1.Hemodynamical Assessment of Cavernous Hemangioma in Cavernous Sinus Using MR-DSA and Conventional DSA.
Yong Woon SHIM ; Tae Sub CHUNG ; Won Suk KANG ; Kyu Sung LEE ; Ralph STRECKER ; Juergen HENNIG
Yonsei Medical Journal 2003;44(5):908-914
We report a hemodynamical assessment of the blood turnover pattern as well as the imaging of cavernous hemangioma in a cavernous sinus using time-resolved contrast enhanced 2D projection MRA, also known as MR-DSA, and conventional digital subtraction angiography (DSA), before and after radiotherapy. MR-DSA showed very fast dynamical images of a contrast turnover pattern and was well matched with the findings obtained from DSA. MR-DSA is a non-invasive study, and can replace DSA in examining a vascular tumor for the initial work-up and follow-up examination.
Angiography, Digital Subtraction/*methods
;
Cavernous Sinus/*radiography
;
Female
;
Hemangioma, Cavernous/*radiography
;
*Hemodynamic Processes
;
Human
;
Magnetic Resonance Angiography
;
Middle Aged
2.Non-Invasive Follow-up Evaluation of Post-Embolized AVM with Time-Resolved MRA: A Case Report.
Yong Woon SHIM ; Tae Sub CHUNG ; Won Suk KANG ; Jin Yang JOO ; Ralph STRECKER ; Juergen HENNIG
Korean Journal of Radiology 2002;3(4):271-275
We report the hemodynamic assessment in a patient with cerebral arteriovenous malformation using time-resolved magnetic resonance angiography (TRMRA), a non-invasive modality, and catheter-based digital subtraction angiography (DSA), before and after embolization. Comparison of the results showed that TR-MRA produced very fast dynamic images and the findings closely matched those obtained at DSA. For initial work-up and follow-up studies in patients with vascular lesions, TR-MRA and DSA are therefore comparable.
Adult
;
Angiography, Digital Subtraction
;
Case Report
;
Cerebrovascular Circulation
;
Comparative Study
;
*Embolization, Therapeutic
;
Follow-Up Studies
;
Human
;
Intracranial Arteriovenous
;
Malformations/diagnosis/physiopathology/*therapy
;
*Magnetic Resonance Angiography
;
Male
;
Support, Non-U.S. Gov't
;
Time Factors
3.Faster Acquisition and Improved Image Quality of T2-Weighted Dixon Breast MRI at 3T Using Deep Learning:A Prospective Study
Caroline WILPERT ; Hannah SCHNEIDER ; Alexander RAU ; Maximilian Frederic RUSSE ; Benedict OERTHER ; Ralph STRECKER ; Marcel Dominic NICKEL ; Elisabeth WEILAND ; Alexa HAEGER ; Matthias BENNDORF ; Thomas MAYRHOFER ; Jakob WEISS ; Fabian BAMBERG ; Marisa WINDFUHR-BLUM ; Jakob NEUBAUER
Korean Journal of Radiology 2025;26(1):29-42
Objective:
The aim of this study was to compare image quality features and lesion characteristics between a faster deep learning (DL) reconstructed T2-weighted (T2-w) fast spin-echo (FSE) Dixon sequence with super-resolution (T2DL) and a conventional T2-w FSE Dixon sequence (T2STD) for breast magnetic resonance imaging (MRI).
Materials and Methods:
This prospective study was conducted between November 2022 and April 2023 using a 3T scanner.Both T2DL and T2STD sequences were acquired for each patient. Quantitative analysis was based on region-of-interest (ROI) measurements of signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Qualitative analysis was performed independently by two radiologists using Likert scales to evaluate various image quality features, morphology, and diagnostic confidence for cysts and breast cancers. Reader preference between T2DL and T2STD was assessed via side-by-side comparison, and inter-reader reliability was also analyzed.
