
<p specific-use="noneIndent">HASTE
<sub>DLR</sub>、BLADE、DWI
<sub>DLR、常规</sub>组图像质量定量评价对比结果见
<xref ref-type="table" rid="T3">表3</xref>。HASTE
<sub>DLR</sub>组肝实质和病灶SNR以及病灶CNR均高于BLADE组，而DWI
<sub>DLR</sub>组肝右叶肝实质和病灶SNR高于DWI常规组（
<italic>P</italic>&lt;0.05）。此外，DWI
<sub>DLR</sub>组测得肝实质及病灶ADC值高于DWI
<sub>常规</sub>组（
<xref ref-type="table" rid="T4">表4</xref>、
<xref ref-type="fig" rid="F1">图1</xref>E、
<xref ref-type="fig" rid="F1">图1</xref>F）。
</p>
<table-wrap id="T3">
<object-id pub-id-type="doi">10.19405/j.cnki.issn1000–1492.2026.05.019.T003</object-id>
<label>表3</label>
<caption>
<p>图像定量性评估 （
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<mml:mover accent="true">
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</graphic>
</alternatives>
</inline-formula>±
<italic>s</italic>）
</p>
</caption>
<abstract abstract-type="caption" xml:lang="en">
<label>Tab.3</label>
<title>Quantitative evaluation of image quality （
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<mml:mover accent="true">
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<mml:mo>¯</mml:mo>
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</graphic>
</alternatives>
</inline-formula>±
<italic>s</italic>）
</title>
</abstract>
<alternatives>
<table id="Table3">
<thead>
<tr>
<th align="left" style="border-top:solid;border-bottom:solid;">Evaluation indicators</th>
<th align="center" style="border-top:solid;border-bottom:solid;">HASTE
<sub>DLR</sub>
</th>
<th align="center" style="border-top:solid;border-bottom:solid;">BLADE</th>
<th align="center" style="border-top:solid;border-bottom:solid;">
<italic>t </italic>value
</th>
<th align="center" style="border-top:solid;border-bottom:solid;">
<italic>P </italic>value
</th>
<th align="center" style="border-top:solid;border-bottom:solid;">DWI
<sub>DLR</sub>
<sup>①</sup>
</th>
<th align="center" style="border-top:solid;border-bottom:solid;">DWI
<sub>conventionl</sub>
<sup>①</sup>
</th>
<th align="center" style="border-top:solid;border-bottom:solid;">
<italic>t </italic>value
</th>
<th align="center" style="border-top:solid;border-bottom:solid;">
<italic>P </italic>value
</th>
</tr>
</thead>
<tbody>
<tr align="center">
<td align="left">Left hepatic lobe SNR</td>
<td align="center">13.83±2.48</td>
<td align="center">12.25±4.35</td>
<td align="center">2.601</td>
<td align="center">0.010</td>
<td align="center">13.28±1.47</td>
<td align="center">12.73±2.45</td>
<td align="center">1.545</td>
<td align="center">0.124</td>
</tr>
<tr align="center">
<td align="left">Right hepatic lobe SNR</td>
<td align="center">14.06±4.24</td>
<td align="center">12.37±5.03</td>
<td align="center">2.150</td>
<td align="center">0.033</td>
<td align="center">13.84±3.80</td>
<td align="center">12.61±2.82</td>
<td align="center">2.134</td>
<td align="center">0.034</td>
</tr>
<tr align="center">
<td align="left">Lesion SNR</td>