Results:
Total of 151 women were enrolled, with 140 women (mean age: 52 ± 14 years; 85 cysts and 31 breast cancers) included in the final analysis. The acquisition time was 110 s ± 0 for T2DL compared to 266 s ± 0 for T2STD. SNR and CNR were significantly higher in T2DL (P < 0.001). T2DL was associated with higher image quality scores, reduced noise, and fewer artifacts (P < 0.001). All evaluated anatomical regions (breast and axilla), breast implants, and bone margins were rated higher in T2DL (P ≤ 0.008), except for bone marrow, which scored higher in T2STD (P < 0.001). Scores for conspicuity, sharpness/ margins, and microstructure of cysts and breast cancers were higher in T2DL (P ≤ 0.002). Diagnostic confidence for cysts was improved with T2DL (P < 0.001). Readers significantly preferred T2DL over T2STD in side-by-side comparisons (P < 0.001).
Conclusion
T2DL effectively corrected for SNR loss caused by accelerated image acquisition and provided a 58% reduction in acquisition time compared to T2STD. This led to fewer artifacts and improved overall image quality. Thus, T2DL is feasible and has the potential to replace conventional T2-w sequences for breast MRI examinations.
4.Faster Acquisition and Improved Image Quality of T2-Weighted Dixon Breast MRI at 3T Using Deep Learning:A Prospective Study
Caroline WILPERT ; Hannah SCHNEIDER ; Alexander RAU ; Maximilian Frederic RUSSE ; Benedict OERTHER ; Ralph STRECKER ; Marcel Dominic NICKEL ; Elisabeth WEILAND ; Alexa HAEGER ; Matthias BENNDORF ; Thomas MAYRHOFER ; Jakob WEISS ; Fabian BAMBERG ; Marisa WINDFUHR-BLUM ; Jakob NEUBAUER
Korean Journal of Radiology 2025;26(1):29-42
Objective:
The aim of this study was to compare image quality features and lesion characteristics between a faster deep learning (DL) reconstructed T2-weighted (T2-w) fast spin-echo (FSE) Dixon sequence with super-resolution (T2DL) and a conventional T2-w FSE Dixon sequence (T2STD) for breast magnetic resonance imaging (MRI).
Materials and Methods:
This prospective study was conducted between November 2022 and April 2023 using a 3T scanner.Both T2DL and T2STD sequences were acquired for each patient. Quantitative analysis was based on region-of-interest (ROI) measurements of signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Qualitative analysis was performed independently by two radiologists using Likert scales to evaluate various image quality features, morphology, and diagnostic confidence for cysts and breast cancers. Reader preference between T2DL and T2STD was assessed via side-by-side comparison, and inter-reader reliability was also analyzed.
Results:
Total of 151 women were enrolled, with 140 women (mean age: 52 ± 14 years; 85 cysts and 31 breast cancers) included in the final analysis. The acquisition time was 110 s ± 0 for T2DL compared to 266 s ± 0 for T2STD. SNR and CNR were significantly higher in T2DL (P < 0.001). T2DL was associated with higher image quality scores, reduced noise, and fewer artifacts (P < 0.001). All evaluated anatomical regions (breast and axilla), breast implants, and bone margins were rated higher in T2DL (P ≤ 0.008), except for bone marrow, which scored higher in T2STD (P < 0.001). Scores for conspicuity, sharpness/ margins, and microstructure of cysts and breast cancers were higher in T2DL (P ≤ 0.002). Diagnostic confidence for cysts was improved with T2DL (P < 0.001). Readers significantly preferred T2DL over T2STD in side-by-side comparisons (P < 0.001).
Conclusion
T2DL effectively corrected for SNR loss caused by accelerated image acquisition and provided a 58% reduction in acquisition time compared to T2STD. This led to fewer artifacts and improved overall image quality. Thus, T2DL is feasible and has the potential to replace conventional T2-w sequences for breast MRI examinations.
5.Faster Acquisition and Improved Image Quality of T2-Weighted Dixon Breast MRI at 3T Using Deep Learning:A Prospective Study
Caroline WILPERT ; Hannah SCHNEIDER ; Alexander RAU ; Maximilian Frederic RUSSE ; Benedict OERTHER ; Ralph STRECKER ; Marcel Dominic NICKEL ; Elisabeth WEILAND ; Alexa HAEGER ; Matthias BENNDORF ; Thomas MAYRHOFER ; Jakob WEISS ; Fabian BAMBERG ; Marisa WINDFUHR-BLUM ; Jakob NEUBAUER
Korean Journal of Radiology 2025;26(1):29-42
Objective:
The aim of this study was to compare image quality features and lesion characteristics between a faster deep learning (DL) reconstructed T2-weighted (T2-w) fast spin-echo (FSE) Dixon sequence with super-resolution (T2DL) and a conventional T2-w FSE Dixon sequence (T2STD) for breast magnetic resonance imaging (MRI).
Materials and Methods:
This prospective study was conducted between November 2022 and April 2023 using a 3T scanner.Both T2DL and T2STD sequences were acquired for each patient. Quantitative analysis was based on region-of-interest (ROI) measurements of signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Qualitative analysis was performed independently by two radiologists using Likert scales to evaluate various image quality features, morphology, and diagnostic confidence for cysts and breast cancers. Reader preference between T2DL and T2STD was assessed via side-by-side comparison, and inter-reader reliability was also analyzed.
Results:
Total of 151 women were enrolled, with 140 women (mean age: 52 ± 14 years; 85 cysts and 31 breast cancers) included in the final analysis. The acquisition time was 110 s ± 0 for T2DL compared to 266 s ± 0 for T2STD. SNR and CNR were significantly higher in T2DL (P < 0.001). T2DL was associated with higher image quality scores, reduced noise, and fewer artifacts (P < 0.001). All evaluated anatomical regions (breast and axilla), breast implants, and bone margins were rated higher in T2DL (P ≤ 0.008), except for bone marrow, which scored higher in T2STD (P < 0.001). Scores for conspicuity, sharpness/ margins, and microstructure of cysts and breast cancers were higher in T2DL (P ≤ 0.002). Diagnostic confidence for cysts was improved with T2DL (P < 0.001). Readers significantly preferred T2DL over T2STD in side-by-side comparisons (P < 0.001).
Conclusion
T2DL effectively corrected for SNR loss caused by accelerated image acquisition and provided a 58% reduction in acquisition time compared to T2STD. This led to fewer artifacts and improved overall image quality. Thus, T2DL is feasible and has the potential to replace conventional T2-w sequences for breast MRI examinations.
6.Faster Acquisition and Improved Image Quality of T2-Weighted Dixon Breast MRI at 3T Using Deep Learning:A Prospective Study
Caroline WILPERT ; Hannah SCHNEIDER ; Alexander RAU ; Maximilian Frederic RUSSE ; Benedict OERTHER ; Ralph STRECKER ; Marcel Dominic NICKEL ; Elisabeth WEILAND ; Alexa HAEGER ; Matthias BENNDORF ; Thomas MAYRHOFER ; Jakob WEISS ; Fabian BAMBERG ; Marisa WINDFUHR-BLUM ; Jakob NEUBAUER
Korean Journal of Radiology 2025;26(1):29-42
Objective:
The aim of this study was to compare image quality features and lesion characteristics between a faster deep learning (DL) reconstructed T2-weighted (T2-w) fast spin-echo (FSE) Dixon sequence with super-resolution (T2DL) and a conventional T2-w FSE Dixon sequence (T2STD) for breast magnetic resonance imaging (MRI).
Materials and Methods:
This prospective study was conducted between November 2022 and April 2023 using a 3T scanner.Both T2DL and T2STD sequences were acquired for each patient. Quantitative analysis was based on region-of-interest (ROI) measurements of signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Qualitative analysis was performed independently by two radiologists using Likert scales to evaluate various image quality features, morphology, and diagnostic confidence for cysts and breast cancers. Reader preference between T2DL and T2STD was assessed via side-by-side comparison, and inter-reader reliability was also analyzed.