<td align="center">10.46±5.46</td>
<td align="center">9.57±6.14</td>
<td align="center">2.082</td>
<td align="center">0.039</td>
<td align="center">9.83±4.38</td>
<td align="center">8.52±2.56</td>
<td align="center">2.234</td>
<td align="center">0.021</td>
</tr>
<tr align="center">
<td align="left" style="border-bottom:solid;">Lesion CNR</td>
<td align="center" style="border-bottom:solid;">5.26±1.28</td>
<td align="center" style="border-bottom:solid;">4.70±2.12</td>
<td align="center" style="border-bottom:solid;">2.037</td>
<td align="center" style="border-bottom:solid;">0.043</td>
<td align="center" style="border-bottom:solid;">5.85±2.78</td>
<td align="center" style="border-bottom:solid;">5.26±1.23</td>
<td align="center" style="border-bottom:solid;">1.750</td>
<td align="center" style="border-bottom:solid;">0.082</td>
</tr>
</tbody>
</table>
<graphic specific-use="big" xlink:href="alternativeImage/FD496FFE-0F18-4788-97F2-FD05D1E8DF1C-T003.jpg"><?fx-imagestate width="169.80001831" height="23.17599869"?>
</graphic>
<graphic specific-use="small" xlink:href="alternativeImage/FD496FFE-0F18-4788-97F2-FD05D1E8DF1C-T003c.jpg"><?fx-imagestate width="169.80001831" height="23.17599869"?>
</graphic>
</alternatives>
<table-wrap-foot>
<fn>
<p>①： DWI refers to images with b=800 s/mm².</p>
</fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="T4">
<object-id pub-id-type="doi">10.19405/j.cnki.issn1000–1492.2026.05.019.T004</object-id>
<label>表4</label>
<caption>
<p>DWI
<sub>DLR</sub>和DWI
<sub>常规</sub>测量ADC值（10
<sup>-6</sup>mm
<sup>2</sup>/s）对比
</p>
</caption>
<abstract abstract-type="caption" xml:lang="en">
<label>Tab.4</label>
<title>Comparison of ADC values measured by DWI
<sub>DLR</sub> and DWI
<sub>conventionl</sub> （10
<sup>-6</sup> mm²/s）
</title>
</abstract>
<alternatives>
<table id="Table4">
<thead>
<tr>
<th align="left" style="border-top:solid;border-bottom:solid;">Measurement location</th>
<th align="center" style="border-top:solid;border-bottom:solid;">DWI
<sub>DLR</sub>
<sup>①</sup>
</th>
<th align="center" style="border-top:solid;border-bottom:solid;">DWI
<sub>convention</sub>
<sup>①</sup>
</th>
<th align="center" style="border-top:solid;border-bottom:solid;">
<italic>t </italic>value
</th>
<th align="center" style="border-top:solid;border-bottom:solid;">
<italic>P </italic>value
</th>
</tr>
</thead>
<tbody>
<tr align="center">
<td align="left">Left Hepatic Lobe</td>
<td align="center">1 086.51±162.41</td>
<td align="center">1 007.83±115.92</td>
<td align="center">5.085</td>
<td align="center">&lt;0.001</td>
</tr>
<tr align="center">
<td align="left">Right Hepatic Lobe</td>
<td align="center">1 128.62±146.57</td>
<td align="center">995.16±204.35</td>
<td align="center">8.243</td>
<td align="center">&lt;0.001</td>
</tr>
<tr align="center">
<td align="left" style="border-bottom:solid;">Lesion</td>
<td align="center" style="border-bottom:solid;">974.54±224.36</td>