Results:
Total of 151 women were enrolled, with 140 women (mean age: 52 ± 14 years; 85 cysts and 31 breast cancers) included in the final analysis. The acquisition time was 110 s ± 0 for T2DL compared to 266 s ± 0 for T2STD. SNR and CNR were significantly higher in T2DL (P < 0.001). T2DL was associated with higher image quality scores, reduced noise, and fewer artifacts (P < 0.001). All evaluated anatomical regions (breast and axilla), breast implants, and bone margins were rated higher in T2DL (P ≤ 0.008), except for bone marrow, which scored higher in T2STD (P < 0.001). Scores for conspicuity, sharpness/ margins, and microstructure of cysts and breast cancers were higher in T2DL (P ≤ 0.002). Diagnostic confidence for cysts was improved with T2DL (P < 0.001). Readers significantly preferred T2DL over T2STD in side-by-side comparisons (P < 0.001).
Conclusion
T2DL effectively corrected for SNR loss caused by accelerated image acquisition and provided a 58% reduction in acquisition time compared to T2STD. This led to fewer artifacts and improved overall image quality. Thus, T2DL is feasible and has the potential to replace conventional T2-w sequences for breast MRI examinations.
7.Faster Acquisition and Improved Image Quality of T2-Weighted Dixon Breast MRI at 3T Using Deep Learning:A Prospective Study
Caroline WILPERT ; Hannah SCHNEIDER ; Alexander RAU ; Maximilian Frederic RUSSE ; Benedict OERTHER ; Ralph STRECKER ; Marcel Dominic NICKEL ; Elisabeth WEILAND ; Alexa HAEGER ; Matthias BENNDORF ; Thomas MAYRHOFER ; Jakob WEISS ; Fabian BAMBERG ; Marisa WINDFUHR-BLUM ; Jakob NEUBAUER
Korean Journal of Radiology 2025;26(1):29-42
Objective:
The aim of this study was to compare image quality features and lesion characteristics between a faster deep learning (DL) reconstructed T2-weighted (T2-w) fast spin-echo (FSE) Dixon sequence with super-resolution (T2DL) and a conventional T2-w FSE Dixon sequence (T2STD) for breast magnetic resonance imaging (MRI).
Materials and Methods:
This prospective study was conducted between November 2022 and April 2023 using a 3T scanner.Both T2DL and T2STD sequences were acquired for each patient. Quantitative analysis was based on region-of-interest (ROI) measurements of signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Qualitative analysis was performed independently by two radiologists using Likert scales to evaluate various image quality features, morphology, and diagnostic confidence for cysts and breast cancers. Reader preference between T2DL and T2STD was assessed via side-by-side comparison, and inter-reader reliability was also analyzed.
Results:
Total of 151 women were enrolled, with 140 women (mean age: 52 ± 14 years; 85 cysts and 31 breast cancers) included in the final analysis. The acquisition time was 110 s ± 0 for T2DL compared to 266 s ± 0 for T2STD. SNR and CNR were significantly higher in T2DL (P < 0.001). T2DL was associated with higher image quality scores, reduced noise, and fewer artifacts (P < 0.001). All evaluated anatomical regions (breast and axilla), breast implants, and bone margins were rated higher in T2DL (P ≤ 0.008), except for bone marrow, which scored higher in T2STD (P < 0.001). Scores for conspicuity, sharpness/ margins, and microstructure of cysts and breast cancers were higher in T2DL (P ≤ 0.002). Diagnostic confidence for cysts was improved with T2DL (P < 0.001). Readers significantly preferred T2DL over T2STD in side-by-side comparisons (P < 0.001).
Conclusion
T2DL effectively corrected for SNR loss caused by accelerated image acquisition and provided a 58% reduction in acquisition time compared to T2STD. This led to fewer artifacts and improved overall image quality. Thus, T2DL is feasible and has the potential to replace conventional T2-w sequences for breast MRI examinations.