<td align="center" style="border-bottom:solid;">837.94±188.51</td>
<td align="center" style="border-bottom:solid;">7.892</td>
<td align="center" style="border-bottom:solid;">&lt;0.001</td>
</tr>
</tbody>
</table>
<graphic specific-use="big" xlink:href="alternativeImage/FD496FFE-0F18-4788-97F2-FD05D1E8DF1C-T004.jpg"><?fx-imagestate width="169.79998779" height="19.20000076"?>
</graphic>
<graphic specific-use="small" xlink:href="alternativeImage/FD496FFE-0F18-4788-97F2-FD05D1E8DF1C-T004c.jpg"><?fx-imagestate width="169.79998779" height="19.20000076"?>
</graphic>
</alternatives>
<table-wrap-foot>
<fn>
<p>①： DWI refers to images with b=800 s/mm².</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
</sec>
<sec id="s3">
<label>3</label>
<title>讨论</title>
<p>HASTE和DWI序列是肝脏局灶性病变检测与定性的核心MRI技术，但在临床实践中，如何平衡图像质量与扫描耗时始终是一大挑战。传统单次激发HASTE序列常因回波链较长导致模糊效应与SNR下降，常规DWI序列易受磁敏感伪影及加速技术导致SNR受损的影响，而传统BLADE序列虽能改善SNR与运动伪影，但耗时较长
<sup> ［
<xref ref-type="bibr" rid="R6">6</xref>］
</sup>。近年来，DLR技术通过整合k空间数据约束与图像正则化，能够在缩短扫描时间的同时重建高SNR图像，为平衡成像效率与质量提供了新路径
<sup>［
<xref ref-type="bibr" rid="R7">7</xref>–
<xref ref-type="bibr" rid="R8">8</xref>］
</sup>。
</p>
<p>该研究证实了DLR技术能显著提升肝脏磁共振成像的整体效能与图像质量。针对HASTE序列的分析表明，引入DLR技术不仅将扫描时间缩短了92.63%，同时有效改善了图像伪影并提升了SNR与CNR。HASTE
<sub>DLR</sub>在病灶清晰度上表现出显著优势，印证了DLR对快速序列固有缺陷的补偿作用，与Kubicka et al
<sup>［
<xref ref-type="bibr" rid="R9">9</xref>］
</sup>的研究结论一致，后者指出HASTEDLR对胆管、胰管等小结构的显示更为清晰，且显著减少了采集时间。尽管Herrmann et al
<sup>［
<xref ref-type="bibr" rid="R10">10</xref>］
</sup>曾得出BLADE序列SNR更高的结论， 但这可能与扫描层厚的差异（其采用5 mm 
<italic>vs</italic> 该研究3 mm）及模型训练数据量有关。在3 mm薄层扫描条件下，神经网络能够更高效地实现噪声抑制与信号增强
<sup>［
<xref ref-type="bibr" rid="R9">9</xref>］
</sup>。此外，Shanbhogue et al
<sup>［
<xref ref-type="bibr" rid="R3">3</xref>］
</sup>的研究亦证实，DLR带来的信号强度变化实为脂肪抑制优化的合理结果，反而有助于增强肝-脂对比度与小病灶的检出灵敏度。Ginocchio et al
<sup>［
<xref ref-type="bibr" rid="R11">11</xref>］
</sup>在3.0T设备上的研究也支持了这一点，证实HASTE
<sub>DLR</sub>的肝缘、血管锐利度显著优于标准序列，且扫描时间缩短一半，与该研究的发现高度吻合。
</p>
<p>在DWI成像方面，DWI
<sub>DLR</sub>序列在将扫描耗时减半的同时提升了肝右叶的SNR 。这一表现与Afat et al
<sup>［
<xref ref-type="bibr" rid="R12">12</xref>］
</sup>的研究高度契合：肝左叶易受心脏跳动干扰，DLR加速扫描虽可能导致局部信号出现不均匀，但整体噪声依然更低。关于ADC值的测量，该研究观察到DWI
<sub>DLR</sub>测得的ADC值普遍高于常规DWI ，这可能与降噪处理及信号均匀性的提升有关；然而Bae et al
<sup>［
<xref ref-type="bibr" rid="R13">13</xref>］
</sup>却得出相反结论，提示ADC值的变异性可能受到脂肪抑制技术、并行加速因子及呼吸模式等多重参数的共同影响
<sup>［
<xref ref-type="bibr" rid="R14">14</xref>–
<xref ref-type="bibr" rid="R16">16</xref>］
</sup>。此外，DLR重建固有的“平滑效应”也可能系统性地高估ADC值。鉴于ADC值在疾病鉴别与疗效评估中的核心地位，后续亟需针对DLR对其变异性的影响机制展开专门研究。
</p>
<p>本研究存在一定的局限性。首先，作为单中心研究，样本来源集中，可能存在选择偏倚导致结果外推性受限，且样本量相对较小，可能影响统计检验效能。其次，本研究纳入多种良恶性病灶，其生物学特性与信号特征差异可能干扰定量指标一致性，降低数据稳定性，进而可能引入潜在偏差，影响组间对比的可靠性。此外，部分良性病灶缺乏病理活检佐证，可能导致定性偏差。最后，本研究未深入探讨ADC值差异的内在机制（如重建算法、扫描参数设置等对扩散信号的影响），后续需针对性研究阐明。</p>
<p>综上所述，DLR技术在提升肝脏MRI扫描效率、改善图像质量和减少伪影方面具有广阔的临床前景。</p>
</sec>
</body>
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